CN118408626B - Dynamic human body weight detection device and detection method - Google Patents
Dynamic human body weight detection device and detection method Download PDFInfo
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- CN118408626B CN118408626B CN202410865429.0A CN202410865429A CN118408626B CN 118408626 B CN118408626 B CN 118408626B CN 202410865429 A CN202410865429 A CN 202410865429A CN 118408626 B CN118408626 B CN 118408626B
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- 238000001514 detection method Methods 0.000 title claims abstract description 34
- 230000037396 body weight Effects 0.000 title claims abstract description 25
- 238000005303 weighing Methods 0.000 claims abstract description 31
- 230000008859 change Effects 0.000 claims abstract description 12
- 238000001914 filtration Methods 0.000 claims description 9
- 230000000694 effects Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000000087 stabilizing effect Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 abstract description 8
- 238000006243 chemical reaction Methods 0.000 abstract description 2
- 230000036541 health Effects 0.000 description 4
- 238000000034 method Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000001684 chronic effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000037221 weight management Effects 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 208000020832 chronic kidney disease Diseases 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
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- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000004260 weight control Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/44—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing persons
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G21/00—Details of weighing apparatus
- G01G21/02—Arrangements of bearings
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G23/00—Auxiliary devices for weighing apparatus
- G01G23/01—Testing or calibrating of weighing apparatus
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G3/00—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances
- G01G3/12—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances wherein the weighing element is in the form of a solid body stressed by pressure or tension during weighing
- G01G3/13—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances wherein the weighing element is in the form of a solid body stressed by pressure or tension during weighing having piezoelectric or piezoresistive properties
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
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Abstract
The invention relates to the technical field of medical monitoring, in particular to a dynamic human body weight detection device, and discloses a detection method of the dynamic human body weight detection device; the weighing device comprises a weighing module and a control module, wherein the weighing module comprises a weighing bracket and a plurality of sensors, at least three fixing plates are arranged on the weighing bracket, each fixing plate is provided with a supporting bottom plate in a pairing mode, the sensors are connected between the fixing plates and the supporting bottom plates, and the plurality of sensors are connected with the control module through lines; the invention has reasonable structure, the resistance value change generated by the strain gauge during deformation is converted into an electric signal after being collected, filtered and amplified, and the human body weight value is calculated according to the corresponding relation of the voltage value after ADC digital-to-analog conversion; the invention is convenient for detecting the dynamic body weight in real time and provides the guardian with quick, convenient and accurate body weight monitoring data.
Description
Technical Field
The invention relates to the technical field of medical monitoring, in particular to a dynamic human body weight detection device and discloses a detection method of the dynamic human body weight detection device.
Background
Weight is an important physiological index, and the weight of a person is influenced by various factors, so that the weight of different persons is different, and the weight of the same person at different time points is also changed. Particularly in the chronic kidney disease group, the diabetes group and other groups requiring strict weight control, the weight of such people is monitored, and the health condition of the people can be accurately mastered through the change of the weight.
Most of the existing weight monitoring modes are universal, and personalized weight management is not carried out according to special physical conditions and health requirements of chronic patients. The weight management of chronic patients needs to take factors such as the type, severity, medication condition and the like of the diseases into consideration, so that a more scientific and reasonable management scheme can be formulated; the existing weight monitoring method mainly records weight measurement values in a specific time area each time, does not combine multiple factors to analyze the dynamic change of the weight, and cannot provide a rapid, convenient and accurate human body weight monitoring method for guardianship personnel; lack of pertinence and instantaneity: most of the existing intelligent weight detection schemes are based on the existing health data for analysis and suggestion, and lack pertinence and instantaneity. These applications cannot directly sense the physical condition, health condition and environmental change of the user, and the user is required to input related data by himself or connect with other intelligent devices for data collection.
Accordingly, the prior art is still in need of improvement and development.
