JP6283637B2 - Thermal transmissivity estimation system, thermal transmissivity estimation device, and thermal transmissivity estimation program - Google Patents

Description

  The present invention relates to a heat transmissibility estimation system, apparatus, and program for estimating the heat transmissivity of a surface member as an index representing the heat insulation performance of the surface member located between an indoor space and an outdoor space of a building.

The thermal insulation performance of a building can be evaluated by estimating the heat loss coefficient of the building. The heat loss coefficient is expressed as a value (Q value) obtained by dividing the amount of heat (W / K) escaping from the building by the total floor area (m ² ). The amount of heat escaping from the building is determined as the total amount of heat escaping from the part (outer wall, first floor, etc.) facing the outdoor space (including the underfloor space and the shed space). Further, the amount of heat escaping from each part is calculated based on the area of the part and the heat transmissibility.

  In order to obtain the heat loss coefficient of a building, for example, in Japanese Patent Laid-Open No. 2013-221774 (Patent Document 1), the temperature of each room of the building and the temperature outside the building are continuously measured, and the average temperature of the entire building and the outside A method has been proposed in which an average temperature of a room in contact with the air is obtained and a heat loss coefficient is estimated according to a heat transfer model in which the two average temperatures have a certain relationship.

  Moreover, in order to obtain | require the heat | fever transmissivity of the outer wall etc. of a building, in Unexamined-Japanese-Patent No. 2014-074953 (patent document 2), for example, the heat | fever transmissivity of an outer wall, the heat conductivity according to the outer wall type, outer wall thickness, A method is disclosed in which the thermal conductivity of the heat insulating material on the outer wall and the outer wall heat insulating material thickness are calculated by substituting them into the outer wall thermal conductivity calculation formula.

JP 2013-221772 A JP 2014-074953 A

  Like patent document 1, in order to estimate the heat loss coefficient of a building, much time and equipment (thermometer) are needed. In addition, if the temperature difference is not large, the estimation error may increase.

  Moreover, in patent document 2, since it is a premise that the thermal conductivity of the target part (for example, the outer wall) is stored in advance, if the thermal conductivity of the target part is unknown, the thermal conductivity is It cannot be calculated.

  The present invention has been made in order to solve the above-described problems, and its object is to easily and quickly estimate the heat transmissivity of the target portion (surface member). An estimation system, apparatus, and program are provided.

  A thermal conductivity estimation system according to an aspect of the present invention is a system for estimating the thermal conductivity of a surface member as an index representing the heat insulation performance of the surface member located between the indoor space and the outdoor space of the building. A plate-like member having a surface in contact with or close to the indoor surface of the surface member and a back surface located on the opposite side, and a heater provided on the back surface side of the plate-like member for heating the indoor surface of the surface member; And a first temperature sensor that is provided on the surface side of the plate member and detects the indoor surface temperature of the surface member. Also, in the process of changing the indoor surface temperature of the surface member due to the heating of the heater, the convergence value of the approximate curve is calculated based on the actual measurement value obtained from the first temperature sensor with the back surface temperature of the plate member being constant. Predicting processing means for predicting the stable temperature of the indoor surface of the surface member, stable temperature predicted by the prediction processing means, outdoor temperature of the surface member, back surface temperature of the plate member, and plate shape And an estimation means for estimating the thermal conductivity of the surface member based on the thermal conductivity of the member.

The prediction processing unit includes a calculation unit, a comparison unit, and a determination unit. Calculating means, the specified point in the change process of the indoor surface temperature of the surface member and x = 0 of the approximate curve, the measured value at a particular point in time in the case of a y _0,
y = − (b−y ₀ ) a ^x + b, or
y = (b−y ₀ ) a ^x + b
Assuming that the unknown a in the equation expressed as is an arbitrary value less than 1, the unknown b as a convergence value is based on the hypothesized value of the unknown a and the measured value at the first time after the specific time. Calculate provisional values. The comparison unit compares the actual measurement value at the second time point after the first time point with the predicted value at the second time point based on the provisional value calculated by the calculation unit. The determination means determines, as a convergence value, a provisional value used for calculation of a predicted value determined to be the same as the actual measurement value as a result of comparison by the comparison means.

  Preferably, the calculation unit repeats the change of the assumed value of the unknown a and the calculation of the provisional value until it is determined that the actually measured value and the predicted value at the second time point are the same.

  The prediction processing means includes an abnormality determination means for determining whether or not the convergence value determined by the determination means is an abnormal value, and at least one of the first time point and the second time point when the abnormality determination means determines that the convergence value is an abnormal value. It is desirable to further include recalculating means for recalculating the convergence value by changing.

  Preferably, the heat transmissivity estimation system is provided on the back surface side of the plate member, and the second temperature sensor for detecting the back surface temperature of the plate member and the back surface temperature of the plate member become the set temperature. And a heating control means for performing a constant temperature control of the heater. It is desirable that the specific time point described above corresponds to a time point when the back surface side temperature of the plate-like member is stabilized at a constant temperature.

  The heat transmissivity estimation system may further include a sub-heater provided on the surface side of the plate member in order to transfer heat directly to the surface member. In this case, it is desirable that the heating control means operates the sub-heater only for a specific period from the start of heating so that the indoor surface temperature of the surface member rises rapidly.

  A thermal conductivity estimation device according to another aspect of the present invention is an estimation device for estimating the thermal conductivity of a surface member as an index representing the heat insulation performance of the surface member located between the indoor space and the outdoor space of the building. And it is provided with a memory | storage means, a prediction process means, and an estimation means. A memory | storage means memorize | stores the outdoor side temperature of a surface member, the back surface side temperature of the plate-shaped member arrange | positioned so that it may contact | abut to or adjoins the indoor surface of a surface member, and the heat transmissivity of a plate-shaped member. The prediction processing means determines the convergence value of the approximate curve based on the measured value of the indoor surface temperature of the surface member obtained when the back surface temperature of the plate member is constant in the process of changing the indoor surface temperature of the surface member. Is calculated, the stable temperature of the indoor surface of the surface member is predicted. The estimation means is based on the stable temperature predicted by the prediction processing means, the outdoor temperature of the surface member stored in the storage means, the back surface temperature of the plate member, and the thermal conductivity of the plate member. Estimate the thermal conductivity of the face member. Similar to the above-described heat transmissibility estimation system, the prediction processing means includes a calculation means, a comparison means, and a determination means.

A thermal conductivity estimation program according to still another aspect of the present invention is a program for estimating the thermal conductivity of a surface member as an index representing the thermal insulation performance of the surface member located between the indoor space and the outdoor space of the building. Then, the step of acquiring the indoor surface temperature of the surface member in a state where the indoor surface of the surface member is heated, and the specific time in the process of changing the indoor surface temperature of the surface member is set to x = 0 of the approximate curve, When the measured value is y0,
y = − (b−y ₀ ) a ^x + b, or
y = (b−y ₀ ) a ^x + b
Assuming that the unknown a of the equation expressed as is an arbitrary value less than 1, the assumed value of the unknown a, and the measured value at the first time point after the specific time point, the convergence value of the approximate curve A step of calculating a provisional value of the unknown b as: a step of comparing an actual measurement value at a second time point after the first time point with a predicted value at a second time point based on the calculated provisional value; As a result, the provisional value used to calculate the predicted value determined to be the same as the actual measurement value is determined as the convergence value, and the convergence value is predicted as the stable temperature of the indoor surface of the surface member. And causing the computer to execute a step of estimating the thermal conductivity of the face member.

