JP3366840B2 - Apparatus quality control method and device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for quality control of equipment, and more particularly, to a method and apparatus for obtaining the accuracy of equipment for evaluating whether or not equipment such as analytical equipment is operating normally. Regarding the device.

[0002]

2. Description of the Related Art In recent years, the importance of guaranteeing the reliability of measurement such as analysis has been generally recognized. In order to guarantee the reliability of such measurement, calibration, management or validation of the equipment used for measurement is required. In addition, it is desired to perform accuracy control of an analytical instrument in order to detect an abnormality during daily management of the instrument. In response to such a background, developmental research on calibration, management or validation of equipment is being conducted.

The conventional quality control of an instrument, in particular, HPLC (High Performance Liquid Chromatography), which is a typical example of an analytical instrument, will be described below. The HPLC outputs the measurement data as an electric signal, the measuring device such as an integrator analyzes the electric signal, and the accuracy of the analytical device is evaluated based on the analysis result. As an HPLC evaluation method, for example, a calibration method of HPLC according to the regulations of JAIMAS (Japan Analytical Instruments Manufacturers Association) is known.

Quantitative accuracy is a universal standard for judging the capability of quantitative analysis methods, and relative standard deviation (RSD) of quantitative values can be used as a standard for the accuracy of analytical instruments. One conventional method of determining RSD is, for example,
The experiment is repeated 5 times under certain HPLC conditions. If the time required for one experiment is 15 minutes, 5
It takes 75 minutes to repeat each time. However, statistically, about 40 repeated experiments (required time is 1
It is said that it is necessary to reach 0 hours)
It is considered that sufficient accuracy cannot be obtained by repeated experiments. However, since it takes about 75 minutes to perform the repeated experiment only five times, the time and labor required for performing the repeated experiment becomes enormous.

Therefore, there is a demand for a method of obtaining accuracy without repeated experiments. Therefore, a theory to evaluate the accuracy of the measurement data by examining the noise and the stochastic properties of the electric signal, which is the final output, was proposed in Yuzuru Hayashi and Rieko Matsuda: Anal. Chem, 66, 2874 (1994). Has been done. In this theory, by focusing on the background noise of the measuring device without mentioning the cause of the error, almost all measuring device noise has the common property of 1 / f fluctuation, and therefore the quantitative accuracy RSD and A mathematical relationship with 1 / f fluctuation has been clarified. Further, this theory points out that the accuracy of almost all analytical instruments can be described by a single basic mathematical formula, so that optimization and evaluation of many analytical instruments can be performed in a unified manner. Further, a method has been proposed in which the property of noise is treated stochastically to predict the degree of error associated with measurement and optimize measurement conditions.

More specifically, the analytical ability parameter that can be directly derived from the above theory is the repeatability.
y), detection limit and quantitation limit
tation limit).

[0007]

In the case of the above-mentioned conventional iterative experimental type accuracy evaluation method, the number of iterations increases, and the time cost and the cost cost increase. Therefore, it is practically impossible to carry out repeated experiments in daily inspection of analytical instruments having a long time for one measurement.

On the other hand, according to the above theory in which the property of noise is treated stochastically, it is not necessary to repeatedly measure,
A reduction in time and cost required for accuracy evaluation can be expected. However, in order to establish standard and general-purpose equipment quality control technology that can be used for daily inspections and is not affected by individual differences in equipment, individual differences in users, etc., the above theory is automatically applied. It is necessary to carry out objective accuracy evaluation.

Furthermore, it is necessary to improve the reliability, standardization and versatility of the quality control device and to obtain traceability to the national measurement standard. Therefore, an object of the present invention is to provide an automated and standardized quality control method and apparatus of a precision evaluation theory that handles the property of noise stochastically in order to solve the above-mentioned problems in the prior art.