Disclosure of Invention
The invention aims to overcome the defects and shortcomings of the prior art and provide a dynamic human body weight detection device and a detection method for detecting the weight of a human body in real time through a sensor and obtaining weight data through algorithm analysis.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
The invention relates to a dynamic human body weight detection device which comprises a weighing module and a control module, wherein the weighing module comprises a weighing bracket and a plurality of sensors, at least three fixing plates are arranged on the weighing bracket, each fixing plate is provided with a supporting bottom plate in a pairing mode, the sensors are connected between the fixing plates and the supporting bottom plates, and the plurality of sensors are connected with the control module through lines.
According to the scheme, four strain gauges are arranged in the sensor, and the four strain gauges form a Wheatstone bridge circuit.
According to the scheme, the control module is integrated with the amplifier chip and the ADC, and signals of the sensor are processed by the amplifier and the ADC and then sent to the control module.
According to the scheme, the invention further comprises a touch display screen and a power supply, and the control module is connected with the touch display screen and the power supply through lines.
According to the scheme, the weighing bracket is provided with four fixing plates, and the four fixing plates are respectively arranged at four corners of the weighing bracket; one end of the sensor is fixedly connected with the supporting bottom plate, and the other end of the sensor is fixedly connected with the fixing plate.
The detection method of the dynamic human body weight detection device comprises the steps that a sensor sends data to a control module, and the control module executes the following steps:
step A, initial calibration;
Step B, AD of the weight value of the human body is adopted and converted;
step C, stabilizing the weight value by a PID control algorithm;
d, executing a creep algorithm for 3 times to perform temperature accumulated error compensation;
And E.N times of filtering, and taking an average value to obtain an accurate weight value.
According to the above scheme, the formula of the PID control algorithm in step C is as follows:
u(t)=a+Kp*e(t)+Ki*∫e(t)dt+Kd*e'(t)
wherein: a is the initial number of times of the detection device, u (t) is the control amount, e (t) is the deviation, e' (t) is the rate of change of the deviation, kp is the proportionality coefficient, ki is the integral coefficient, kd is the differential coefficient.
According to the above scheme, the creep algorithm in step D comprises:
Comparing the current acquired sensor deformation acquisition AD value Va1 and the temperature AD value Vt1 with the corresponding values acquired last time, and judging whether creep is transmitted or not by combining the initial calibration values Xa and Xt and judging the current sampling value, wherein the creep state comprises a positive creep state and a negative creep state;
According to the state of the first creep, the positive states Xa and Xt take positive values, the negative states Xa and Xa take negative values, the AD value Va2 and the temperature AD value Vt2 are acquired through the second sensor deformation, the absolute value of the difference between the AD value Va and the temperature AD value Vt2 is judged again, whether the absolute value exceeds a threshold K1 or not is judged, and the magnitude P of the creep is judged;
And judging whether the absolute value of the calibration value exceeds the average threshold value M again according to the calibration amplitude P obtained for the second time and acquiring the AD value Va3 and the temperature AD value Vt3 acquired for the third time of sensor deformation, judging the effect after creep, if the deviation from the actual value is within a reasonable accuracy range, determining that the parameters Xa, xt, P and M are effective parameters, otherwise, carrying out proper adjustment.
The invention has the beneficial effects that: the invention has reasonable structure, adopts the Wheatstone four-bridge sensor, converts the resistance change generated by the strain gauge during deformation into an electric signal after acquisition, filtering and amplification, and calculates the weight value of the human body according to the corresponding relation of the voltage value after ADC digital-to-analog conversion.
The invention is convenient for detecting the dynamic body weight in real time and provides the guardian with rapid, convenient and accurate body weight monitoring data (the accuracy reaches 10-50 g).
Drawings
FIG. 1 is a schematic view of a weighing module configuration of the present invention;
FIG. 2 is a schematic diagram of the overall architecture of the detection device of the present invention;
FIG. 3 is a schematic flow chart of the detection method of the present invention;
FIG. 4 is a schematic flow chart of a creep algorithm of the present invention;
fig. 5 is a schematic diagram of the internal wiring of the sensor of the present invention.