  According to the present invention, it is possible to estimate the thermal conductivity of the surface member in a simple and short time.

It is a figure which shows typically the structure of the heat transmissivity estimation system which concerns on embodiment of this invention. It is a disassembled perspective view of the thermal conductivity test apparatus main body which concerns on embodiment of this invention. It is a block diagram showing an example of composition of a heat transmissivity estimating system concerning an embodiment of the invention. In embodiment of this invention, it is a figure which shows notionally the estimation principle of the heat-transfer rate of a surface member. In embodiment of this invention, it is a graph which shows the typical example of the time transition of the surface side temperature of a plate-shaped member, and a back surface side temperature. In embodiment of this invention, it is a graph for demonstrating the prediction process of the stable temperature of the surface side of a plate-shaped member. In an embodiment of the invention, it is a graph which shows an example of a prediction formula which can be created at the 1st time. In embodiment of this invention, it is a graph of a prediction formula in case the actual value obtained in a 2nd time is smaller than a predicted value. In embodiment of this invention, it is a graph of a prediction formula in case there exist more actual measurement values obtained in a 2nd time than a predicted value. In embodiment of this invention, it is a graph of a prediction formula in case the actual measurement value and prediction value which are obtained at the 2nd time are the same. It is a flowchart which shows the heat transmissivity measurement process in embodiment of this invention. It is a flowchart which shows the stable temperature prediction process in embodiment of this invention. It is a flowchart which shows the stable temperature prediction process in embodiment of this invention. It is a figure for demonstrating the process of step S48 of FIG. It is a flowchart which shows an example of the recalculation process of step S56 of FIG. It is a figure for demonstrating the recalculation process of FIG. It is a flowchart which shows the other example of the recalculation process of step S56 of FIG. It is a figure for demonstrating the recalculation process of FIG. It is a disassembled perspective view of the thermal conductivity test apparatus main body which concerns on the modification of embodiment of this invention. It is a block diagram which shows the structural example of the heat transmissivity estimation system which concerns on the modification of embodiment of this invention. In the modification of embodiment of this invention, it is a figure which shows typically the arrangement | positioning relationship between a heat | fever permeability test apparatus main body and a surface member. It is a figure which shows typically the example of arrangement | positioning of a temperature sensor in the thermal conductivity test apparatus main body which concerns on the modification of embodiment of this invention. It is a figure which shows typically the example of a structure of an apparatus in case the heat-transfer coefficient estimation system which concerns on embodiment of this invention is comprised as a single apparatus. As a comparative example, it is a graph showing a specific example of the time required for measurement of the heat transmissivity when a surface member having a relatively large heat capacity is targeted and the heater is set to a constant output. A typical example of the time transition of the temperature of the position is shown, and the graph of (B) shows the relationship between the thermal conductivity (estimated U value) of the face member and the true value.

  Embodiments of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and description thereof will not be repeated.

  In the present embodiment, a heat transmissivity estimation system that estimates the heat transmissivity of a surface member as an index representing the heat insulation performance of the surface member located between the indoor space and the outdoor space of the building will be described. The surface member to be evaluated for heat insulation performance includes an outer wall, a floor on the first floor, a ceiling on the top floor, and the like, and the outdoor space includes an under-floor space and a shed space. The surface member is not limited to a single-layer member, and may be a member composed of a plurality of layers.

(About schematic configuration)
First, a schematic configuration of the heat transmissivity estimation system according to the present embodiment will be described. Referring to FIG. 1, a thermal transmissivity estimation system 1 includes a thermal transmissivity test apparatus (hereinafter abbreviated as “test apparatus”) 10 attached to a surface member (hereinafter also referred to as “object”) 80 to be evaluated, An estimation apparatus 13 that is electrically connected to the test apparatus 10 and performs processing for estimating the heat transmissibility is provided.

  The test apparatus 10 includes an apparatus main body 11 arranged in contact with an indoor surface (indoor side surface) of a surface member 80 to be evaluated (hereinafter referred to as “object”), and an outdoor surface (outdoor side of the object 80). And an external temperature sensor 12 that detects the outdoor side temperature of the object 80. As shown in FIG. 2, the apparatus main body 11 includes a reference plate 21, a heater 22, a heat insulating member 23, and two temperature sensors 24 and 25. In FIG. 2, the wiring of the heater 22 and the temperature sensors 24 and 25 is not shown.

The reference plate 21 is a plate-like member that forms one surface (front surface) of the apparatus main body 11, and is arranged (contacted) in contact with the indoor surface of the object 80. That is, the reference plate 21 has a surface 21a that abuts against the indoor surface of the object 80 and a back surface 21b that is located on the opposite side. Thermal transmittance U ₁ of the reference plate 21 is known.

  The reference plate 21 is formed of, for example, a resin-based heat insulating material such as an extruded polystyrene foam. In addition, the reference | standard board 21 should just be a material which can transmit heat to the target object 80 and heat resistance is not too high. Moreover, it is desirable that the heat insulation performance does not change over time. Or it is desirable that it is replaceable when it changes over time. Further, it is desirable that the surface 21a of the reference plate 21 is smooth and can secure the degree of adhesion of the object 80 with the indoor surface. Moreover, the shape is a rectangular shape, for example.

  The heater 22 is a heat generating member provided on the back side of the reference plate 21. When the heater 22 is turned on (heat generation state), heat is transmitted to the object 80 via the reference plate 21. The heater 22 is preferably composed of a planar heating element and has substantially the same area as the reference plate 21. ON / OFF of the heater 22 is controlled by the estimation device 13.

  The heat insulating member 23 is provided on the indoor side of the heater 22, and the reference plate 21, the heater 22, and the heat insulating member 23 are formed in layers. The thickness of the heat insulating member 23 is larger than the thickness of the reference plate 21. The heat resistance of the heat insulating member 23 is sufficiently higher than the heat resistance of the reference plate 21 and prevents the heat of the heater 22 from flowing backward to the indoor space side. As a result, most of the heat of the heater 22 can be transmitted to the object 80 side. In order to evenly transmit the heat of the heater 22 to the reference plate 21, a soaking plate (not shown) may be provided between the heater 22 and the reference plate 21.

  The temperature sensor 24 is provided on the back surface 21 b of the reference plate 21 and detects the temperature on the back surface 21 b side of the reference plate 21. The temperature sensor 25 is provided on the surface 21 a of the reference plate 21 and detects the temperature on the surface 21 a side of the reference plate 21. Here, since the surface 21 a of the reference plate 21 is disposed in contact with the indoor surface of the object 80, the temperature detected by the temperature sensor 25 is equal to the temperature of the indoor surface of the object 80.

  It is desirable that the temperature sensor 12 be disposed on the same line as the temperature sensors 24 and 25 of the apparatus main body 11 on the outdoor surface of the object 80. That is, when the object 80 is an outer wall, it is desirable that the position of the temperature sensor 12 and the positions of the temperature sensors 24 and 25 are substantially the same height. Since the rate of increase in the temperature of the outdoor surface of the object 80 due to the heating of the heater 22 is slight, the temperature sensor 12 is not limited to the temperature of the outdoor surface of the object 80 itself, but the temperature of the object 80 on the outdoor side. Can be detected. That is, the temperature of the outdoor surface of the object 80 may be replaced with the outside air temperature, or the temperature of the outdoor surface of the object 80 may be estimated by multiplying the outside air temperature by the heat transfer coefficient of air. For example, when the target object 80 is the first floor, the temperature of the outdoor surface of the target object 80 can be replaced with the underfloor temperature. In such a case, the installation position of the temperature sensor 12 is not particularly limited.