Further, the multimeter for converting the electric signal of the equipment into the measurement data is easily affected by temperature and humidity,
Alternatively, the measured values vary due to individual differences of the multimeter, and the accuracy of accuracy control of the device tends to depend on the operating conditions of the multimeter. For this reason, conventionally, in order to measure electric signals with high accuracy using a multimeter, a quality control device including a multimeter must be installed in a calibration room in which environmental conditions such as temperature and humidity are controlled. It is difficult to perform work on a daily basis easily.

Therefore, according to the present invention, the measuring device connected to the equipment is maintained in a constant operating environment to secure the accuracy of the equipment quality control, and the equipment quality control is standardized and versatile. The purpose is to realize a portable quality control device.

[0012]

FIG. 1 is a diagram for explaining the principle of the present invention. INDUSTRIAL APPLICABILITY The present invention evaluates the accuracy of a device that outputs a measurement value including a signal and noise, and in a device verification / calibration system that guarantees a normal operation of the device, the amount of the measurement object dependency of the signal and the noise parameter This is a method for quality control of a device, characterized in that the accuracy of the device is obtained by combining with a quantity representing the dependency of the measurement target (step 31).

The quantity representing the dependence of the signal on the object to be measured is obtained by measuring the sample on the object to be measured with the above-mentioned device (step 11),
It is obtained by calculating the signal statistics for the measurement target from the signals obtained for the measurement target (step 12) and combining the statistics of the signals obtained for the measurement target (step 13).

The quantity representing the dependence of the noise parameter on the measurement object is obtained for the measurement object by acquiring the noise parameter by measuring the power spectrum of the background noise on the measurement object with the above equipment (step 21). The noise parameter statistics of the measurement object are calculated from the noise parameters (step 22), and the noise parameter statistics obtained for the measurement object are combined (step 23).
It is obtained by

As described above, according to the device quality control method of the present invention, a parameter related to a signal and noise is determined by measuring a certain measurement object, and the dependence of the signal on the measurement object and the dependence of the noise parameter on the measurement object are respectively determined. Hierarchical treatment, predicting statistics such as accuracy and detection limit, which were conventionally known only by multiple repeated measurements, and realizing a general-purpose equipment quality control method and device suitable for daily inspection.

According to the present invention, it is possible to predict statistics, such as accuracy and detection limit, based on one measurement of a measurement target. In addition, by measuring a certain measurement target multiple times, the statistic amount of the parameter related to the signal and noise is obtained, and the statistic amount such as the accuracy and the detection limit is predicted using the obtained statistic amount of the parameter related to the signal and noise. To be done.

As the noise parameter, the background noise is converted into a power spectrum, the power spectrum is approximated to white noise and Markov process, one noise parameter is obtained from the white noise, and 2 from the Markov process. It is obtained by acquiring the individual noise parameters. Furthermore, the present invention
Accuracy of equipment that outputs electrical signals including signal and noise
Of the equipment to evaluate and guarantee the normal operation of the equipment.
In a positive system, the electrical signal connected to the device is
Measurement of multi-meter measuring object
An integration process that produces an integrated amount of the signal contained in the value
And the integration of multiple signals obtained for the measurement target
And processes causing obtain statistics of the signal from the amount, a plurality of
From the statistics of the above signals obtained for the measurement target,
Process for obtaining a quantity that expresses the dependence of the signal on the target
And the noise included in the measurement value received from the above multimeter.
Of the power spectrum generated above.
-Probabilistically obtain noise parameter from spectrum
The process and several of the above noises obtained for the measured object.
The noise parameter statistics from the
The process and the above noise obtained for multiple measurement targets
Measurement target of noise parameter from statistical parameter
The process that gives the quantity that represents the dependency and the signal
Dependence of the above signals obtained hierarchically by
And the above obtained hierarchically with respect to noise.
Combined with the quantity that represents the dependence of the noise parameter on the measurement target
In addition, there is a process to obtain the accuracy of the above equipment.
Record equipment quality control program characterized by
Recording medium.