In the figure: 1. a control module; 2. a touch display screen; 3. a weighing bracket; 4. a sensor; 5. a power supply; 11. a fixing plate; 12. and a supporting bottom plate.
Detailed Description
The technical scheme of the invention is described below with reference to the accompanying drawings and examples.
As shown in fig. 1-2, the dynamic human body weight detection device comprises a weighing module and a control module 1, wherein the weighing module comprises a weighing bracket 3 and a plurality of sensors 4, at least three fixing plates 11 are arranged on the weighing bracket 3, each fixing plate 11 is provided with a supporting bottom plate 12 in a pairing mode, the sensors 4 are connected between the fixing plates 11 and the supporting bottom plates 12, and a plurality of the sensors 4 are connected with the control module 1 through lines.
Four strain gauges are arranged in the sensor 4, and the four strain gauges form a Wheatstone bridge circuit. The control module 1 is integrated with an amplifier chip and an ADC digital-to-analog converter, and the signals of the sensor 4 are processed by the amplifier and the ADC digital-to-analog converter and then sent to the control module 1.
The invention further comprises a touch display screen 2 and a power supply, wherein the control module 1 is connected with the touch display screen 2 and the power supply 5 through a circuit. The weighing bracket 3 is preferably provided with four fixing plates 11, and the four fixing plates 11 are respectively arranged at four corners of the weighing bracket 3; the four fixing plates 11 are pairwise and symmetrically arranged on the weighing bracket 3, so that the weighing bracket 3 ensures the stability of the weighing bracket, and the accuracy of the detection data of the sensor 4 is ensured. One end of the sensor 4 is fixedly connected with the supporting bottom plate 12, and the other end of the sensor 4 is fixedly connected with the fixing plate 11.
The sensor comprises four strain gauges, wherein the four strain gauges form a Wheatstone bridge circuit, and the internal wiring of the sensor is shown in figure 5.
The wheatstone bridge circuit may measure resistance in various ways:
① Determining an absolute value of the resistance by comparing with a known resistance;
② The relative change in resistance was measured.
The latter method is used in strain technology, which can measure the relative change of strain gage resistance, and the accuracy can reach 10 < -4 > to 10 < 2 > ohm/ohm.
The detection principle of the sensor 4 is as follows:
Four legs or branches of the wheatstone bridge are made up of four resistors R1, R2, R3 and R4. Corner points 2 and 3 of the bridge indicate the connection of the bridge excitation voltage Vs; corner points 1 and 4 are bridge output voltages Vo, i.e. measurement signals.
If a supply voltage Vs is applied to the bridge terminals 2 and 3, the supply voltage is divided by R1, R2 and R4, R3 into two half-bridges, i.e. each half-bridge forms a voltage divider.
The bridge may be unbalanced due to the different resistance voltages of R1, R2 and R3, R4. The formula of the calculation materials is as follows:
According to this formula, it is assumed that the ratio α of Vo/Vs is measured. When three of the resistance values R1, R2, R3, R4 are known, the 4 th resistance value can be calculated. The resistance is proportional to the weight, and when standard weights, such as 100g and measured values, are calibrated, the weight of the object can be obtained.
As shown in fig. 3-4, a detection method of a dynamic body weight detection device, the sensor 4 sends data to the control module 1, and the control module performs the following steps:
step A, initial calibration;
Step B, AD of the weight value of the human body is adopted and converted;
step C, stabilizing the weight value by a PID control algorithm;
d, executing a creep algorithm for 3 times to perform temperature accumulated error compensation;
And E.N times of filtering, and taking an average value to obtain an accurate weight value.
The formula of the PID control algorithm in the step C is as follows:
u(t)=a+Kp*e(t)+Ki*∫e(t)dt+Kd*e'(t)
wherein: a is the initial number of times of the detection device, u (t) is the control amount, e (t) is the deviation, e' (t) is the rate of change of the deviation, kp is the proportionality coefficient, ki is the integral coefficient, kd is the differential coefficient.