  The detection signals from the temperature sensors 24 and 25 and the temperature sensor 12 are input to the estimation device 13, and the estimation device 13 estimates the thermal conductivity of the object 80.

  As shown in FIG. 3, the estimation device 13 includes a control unit 31 that performs various arithmetic processes and control of each unit, a storage unit 32 that stores various types of data and programs, an operation unit 33 that receives instructions from a user, A display unit 34 for displaying various information, a communication unit 35 for performing network communication, a power supply unit 36, and a time measuring unit (not shown) for performing a time measuring operation are included. The estimation device 13 also receives a heating control unit 37 that controls the output of the heater 22 and signals from the temperature sensors 24, 25, and 12 based on an instruction from the control unit 31 and outputs the signals to the control unit 31. And an input unit (not shown). The control unit 31 is realized by an arithmetic processing device such as a CPU (Central Processing Unit). The storage unit 32 is realized by, for example, a nonvolatile storage device. Alternatively, the control unit 31 and the storage unit 32 may be configured as one piece of hardware (storage / calculation unit).

  As shown in FIG. 1, when the test apparatus 10 and the estimation apparatus 13 are separated, the estimation apparatus 13 is a connector to which the wiring terminals of the heater 22 and the temperature sensors 24, 25, 12 are connected (see FIG. 1). (Not shown).

  Note that the apparatus main body 11 and the estimation apparatus 13 of the test apparatus 10 are desirably provided in one housing 100 as shown in FIG. That is, it is desirable that the heat transmissivity estimation system 1 is constituted by a single device (heat transmissivity estimation device) 1A. In this case, the operation unit 33 and the display unit 34 of the estimation device 13 may be provided on the housing 100. In this case, the operation unit 33 and the display unit 34 may be integrally configured as a touch panel. Further, a partition plate 101 may be provided between the apparatus main body 11 and the estimation apparatus 13.

  Further, as described above, when the temperature of the outdoor surface of the object 80 is replaced by the outside air temperature or the underfloor temperature, the temperature sensor 12 itself is not provided, and the operation unit 33 or the communication unit 35 of the estimation device 13 is provided. Via, the outdoor side temperature of the target 80 may be input. That is, the test apparatus 10 may be configured by only the apparatus main body 11.

(About functional configuration)
Next, the functional configuration of the heat transmissibility estimation system 1 will be described.

As shown in FIG. 3, the estimation device 13 includes a measurement processing unit 41, a prediction processing unit 42, an estimation unit 43, and a result processing unit 44 in addition to the above-described heating control unit 37 as its functional configuration. . The functions of the measurement processing unit 41, the prediction processing unit 42, the estimation unit 43, and the result processing unit 44 are realized by the control unit 31 in a state where the test apparatus 10 is attached to the object 80. The storage unit 32 stores in advance the thermal conductivity U ₁ of the reference plate 21.

  Based on detection signals from the temperature sensors 24, 25, and 12, the measurement processing unit 41 measures the temperature at each position in a state where heat is transmitted to the object 80 by the heater 22. That is, referring to FIG. 4, the rear surface side temperature Th of the reference plate 21, the surface side temperature of the reference plate 21 (the indoor surface temperature of the object 80) Ts, and the outdoor side temperature Tg of the object 80 are measured. The measured temperature (° C.) of each point is temporarily stored in a storage unit such as an internal memory of the control unit 31.

  In addition, the measurement processing unit 41 operates the heater 22 via the heating control unit 37 to heat the object 80 from the indoor space side. That is, the heating control unit 37 controls the output of the heater 22 in accordance with an instruction from the measurement processing unit 41. The output control of the heater 22 by the heating control unit 37 will be described later.

The estimation unit 43 estimates the thermal conductivity of the object 80 from the three temperature gradients after the object 80 is heated. The heat flow rate of the object 80 is estimated based on the temperatures Th, Ts, Tg at each position and the heat flow rate U ₁ of the reference plate 21 stored in the storage unit 32. The estimation principle of the heat transmissivity of the object 80 by the estimation unit 43 is as follows.

Since the heat transmissivity of the reference plate 21 is known, the heat flow W ₁ (which passes through the reference plate 21) from the value U ₁ and the front and back temperatures (surface side temperature and back surface temperature) Th, Ts of the reference plate 21 ( Unit: W / m ² ) can be estimated. That is, the heat flow W ₁ passing through the reference plate 21 can be estimated by the following equation (1).

W ₁ = U ₁ × (Th−Ts) (1)
On the other hand, the following equation (2) is established for the heat flow W ₀ passing through the object 80 from the unknown heat transmissibility U ₀ and the front and back temperatures (Ts, Tg) of the object 80.

W ₀ = U ₀ × (Ts−Tg) (2)
Here, since the heat flow W ₀ passing through the object 80 and the heat flow W ₁ passing through the reference plate 21 are the same when considered in a unified manner, the following equation (3) holds.

U ₁ × (Th−Ts) = U ₀ × (Ts−Tg) (3)
Therefore, the heat transmissibility U ₀ of the object 80 to be obtained is obtained by the following equation (4).

U ₀ = U ₁ × (Th−Ts) / (Ts−Tg) (4)
That is, the estimation unit 43 estimates the heat flow (W ₀ ) of the reference plate 21 obtained by multiplying the temperature difference between the front and back temperatures Th and Ts of the reference plate 21 and the heat flow rate U _{1 of the} reference plate 21. Is divided by the temperature difference between the front and back temperatures Ts, Tg of the object 80 (the surface side temperature Ts of the reference plate 21 and the outdoor side temperature Tg of the object 80), thereby obtaining the thermal conductivity U ₀ of the object 80. Can be derived.

Based on the above estimation principle, in the present embodiment, the target 80 is obtained by substituting the thermal conductivity of the reference plate 21 and the three measured temperatures into the calculation formula represented by the formula (4). estimating the thermal transmittance _{U 0} of (calculated).

Here, in order to accurately estimate the heat transmissibility U ₀ of the object 80 by the estimation unit 43, the front and back temperatures (Th, Ts) of the reference plate 21 and the outdoor side temperature (Tg) of the object 80 are originally set. It is necessary to wait until each becomes substantially constant and stable. Note that, as described above, the outdoor side temperature (Tg) of the object 80 can be regarded as constant regardless of the heating state of the object 80, and thus the front and back temperatures (Th, Ts) of the reference plate 21 are actually stable. You have to wait until you do. The time until the front and back temperatures of the reference plate 21 are stabilized varies depending on the heat capacity of the object 80. Generally, the heat capacity of the flooring is larger than the heat capacity of the outer wall. The flooring is typically composed of a plywood (for example, flooring, wooden floor, etc.) facing an indoor space, and a heat insulating material (for example, polystyrene foam) provided on the back side thereof.

When the object 80 is a surface member having a large heat capacity such as a flooring material, if the object 80 is heated with the output of the heater 22 being a constant output, as shown in FIG. It may take nearly 9 hours for both the back surface temperature Th and the surface side temperature (indoor surface temperature of the object 80) Ts of the reference plate 21 to stabilize. In this case, of course, as shown in FIG. 24 (B), it takes nearly 9 hours for the heat flow rate U ₀ of the object 80 to be close to the true value Ut. This is considered to be because, in the case of the object 80 having a large heat capacity, the temperatures Th and Ts at the two points rise while the heat from the heater 22 is stored in the object 80. In FIG. 24, the time when both the front and back temperatures Th and Ts of the reference plate 21 are stable and the estimated U value substantially coincides with the true value is indicated by “tz”. Further, the outdoor surface temperature of the first floor is indicated by Tg ₁ , and the underfloor temperature is indicated by Tg ₂ .

  In order to make it possible to diagnose the thermal insulation performance in a real property during occupancy, it is ideally necessary to evaluate (diagnose) the thermal insulation performance of the object 80 in a short time of 2 hours or less. In the case as shown in FIG. 24, when the calculation of the heat transmissivity is attempted at the timing when the ideal measurement end time (indicated by a two-dot chain line) from the start of heating, the front and back of the reference plate 21 at that time. The temperatures Th and Ts are still rising and have not reached their stable temperatures TSh and TSs. Therefore, even if the front and back temperatures Th and Ts of the reference plate 21 obtained at that time are applied to the calculation formula (4), the error between the estimated U value and the true value (Ut) is very large.

  Therefore, in the present embodiment, the back surface side temperature Th of the reference plate 21 is controlled to be constant, and the variable is only the surface side temperature Ts of the reference plate 21, so that the surface side temperature Ts can be reduced in a short time from the start of heating. The stable temperature was predicted. The constant temperature control of the heater 22 is performed by the heating control unit 37, and the surface side stable temperature of the reference plate 21 is predicted by the prediction processing unit 42. In the following description, for ease of understanding, the rear surface temperature Th of the reference plate 21 is referred to as “heater temperature Th”, and the front surface temperature Ts of the reference plate 21 is referred to as “target surface temperature Ts”.

  As shown in the graph of FIG. 5, the heating control unit 37 rapidly increases the temperature of the heater 22 immediately after the start of operation, and controls so that the heater temperature Th measured by the measurement processing unit 41 becomes the set temperature TSh. To do. Such constant temperature control is realized by repeating ON / OFF of the heater 22, for example. The detection signal from the temperature sensor 24 may be input to the heating control unit 37 without going through the measurement processing unit 41.

  When the constant temperature control is performed by the heating control unit 37, the prediction processing unit 42 is based on the target surface temperature (actually measured value) Ts obtained in time series, that is, the target surface (that is, the indoor surface of the target object 80). The stable temperature TSs is predicted. Note that the stable temperature TSs can be predicted after the measurement is started after the heater temperature Th becomes substantially constant and the rising gradient of the target surface temperature Ts is stabilized (time ta in FIG. 5). A method for predicting the stable temperature of the target surface will be described with reference to the graph of FIG.

  It is assumed that the time tb shown in FIG. 6 is an ideal measurement end time (typically, between 60 minutes and 120 minutes after the start of measurement). At the stage of time tb, the target surface temperature Ts is not stable and continues to rise. Usually, the increase in the target surface temperature Ts finally converges after a long time has elapsed from the ideal end time tb. The prediction processing unit 42 predicts the stable temperature TSs of the target surface by performing function approximation from the temperature change before time tb and deriving the convergence value b. That is, the prediction processing unit 42 calculates the convergence value b of the approximate curve based on the actual measurement value (Ts) obtained when the heater temperature is constant in the process of changing the target surface temperature. The stable temperature TSs is predicted.

  The approximate curve is represented by the following equation (5).

y = −Ca ^x + b (where 0 <a <1) (5)
Here, as shown in the graph of FIG. 6, not the measurement start time but the specific time point is x = 0 of the approximate curve, and the actual measurement value at the specific time point is y ₀ . In that case, substituting x = 0 and y = y ₀ into the approximate expression of equation (5),
y ₀ = −Ca ⁰ + b = −C + b
So that
C = by- ₀
Holds. Therefore, the approximate expression of the equation (5) is replaced with the equation of the following equation (6).

y = − (b−y ₀ ) a ^x + b (6)
When this equation (6) is used, the unknown b is a convergence value to be finally obtained, but can be calculated if the unknown a is determined. Therefore, the prediction processing unit 42 derives the unknown a of the equation (6) from the actually measured values (y ₁ , y ₂ ) at the first time point (x ₁ ) and the second time point (x ₂ ) after the specific time point. To do. In the present embodiment, the specific time point is typically a time point (time ta) when the heater temperature Th is stabilized. Therefore, the specific time point is hereinafter referred to as “heater stable time point”. The first time point is a time point after Δt1 minutes from the heater stable time point, and the second time point is a time point after Δt2 minutes (Δt2> Δt1) from the heater stable time point. Note that the specific time point may be after the time ta.

Specifically, first, the unknown number a is assumed to be an arbitrary numerical value less than 1. Then, a provisional value of the convergence value b (hereinafter referred to as “provisional convergence value b ^* ”) is obtained from the actually measured value at the first time point by the following equation (7).

b ^* = (y ₁ -y ₀ a ^x1 ) / (1-a ^x1 ) (7)
When the provisional convergence value b ^* is obtained, a prediction formula for the target surface temperature Ts at a later time can be set as the following formula (8).

y = − (b ^* −y ₀ ) a ^x + b ^* (8)
Since the provisional convergence value b ^* calculated based on the actual measurement value at the first time point is used as the prediction equation, Δt1 minutes have elapsed from the first time point, that is, the heater stable time point (x = 0) in the present embodiment. The time point is called “prediction formula creation timing”. In FIG. 7, the first time point is shown as “prediction formula creation time”.

FIG. 7 shows a prediction formula graph when the unknown number a = 0.50 at the prediction formula generation timing (x ₁ ), a prediction formula graph when the unknown number a = 0.90, and the unknown number a =. A graph of a prediction formula when 0.99 is assumed is shown. Of course, the provisional convergence value b ^* takes various values depending on the assumed value of the unknown a. For example, assuming that x ₁ = 10 and the unknown number a = 0.90, the temporary convergence value b ^* is “b ^* = {y ₁₀ −y 0 (0.9) ¹⁰ } / {1− (0.9)”. ¹⁰ } ". “Y ₁₀ ” is the target surface temperature Ts (measured value) when x = 10.

Next, the prediction processing unit 42 calculates the predicted value “− (b ^* −y ₀ ) a ^x2 + b ^* calculated from the prediction formula (8) at the second time point when Δt2 time (x ₂ ) has elapsed from the heater stabilization time point ^. ”And the actual measurement value y _{2 at} that time. Thereby, it is determined (confirmed) whether or not the assumed value of the unknown a is correct.

If the predicted value and the measured value y ₂ are different, it can be determined that unknowns a incorrect. In this case, the prediction processing unit 42, the predicted value and the measured value y ₂ changes the assumed value of the unknowns a until the same. For example, as shown in FIG. 8, if the predicted value is smaller than the measured value y _2, unknowns a, which assumed it is understood that too much lower than the original value. Conversely, as shown in FIG. 9, if the predicted value is greater than the measured value y _2, the assumed value of the unknowns a is seen to be too large than the original value.

In contrast, as shown in FIG. 10, if the match predicted value and the measured value y ₂ is the assumed value of the unknowns a can be regarded as correct. Therefore, the prediction processing unit 42 can predict the stable surface temperature TSs by determining the provisional convergence value b ^* used for calculating the prediction value at this time as the convergence value b.

Thus, since it is confirmed whether the assumed value of the unknown a and the provisional convergence value b ^* are correct based on the actually measured value at the second time point, in the present embodiment, the second time point, that is, the heater stable time point (x = 0). ) Is the “confirmation timing”. 8 to 10, the second time point is shown as “confirmation time”.