Wherein the proportionality coefficient Kp controls the magnitude of the deviation. When the deviation is larger, the control amount is larger, and the system response speed is faster.
The integral coefficient Ki controls the integration of the deviation. The system can eliminate accumulation of deviation as the control amount is larger as the deviation integral is larger.
The differential coefficient Kd controls the rate of change of the deviation. The larger the deviation change rate is, the larger the control amount is, and the system can prevent the overshoot of the system.
The creep algorithm in the step D comprises the following steps:
Comparing the current acquired sensor deformation acquisition AD value Va1 and the temperature AD value Vt1 with the corresponding values acquired last time, and judging whether creep is transmitted or not by combining the initial calibration values Xa and Xt and judging the current sampling value, wherein the creep state comprises a positive creep state and a negative creep state;
According to the state of the first creep, the positive states Xa and Xt take positive values, the negative states Xa and Xa take negative values, the AD value Va2 and the temperature AD value Vt2 are acquired through the second sensor deformation, the absolute value of the difference between the AD value Va and the temperature AD value Vt2 is judged again, whether the absolute value exceeds a threshold K1 or not is judged, and the magnitude P of the creep is judged;
And judging whether the absolute value of the calibration value exceeds the average threshold value M again according to the calibration amplitude P obtained for the second time and acquiring the AD value Va3 and the temperature AD value Vt3 acquired for the third time of sensor deformation, judging the effect after creep, if the deviation from the actual value is within a reasonable accuracy range, determining that the parameters Xa, xt, P and M are effective parameters, otherwise, carrying out proper adjustment.
And finally, carrying out Kalman filtering treatment on the weight value under the effective parameters to obtain concurrent Chu Kaer Mans filtering data, and carrying out median filtering treatment on the N times of filtering data to obtain a stable and accurate weight value.
The accurate human body weight data is obtained through a PID algorithm and a creep filtering algorithm; according to the weighing system, the weight detection support is supported by 4 sensors, the data of the sensors are received by the control module 1 of the weighing system, the data are analyzed and calculated through an algorithm and transmitted to the touch display screen, and the data are displayed in a digital mode, so that the weighing purpose is achieved. The invention can provide the guardian with rapid, convenient and accurate human body weight monitoring data (the accuracy reaches 10-50 g).
The foregoing description is only of the preferred embodiments of the invention, and all changes and modifications that come within the meaning and range of equivalency of the structures, features and principles of the invention are therefore intended to be embraced therein.
Claims (5)
1. The utility model provides a dynamic human body weight detection device, includes weighing module and control module, its characterized in that: the weighing module comprises a weighing bracket and a plurality of sensors, at least three fixing plates are arranged on the weighing bracket, each fixing plate is provided with a supporting bottom plate in a matched mode, the sensors are connected between the fixing plates and the supporting bottom plates, and the plurality of sensors are connected with the control module through lines;
the detection method of the dynamic human body weight detection device comprises the steps that the sensor sends data to the control module, and the control module executes the following steps:
step A, initial calibration;
Step B, AD of the weight value of the human body is adopted and converted;
step C, stabilizing the weight value by a PID control algorithm;
d, executing a creep algorithm for 3 times to perform temperature accumulated error compensation;
Filtering E.N times, and taking an average value to obtain an accurate weight value;
the formula of the PID control algorithm in the step C is as follows:
u(t)=a+Kp*e(t)+Ki*∫e(t)dt+Kd*e'(t)
Wherein: a is the initial number of times of the detection device, u (t) is a control quantity, e (t) is a deviation, e' (t) is a change rate of the deviation, kp is a proportionality coefficient, ki is an integral coefficient, and Kd is a differential coefficient;
the creep algorithm in step D includes:
Comparing the current acquired sensor deformation acquisition AD value Va1 and the temperature AD value Vt1 with the corresponding values acquired last time, and judging whether creep is transmitted or not by combining the initial calibration values Xa and Xt and judging the current sampling value, wherein the creep state comprises a positive creep state and a negative creep state;
According to the state of the first creep, the positive states Xa and Xt take positive values, the negative states Xa and Xa take negative values, the AD value Va2 and the temperature AD value Vt2 are acquired through the second sensor deformation, the absolute value of the difference between the AD value Va and the temperature AD value Vt2 is judged again, whether the absolute value exceeds a threshold K1 or not is judged, and the magnitude P of the creep is judged;
And judging whether the absolute value of the calibration value exceeds the average threshold value M again according to the calibration amplitude P obtained for the second time and acquiring the AD value Va3 and the temperature AD value Vt3 acquired for the third time of sensor deformation, judging the effect after creep, if the deviation from the actual value is within a reasonable accuracy range, determining that the parameters Xa, xt, P and M are effective parameters, otherwise, carrying out proper adjustment.