By using such a prediction method, the convergence value b, that is, the stable temperature TSs can be predicted when the target surface temperature Ts is not stable. Therefore, the heat flow rate U ₀ of the object 80 can be estimated in a short time.

Note that due to the characteristics of the temperature sensor 25, one or both of the _two actual measurement values y ₁ and y ₂ may include an error of ± 0.5 ° C. or less. If there is an error in any of the actual measurement values y ₁ and y ₂ , the calculation result of the convergence value b is also affected. Therefore, it is desirable that the prediction processing unit 42 determines whether the value predicted as the convergence value b at the confirmation timing (candidate value of the convergence value b) is not an abnormal value. Such abnormality determination processing will be described later.

  Further, according to the stable temperature prediction method as in the present embodiment, the time difference Δt1 between the heater stabilization time and the prediction formula creation timing and the time difference (Δt2−Δt1) between the prediction formula creation timing and the confirmation timing are: It does not have to be equal. Therefore, the prediction formula creation timing and the confirmation timing can be freely set within the ideal end time.

Therefore, two points where the difference between the actual measurement values y ₀ and y ₁ and the difference between the actual measurement values y ₁ and y ₂ are relatively large can be selected as the prediction formula creation timing and the confirmation timing. As a result, convergence error calculation errors can be reduced.

Further, since the confirmation timing can be set freely, the confirmation timing may be determined as an ideal end time tb with the measurement start time as a reference. In this case, the time obtained by subtracting the settling time ta from the ideal end time tb is a value of _{x 2 (Δt2).} Alternatively, the confirmation timing may be determined as a target predicted time from the heater stable point.

  Information for specifying each of the prediction formula creation timing and the confirmation timing may be stored in the storage unit 32 in advance, or may be input by the user at the start of measurement. In the latter case, a specific time (hour and minute) may be input, or an elapsed time (Δt1, Δt2) from the stable time ta may be input. Alternatively, an elapsed time (ta + Δt1, ta + Δt2) from the start of measurement may be input.

Referring to FIG. 3 again, the result processing unit 44 of the estimation device 13 performs a process of storing the estimation result by the estimation unit 43 (the heat transmissivity U _{0 of the} object 80) in the storage unit 32. At this time, it is desirable to associate the identification information for identifying the object 80 with the estimated data of the heat transmissibility and store it in the storage unit 32. In addition, the result processing unit 44 performs processing for displaying the estimation result on the display unit 34 in order to notify the user of the estimation result. The storage unit 32 includes a memory for storing the thermal transmittance U ₁ of the reference plate 21, and a memory for storing the estimated result, it may include separately.

  In the present embodiment, the functions of the measurement processing unit 41, the prediction processing unit 42, the estimation unit 43, and the result processing unit 44 described above are realized by the control unit 31 executing software. At least one of these may be realized by hardware.

(About operation)
Next, the operation of the heat transmissibility estimation system 1 will be described. Operation | movement of the said system 1 is implement | achieved when the control part 31 reads the program memorize | stored in the memory | storage part 32, and performs a heat transmissivity measurement process.

  FIG. 11 is a flowchart showing the heat transmissivity measurement process in the present embodiment. The process illustrated in FIG. 11 is started when a measurement start instruction is input from the user via the operation unit 33 while the apparatus main body 11 is in contact with the indoor surface of the object 80.

  Referring to FIG. 11, first, measurement processing unit 41 starts the heating process of heater 22 via heating control unit 37 (step S <b> 2), and measures the temperature at each position described above in parallel with the heating process. Is started (step S4). That is, the measurement processing unit 41 measures the heater temperature Th, the target surface temperature Ts, and the outdoor side temperature Tg of the target object 80 based on the detection signals from the temperature sensors 24, 25, and 12 during heating of the heater 22. To do. The detection signal from each temperature sensor input to the estimation device 13 is converted into a digital signal and output to the control unit 31. Note that, as described above, the outdoor side temperature Tg of the object 80 can be regarded as constant regardless of the heating state of the object 80, and therefore the measurement timing of the temperature does not matter.

  The heating control unit 37 performs constant temperature control of the heater 22 so that the heater temperature Th becomes the set temperature. The set temperature may be stored in the storage unit 32 in advance.

  Subsequently, the prediction processing unit 42 executes a stable temperature prediction process (step S6). The stable temperature prediction process will be described with reference to a subroutine in FIG.

  With reference to FIG. 12, the prediction processing unit 42 temporarily stores, for example, the temperature data of each point obtained in time series in the internal memory during the processing period (step S22). When the variable i is an elapsed time from the start of measurement, the heater temperature Thi and the target surface temperature Tsi measured at the time i are sequentially stored.

  First, the prediction processing unit 42 determines whether or not the heater temperature is stable (step S24). Specifically, for example, when the average value of the heater temperature data at the previous 10 points and the average value of the heater temperature data at the previous 100 points become substantially the same at time i, the heater temperature is stabilized. Judge.

When it is determined that the heater temperature is stable (YES in step S24), the time i at that time is stored as “x ₀ ” and the target surface temperature Tsi is stored as “y ₀ ” (NO in step S26, step S28). . Whether the heater temperature is stable or not is detected not only by detecting the fluctuation of the heater temperature Thi but also by detecting whether the gradient of the target surface temperature Tsi is stable. Therefore, it can be considered that there is no sensor error on the target surface temperature y _0.

  After that, the prediction processing unit 42 determines whether or not the prediction formula creation timing has come (step S30). Whether or not it is the prediction formula creation timing is determined based on information stored in the storage unit 32 or information input via the operation unit 33.

If the elapsed time i is long indicates a prediction expression creation timing (YES at step S30), the current elapsed time i, the time Δt1 minus x ₀ hours saved as "x _1", the target surface at this time The temperature Tsi is stored as “y ₁ ” (step S32).

Subsequently, the prediction processing unit 42 sets the unknown number a to an arbitrary numerical value (0 <a <1) (step S34), and based on the above equation (7), the assumed value of the unknown number a and the stored x ₁ , y Based on ₁ , the provisional convergence value b ^* is calculated (step S35).

When the provisional convergence value b ^* is obtained, the prediction processing unit 42 sets a prediction formula for the subsequent target surface temperature as in the above formula (8) (step S36). When the assumed value of the unknown a is 0.90, for example, the prediction equation is expressed as “y = − (b ^* −y ₀ ) (0.9) ^x + b ^* ”.

  When the prediction formula is created, the process returns to step S22. In step S22, each point temperature data at time i is additionally stored, and it is determined whether or not the confirmation timing has come (after the above-described various determinations) (step S38). Whether or not it is a confirmation timing is also determined based on information stored in the storage unit 32 or information input via the operation unit 33.

If it is determined that the confirmation timing (YES at step S38), the current elapsed time i, the time Δt2 minus the saved x ₀ hours and "x _2", the target surface temperature Tsi of the time " It is stored as “y ₂ ” (step S40).

Next, the prediction processing unit 42 determines that the actual measurement value y ₂ is the predicted value “− (b ^* −y ₀ ) a obtained by substituting the value of x ₂ into“ x ”of the prediction formula created in step S36. ^It is determined whether or not it is the same as “ ^x2 + b ^* ” (step S42). Specifically, if the measured value and the predicted value match the third decimal place or more, it is determined that they are the same. Note that if the measured value and the predicted value match the second decimal place or more, they may be determined to be the same.

If the actually measured value and the predicted value are different (NO in step S42), the assumed value of the unknown a in the prediction formula is changed, and the provisional convergence value b ^* is updated (step S44). Specifically, the unknown number a is changed so that the predicted value approaches the actual measured value according to the magnitude relationship between the actual measured value and the predicted value. That is, when the measured value is smaller than the predicted value, the assumed value of the unknown a is changed to be smaller than the original assumed value, and when the measured value is larger than the predicted value, the assumed value of the unknown a is changed to the original assumption. Change larger than the value. The value of the unknown a is changed, for example, in units of 0.1, and after the first decimal place number is determined, the second decimal place number is changed.

Until it is determined that the actually measured value and the predicted value are the same, the assumed value of the unknown a is changed and the provisional convergence value b ^* is calculated (steps S42 and S44). When it is determined that the actual measurement value and the predicted value are the same (YES in step S42), the prediction processing unit 42 uses the latest provisional convergence value b ^* used for calculating the predicted value determined to be the same as the actual measurement value. It is determined as a convergence value b (candidate). Thereby, the convergence value b is output (step S46).

Next, referring to FIG. 13, the prediction processing unit 42 executes an abnormality determination process for the convergence value b (candidate). Specifically, as shown in the graph of FIG. 14, the prediction processing unit 42, a confirmation timing and _'Found y _2' in a predetermined time before the time point x ₂ than x _2, x ₂ a predetermined time than the time The actual measurement value y ₂ ″ at the later time point x ₂ ″ is acquired. Then, the convergence value b ′ is calculated from the actual measurement value y ₂ ′, and the convergence value b ″ is calculated from the actual measurement value y ₂ ″ (step S48). The value of the unknown a used for calculating these convergence values b ′ and b ″ is the same as the value used for calculating the convergence value b to be determined.

  Next, the prediction processing unit 42 calculates an average value Bave between the convergence value candidate value b and the convergence values b ′ and b ″ calculated here (step S50). When convergence value candidate value b substantially matches average value Bave (YES in step S52), it is determined that convergence value candidate value b is correct, and convergence value b is determined as a predicted value (step S54). It should be noted that if the convergence value candidate value b and the average value Bave match, for example, at the second decimal place or more, it is determined that they substantially match.

If convergence value candidate value b does not match average value Bave (NO in step S52), it is determined that convergence value candidate value b is abnormal, and recalculation of convergence value b is executed (step S56). When the recalculation of the convergence value b is performed, the process returns to step S46 and the above process is repeated. In this embodiment, actual measurement values of three points y _2, y ₂ in the vicinity of confirmation timing ', y _2' based on 'has been determined the presence or absence of an abnormality of convergence value b, but is not limited to a 4 The presence / absence of an abnormality in the convergence value b may be determined based on an 'measured value over a point'.

An example of the recalculation process of the convergence value b will be described with reference to the flowchart of FIG. The prediction processing unit 42 shifts the prediction formula creation timing forward or backward to change the value of “x ₁ ”, and changes the actual measurement value at that time to “y ₁ ” (step S 60). Thus, the provisional convergence value b ^* is recalculated based on the equation (7), and the prediction equation (8) is recreated (step S62). Specifically, the same processing as steps S34 to S36 in FIG. 12 is performed. Note that the assumed value of the unknown a used for calculating the provisional convergence value b ^* may be the same as the numerical value used for calculating the convergence value b (candidate) of the previous abnormality determination target.

When the prediction formula creation timing before the change is expressed as “x _p1 ” and the actual measurement value at that time is expressed as “y _p1 ”, the prediction formula (8) re-created when the actual measurement value y _p1 has an error An example of the graph is shown in FIG.

Thereafter, the unknown value a in which the actually measured value y _{2 at} the confirmation timing (x ₂ ) is the same as the predicted value obtained from the re-created prediction formula is determined, and the provisional convergence value b ^* is updated (step S64). Thereby, the provisional convergence value b ^* corresponding to the re-created prediction formula is output again as a new convergence value b (candidate) (step S46 in FIG. 12).

Such a recalculation process is particularly effective when there is an error in the actual measurement value y1 at the _first prediction formula creation timing.

Incidentally, assume that also in the second time of the abnormality determination processing (step S48, S50, S52 in FIG. 13), if the candidate of the convergence value b is determined to be abnormal, there is an error in the measured value y ₂ at the confirmation timing Then, the recalculation process may be executed.

An example of the recalculation process in this case is shown in the flowchart of FIG. Referring to FIG. 17, prediction processing unit 42 shifts the confirmation timing forward or backward to change the value of “x ₂ ”, and changes the actual measurement value at that time to “y ₂ ” (step S 70). Next, the unknown value a in which the actually measured value y ₂ after the change is the same as the predicted value obtained by substituting “x ₂ ” after the change is determined, and the provisional convergence value b ^* is updated (step S72). Specifically, processing similar to steps S42 and S44 in FIG. 12 is performed. The updated provisional convergence value b ^* is output again as a new convergence value b (candidate) (step S46 in FIG. 12).

When the confirmation timing before the change is expressed as “x _p2 ” and the actual measurement value at that time is expressed as “y _p2 ”, if there is an error in the actual measurement value y _p2 , the unknown a and the provisional convergence value b ^* are updated. An example of the prediction formula graph is shown in FIG.

  Note that it is desirable that the measured values at the prediction formula creation timing and the confirmation timing are each subjected to moving average processing so that extreme variations in measured values are suppressed. In addition, it is desirable to obtain a smooth curve by performing a moving average process of measured values continuously for a certain period of time (for example, about 5 minutes) even at the start of measurement.

Referring again to FIG. 11, the stable temperature prediction processing is completed, the estimation unit 43 reads the numerical data indicating the thermal transmittance U ₁ of the reference plate 21 from the storage unit 32 (step S8), and the object 80 The heat transmissibility U ₀ is estimated (step S10). Specifically, the calculation formula shown by the above formula (4) is also read from the storage unit 32, and the set temperature (Th) of the heater 22 and the convergence value (Ts) obtained by the prediction process are added to the read calculation formula. Then, the estimated value (U ₀ ) of the heat transmissibility of the object 80 is calculated by substituting the outdoor temperature (Tg) of the object 80 and the numerical value (U ₁ ) read in step S8. Note that a calculation formula in which the thermal conductivity of the reference plate 21 is substituted in advance for the character U ₁ in the formula (4) may be stored in the storage unit 32 in advance. The processing of step S8 (U ₁ value read) may be performed at the beginning of the measurement process.

When the thermal conductivity (U ₀ ) of the object 80 is estimated, the result processing unit 44 displays the estimation result (U ₀ ) on the display unit 34 and records it in the storage unit 32 (step S12). Thus, by recording the heat transmissibility of the object 80, the amount of heat escaping from the object 80 can be obtained by inputting the area of the object 80. Further, in the building, when the heat transmissibility estimation processing is completed for all the surface members to be evaluated for heat insulation performance, the heat transmissivity for each surface member stored in the storage unit 32 and the area thereof are referred to. Thus, it is possible to estimate the average skin heat transfer coefficient and heat loss coefficient of the entire building.

  As described above, according to the present embodiment, since the test apparatus 10 forcibly applies heat to the object 80 from the indoor space side, even when the actual temperature difference between the inside and outside of the object 80 is small, It is possible to estimate the heat transmissibility. Moreover, since the area of the reference plate 21 of the test apparatus 10 is sufficiently smaller than the area of the object 80 and only a part of the object 80 needs to be heated, the heat insulation performance should be evaluated in a shorter time than before. Can do.

  Moreover, as equipment used for estimating the heat transmissibility, it is only necessary to install the test apparatus 10 on the object 80, so that the system configuration can be simplified.