2. The dynamic body weight detection device of claim 1, wherein: four strain gauges are arranged in the sensor, and the four strain gauges form a Wheatstone bridge circuit.
3. The dynamic body weight detection device of claim 1, wherein: the control module is integrated with an amplifier chip and an ADC, and signals of the sensor are processed by the amplifier and the ADC and then sent to the control module.
4. The dynamic body weight detection device of claim 1, wherein: the touch control display screen and the power supply are connected through a circuit.
5. The dynamic body weight detection device of claim 1, wherein: four fixing plates are arranged on the weighing bracket and are respectively arranged at four corners of the weighing bracket; one end of the sensor is fixedly connected with the supporting bottom plate, and the other end of the sensor is fixedly connected with the fixing plate.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110834853A (en) * | 2019-11-14 | 2020-02-25 | 南京英诺森软件科技有限公司 | Cargo weighing system based on cloud platform and detection method thereof |
| CN117760536A (en) * | 2024-01-04 | 2024-03-26 | 山东大学 | Creep state identification and compensation method for high-precision weighing sensor |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CH675158A5 (en) * | 1988-06-14 | 1990-08-31 | Mettler Toledo Ag | |
| CN1297803C (en) * | 2004-07-23 | 2007-01-31 | 孔令宇 | Float weighing sensor and PID deviation control method for dynamic coeighing |
| JP4525262B2 (en) * | 2004-09-14 | 2010-08-18 | 株式会社島津製作所 | Weighing device |
| JP4752528B2 (en) * | 2006-02-08 | 2011-08-17 | 株式会社島津製作所 | Strain gauge type load cell and electronic scale using the same |
| CN100533311C (en) * | 2007-09-19 | 2009-08-26 | 山西万立科技有限公司 | Embedded type weighing system based on intelligent fuzzy control |
| JP5600415B2 (en) * | 2009-07-30 | 2014-10-01 | 現代自動車株式会社 | Electric vehicle motor position and creep control device and control method thereof |
| CN206886075U (en) * | 2017-07-06 | 2018-01-16 | 大唐环境产业集团股份有限公司 | A kind of totally-enclosed lime stone belt of weighing batcher weighing control device |
| CN110849459B (en) * | 2019-10-24 | 2022-02-22 | 华帝股份有限公司 | Creep deformation correction method for weighing sensor |
| CN114326630A (en) * | 2021-12-30 | 2022-04-12 | 镇江鑫海自动化技术有限公司 | Intelligent weighing and batching control method for asphalt mixture |
| CN116907621A (en) * | 2023-08-15 | 2023-10-20 | 广州医科大学附属第一医院 | Creep compensation method and device for weighing sensor, medium and weighing equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110834853A (en) * | 2019-11-14 | 2020-02-25 | 南京英诺森软件科技有限公司 | Cargo weighing system based on cloud platform and detection method thereof |
| CN117760536A (en) * | 2024-01-04 | 2024-03-26 | 山东大学 | Creep state identification and compensation method for high-precision weighing sensor |
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