  Further, when measuring the heat flow with a heat flow meter, an error from the true value is likely to occur, but in the present embodiment, it is only necessary to measure the temperature at each position in a state where heat is transmitted to the object 80. Errors can be reduced.

  Furthermore, in the present embodiment, the stable temperature (convergence value) on the surface side of the reference plate 21 can be predicted at an early stage after the heating of the heater 22 is started. Therefore, even when the object 80 having a large heat capacity is set as an evaluation target, the measurement time can be suppressed to a short time (ideally, one hour or less). Therefore, the system 1 of this Embodiment can be applied also to the real property in which it moves.

  In addition, according to the method for predicting the stable temperature of the target surface as in the present embodiment, it is possible to determine whether or not the convergence value candidate is an abnormal value, so that the stable temperature of the target surface can be accurately predicted. . Further, since the convergence value can be recalculated by changing only one of the prediction formula creation timing and the confirmation timing, the processing load can be suppressed. Note that both the prediction formula creation timing and the confirmation timing may be changed.

  In the convergence value abnormality determination process, if the convergence value is determined to be abnormal a predetermined number of times, a predicted value having a width is obtained from the maximum value and the minimum value of the convergence value to be determined. Also good. In this case, the estimation unit 43 may calculate the maximum value and the minimum value of the estimated U value of the object 80 based on the maximum prediction value and the minimum prediction value obtained from the prediction processing unit 42. That is, the result processing unit 44 may output an estimated range of the heat transmissibility.

  Alternatively, convergence value abnormality determination processing is not essential. In that case, the statistical value of the convergence value calculated from the actual measurement value near the confirmation timing may be determined as the stable temperature of the target surface. Specifically, Bave (average of convergence value candidates and convergence values calculated from actually measured values before and after the confirmation timing) calculated in step S50 in FIG. 13 may be determined as the stable temperature of the target surface. .

  Further, in the present embodiment, the heater 80 is controlled at a constant temperature to heat the object 80, and the prediction process is performed on the surface side temperature in the rising process. However, it is also possible to raise the surface side temperature once and perform prediction processing on the surface side temperature in the subsequent lowering process. In that case, an approximate expression shown by the following expression (9) may be used instead of the approximate expression shown by the above expression (5).

y = Ca ^x + b (where 0 <a <1) (9)
In this case, the approximate expression (6) used in the case of the ascending process is replaced with an equation of the following expression (10). However, this equation (10) is synonymous with setting the range of the unknown a in the approximate expression (6) to “−1 <a <0”.

y = (b−y ₀ ) a ^x + b (10)
The system configuration for rapidly increasing the surface side temperature of the reference plate 21 may be a configuration as shown in the following modification.

(Modification)
Referring to FIG. 19 and FIG. 20, the thermal transmissivity estimation system 1 in the modification of the present embodiment includes an apparatus main body 11A instead of the apparatus main body 11 shown in the above embodiment.

  As shown in FIG. 19, the apparatus main body 11 </ b> A is provided on the surface 21 a of the reference plate 21 in addition to the reference plate 21, the heater (hereinafter referred to as “main heater”) 22, the heat insulating member 23, and the temperature sensors 24 and 25. The sub heater 26 is overlapped. That is, in this modification, in addition to the main heater 22, the sub heater 26 is further provided as a heat generating member that transfers heat to the object 80.

  Similar to the main heater 22, the sub-heater 26 is configured by a planar heating element. In this case, the temperature sensor 25 that detects the surface side temperature of the reference plate 21, that is, the indoor surface temperature of the object 80, is provided on the surface of the sub-heater 26. The area of the sub heater 26 may be smaller than the area of the main heater 22.

  As shown in FIG. 20, the sub-heater 26 is controlled by the heating control unit 37 </ b> A of the estimation device 13. The heating control unit 37A operates the sub heater 26 only for a specific period from the start of heating. That is, both the main heater 22 and the sub heater 26 are operated during the specific period, and only the main heater 22 is operated after the specific period. Thereby, the output of the heat generating member is controlled so that the heating intensity of the object 80 in the specific period at the beginning of heating becomes larger than the heating intensity of the object 80 thereafter.

  The “specific period” represents a period from the start of operation of the heat generating member (heating start) to the specific time. The “specific time” is, for example, a set time set before the start of measurement, and is typically a time (predetermined time) stored in advance in the storage unit 32. The set time is, for example, 30 minutes or less. Note that the set time may not be the time stored in the storage unit 32 in advance, and may be, for example, the time input by the user at the start of measurement. Alternatively, the “specific time” may be a time when the target surface temperature Ts reaches a threshold value.

  The operation of the heating control unit 37A is controlled by the measurement processing unit 41A. Note that the heating control unit 37 </ b> A may include a main heating control unit that controls ON / OFF of the main heater 22 and a sub-heating control unit that controls ON / OFF of the sub-heater 26.

  As shown in FIG. 21, since the sub-heater 26 is arranged on the surface of the apparatus main body 11 </ b> A, the surface 21 a of the reference plate 21 is arranged in close proximity without contacting the indoor surface of the object 80. In this case, since the object 80 can be directly heated by the sub-heater 26, the surface temperature of the object can be rapidly increased even when the main heater 22 is controlled at a constant temperature. The output of the sub heater 26 may be a constant output.

  As shown in FIG. 22, a soaking plate 70 may be provided also on the surface of the sub-heater 26. Since the soaking plate 70 is a hard material, the temperature sensor 25 may be provided on the back side of the sub-heater 26 in order to bring the entire surface of the soaking plate 70 into close contact with the indoor surface of the object 80. In that case, a soaking plate 70 may be further provided between the surface of the reference plate 21 and the sub heater 26, and the temperature sensor 25 may be disposed between the surface of the reference plate 21 and the soaking plate 70. The temperature sensor 25 is embedded in the surface of the reference plate 21 made of a soft material. Similarly, when the temperature sensor 24 on the main heater 22 side is disposed between the back surface of the reference plate 21 and the soaking plate 70, the temperature sensor 24 is embedded in the back surface of the reference plate 21.

  In the present embodiment and its modification, the heating control unit 37 (37A) performs the constant temperature control of the main heater 22, but the output of the main heater 22 may be a constant output. Even if such heating control is performed, when the heater temperature Th is stabilized earlier than the target surface temperature Ts, the stable value of the target surface temperature Ts is determined when the heater temperature Th is determined to be stable. Can be predicted. Therefore, the measurement time can be shortened rather than waiting for both temperatures to stabilize. As described above, the stable temperature TSs of the target surface can be predicted regardless of the heating control method of the heat generating member as long as the heater temperature Th is in a stable state.

  As described above, according to the embodiment and the modification of the present invention, it is possible to accurately estimate the heat flow rate of the object 80 in a short time. Therefore, since the heat insulation performance of the entire existing building can be easily evaluated, the remodeling business can be activated by using the present system 1.

  In addition, the said heat transmissibility estimation method can also be provided as a program. Such a program can be recorded and provided on an optical medium such as a CD-ROM or a computer-readable non-transitory recording medium such as a memory card. In this case, it is assumed that the estimation device 13 further includes a drive device (not shown) capable of reading / writing programs and data from a recording medium (not shown). The program can also be provided by downloading via the network by the communication unit 35.

Moreover, in this Embodiment and its modification, estimation of the heat transmissivity of the target object 80 was performed in the estimation apparatus 13 electrically connected to the apparatus main body 11 (11A) of the test apparatus 10. However, the estimation apparatus including the functions of the prediction processing unit 42, the estimation unit 43, and the result processing unit 44 illustrated in FIG. 3 may be realized by another computer that is not connected to the test apparatus 10. Such a computer may be, for example, a general personal computer or a portable terminal. In this case, it is assumed that the storage unit of the estimation device stores not only the heat flow rate U ₀ of the reference plate 21 but also temperature data of each point necessary for estimating the heat flow rate of the object 80.

  In this case, a device that is electrically connected to the apparatus main body 11 of the test apparatus 10 and is used for on-site testing (hereinafter referred to as “control device”) includes a heating control unit 37 (37A) and a heating control unit 37. A function with the measurement processing unit 41 (41A) that performs control and temperature measurement at each position may be included.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

  DESCRIPTION OF SYMBOLS 1 Thermal conductivity estimation system, 10 Test apparatus, 11, 11A apparatus main body, 12, 24, 25 Temperature sensor, 13 Estimation apparatus, 21 Reference plate, 22 Heater (main heater), 23 Heat insulation member, 26 Sub heater, 31 Control part 32 storage unit 33 operation unit 34 display unit 35 communication unit 36 power supply unit 37 37A heating control unit 41 41A measurement processing unit 42 prediction processing unit 43 estimation unit 44 result processing unit 70 Soaking plate, 80 object (surface member), 100 housing, 101 partition plate.

Claims (7)

As an index representing the heat insulation performance of a surface member located between an indoor space and an outdoor space of a building, a system for estimating the heat transmissivity of the surface member,
A plate-like member having a surface in contact with or close to the indoor surface of the surface member and a back surface located on the opposite side;
A heater that is provided on the back side of the plate-like member and heats the indoor surface of the surface member;
A first temperature sensor provided on the surface side of the plate-like member for detecting an indoor surface temperature of the surface member;
In the process of changing the indoor surface temperature of the surface member due to the heating of the heater, the convergence value of the approximate curve based on the actual measurement value obtained from the first temperature sensor in a state where the back surface temperature of the plate member is constant. Predicting processing means for predicting a stable temperature of the indoor surface of the surface member by calculating
Based on the stable temperature predicted by the prediction processing means, the outdoor side temperature of the surface member, the back surface temperature of the plate member, and the thermal conductivity of the plate member, the heat of the surface member. An estimation means for estimating the transmissivity,
The prediction processing means includes
When the specific point in the process of changing the indoor surface temperature of the surface member is x = 0 of the approximate curve, and the measured value at the specific point is y0,
y = − (b−y ₀ ) a ^x + b, or
y = (b−y ₀ ) a ^x + b
Assuming that the unknown a in the equation expressed as is an arbitrary value less than 1, the unknown as the convergence value based on the assumed value of the unknown a and the measured value at the first time after the specific time a calculating means for calculating a provisional value of b;
A comparison unit that compares an actual measurement value at a second time point after the first time point with a predicted value at the second time point based on the provisional value calculated by the calculation unit;
A heat transmissivity estimation system comprising: determination means for determining, as the convergence value, the provisional value used for calculation of a predicted value determined to be the same as an actual measurement value as a result of comparison by the comparison means.   The heat transmissivity estimation according to claim 1, wherein the calculation means repeats the change of the assumed value of the unknown a and the calculation of the provisional value until it is determined that the actually measured value and the predicted value at the second time point are the same. system. The prediction processing means includes
Abnormality determination means for determining whether the convergence value determined by the determination means is an abnormal value;
2. A recalculation unit that recalculates the convergence value by changing at least one of the first time point and the second time point when the abnormality determination unit determines that the value is an abnormal value. Or the heat transmissivity estimation system according to 2. A second temperature sensor that is provided on the back side of the plate-like member and detects the back-side temperature of the plate-like member;
A heating control means for performing a constant temperature control of the heater so that the back surface side temperature of the plate-like member becomes a set temperature;
The heat transmissivity estimation system according to any one of claims 1 to 3, wherein the specific time corresponds to a time when a back surface temperature of the plate-like member is stabilized at a constant temperature. In order to directly transfer heat to the surface member, the plate member further includes a sub-heater provided on the surface side,
The heat transmissivity estimation system according to claim 4, wherein the heating control means operates the sub-heater only for a specific period from the start of heating so that the indoor surface temperature of the surface member rapidly increases. As an index representing the heat insulation performance of the surface member located between the indoor space and the outdoor space of the building, an estimation device for estimating the heat permeability of the surface member,
Storage means for storing the outdoor side temperature of the surface member, the back surface side temperature of the plate-like member arranged so as to be in contact with or close to the indoor surface of the surface member, and the thermal conductivity of the plate-like member ,
In the process of changing the indoor surface temperature of the surface member, the convergence value of the approximate curve is calculated based on the measured indoor surface temperature of the surface member obtained when the back surface temperature of the plate-like member is constant. Prediction processing means for predicting a stable temperature of the indoor surface of the surface member,
Based on the stable temperature predicted by the prediction processing means, the outdoor temperature of the surface member stored in the storage means, the back surface temperature of the plate member, and the thermal conductivity of the plate member. And an estimating means for estimating the heat transmissivity of the surface member,
The prediction processing means includes
When the specific point in the process of changing the indoor surface temperature of the surface member is x = 0 of the approximate curve, and the measured value at the specific point is y0,
y = − (b−y ₀ ) a ^x + b, or
y = (b−y ₀ ) a ^x + b
Assuming that the unknown a in the equation expressed as is an arbitrary value less than 1, the unknown as the convergence value based on the assumed value of the unknown a and the measured value at the first time after the specific time a calculating means for calculating a provisional value of b;
A comparison unit that compares an actual measurement value at a second time point after the first time point with a predicted value at the second time point based on the provisional value calculated by the calculation unit;
A heat transmissivity estimation device, comprising: a determination unit that determines, as the convergence value, the provisional value used to calculate a predicted value determined to be the same as an actual measurement value as a result of comparison by the comparison unit. A program executed by a computer to estimate the thermal conductivity of the surface member as an index representing the heat insulation performance of the surface member located between the indoor space and the outdoor space of the building,
The computer stores the outdoor-side temperature of the surface member, the back-side temperature of the plate-like member disposed so as to be in contact with or close to the indoor surface of the surface member, and the thermal conductivity of the plate-like member. Storage means for
In the process of changing the indoor surface temperature of the surface member, the convergence value of the approximate curve is calculated based on the measured indoor surface temperature of the surface member obtained when the back surface temperature of the plate-like member is constant. A prediction step for predicting a stable temperature of the indoor surface of the surface member,
Based on the stable temperature predicted in the prediction step, the outdoor temperature of the surface member stored in the storage means, the back surface temperature of the plate member, and the thermal conductivity of the plate member. An estimation step for estimating a heat transmissivity of the surface member,
The prediction step includes
The particular point in the change process of the indoor surface temperature of the surface member and x = 0 of the approximate curve, the measured value at the specific point in time when the y0,
y = − (b−y ₀ ) a ^x + b, or
y = (b−y ₀ ) a ^x + b
Assuming an unknown a of the equation expressed as
A method and assumptions unknowns a, based on the actual measurement values in the first time point later than the point in time, calculates a provisional value of the unknown b as the convergence value,
Comparing an actual measurement value at a second time point after the first time point with a predicted value at the second time point based on the calculated provisional value;
Comparison of results, the provisional value used to calculate the same as the determined predicted and measured values, and a step of determining as the convergence value, heat transmission coefficient estimation program.

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