[0018]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 2 is a block diagram showing the principle of a device quality control apparatus according to the present invention. The quality control device 2 of the device of the present invention in the verification / calibration system of the device 10 that evaluates the accuracy of the device that outputs an electrical signal including a signal and noise and guarantees the normal operation of the device includes a multimeter 12,
It comprises an accuracy evaluation means 14 and a portable calibration means 16.

The multimeter 12 is connected to the device 10, measures the electric signal output from the device 10, and generates a measurement value corresponding to the electric signal. The accuracy evaluation means 14 is connected to the multimeter 12,
The measurement value is received from the multimeter 12 to obtain the accuracy of the device 10. The portable calibration means 16 accommodates the multimeter 12, and is provided with a temperature adjusting means 18 and a humidity adjusting means 20.

According to the equipment quality control apparatus 2 of the present invention,
Since the portable calibration means 16 is provided, it can be applied to the quality control of a large-sized analytical instrument which is difficult to move.
The accuracy evaluation means 14 for probabilistically handling the nature of noise to obtain accuracy includes an integration means 22 for generating an integrated amount of a signal included in a measurement value received from the multimeter for the measurement target, and an integration means 22 for the measurement target. Means 24 for obtaining a signal statistic from the integrated amount of the signal, means 26 for obtaining an amount representing the dependence of the signal on the measurement target from the statistic of the signal obtained for the measurement target, and measurement received from the multimeter Fourier transform means 28 for generating a power spectrum of noise included in the value, and means 30 for obtaining a noise parameter from the power spectrum obtained by the Fourier transform means 28 for the measurement target.
A means 32 for obtaining a statistic of a noise parameter from the noise parameter obtained for the measurement object, and a means 34 for obtaining a quantity representing the dependence of the noise parameter on the measurement object from the statistic of the noise parameter obtained for the measurement object. And means 36 for obtaining the accuracy of the device by combining the quantity representing the dependence of the signal on the measurement object and the quantity representing the dependence on the measurement object of the noise parameter.

[0021]

EXAMPLES The accuracy prediction in the chromatography quality control method according to the first embodiment of the present invention will be described below. The accuracy prediction according to the first embodiment of the present invention predicts the accuracy from the signal and noise of the device. Among the analytical performance parameters according to the Japanese Pharmacopoeia, the analytical performance parameters that can be directly derived by the above theory that handles the property of noise stochastically are repeatability, detection limit and quantification limit.

The parameters related to the signal provided by the above-mentioned accuracy prediction are (s1) measured value (setting of integration region of integrator), (s2) measured value after smoothing, (s3) chromatographic parameter (separation degree, etc.). , (S4) statistics of the measured values (mean, standard deviation, relative standard deviation) and (s5) calibration curve, that is, signal concentration dependence.

The noise-related parameters provided by the accuracy prediction are (n1) noise parameters in the theory, (n2) noise parameter statistics (mean, standard deviation, relative standard deviation) and (n3) dispersivity. (sce
dasticity), that is, the density dependence of the noise parameter. In addition, the quantities related to both signal and noise are
(F1) Accuracy curve (analysis accuracy of target substance, detection limit, relative standard deviation), (f2) correlation between theoretical and actual measurements (scatter plot), and (f3) confidence interval of calibration curve.

Here, according to the first embodiment of the present invention,
It should be noted that not only parameters have a hierarchical structure with respect to signals, but both signals and noise are treated hierarchically. FIG. 3 is a diagram for explaining the hierarchical structure of the analytical capability parameters according to the first embodiment of the present invention.
In the above description, the statistic of the measurement value and the statistic of the noise parameter are shown as the parameters relating to the signal and the noise, respectively. These statistics are generally obtained by a plurality of measurements, but in the first embodiment of the present invention, the number of measurements is not limited to a plurality of times, and one measurement may be performed. When the number of measurements is one, for example, the average may be a value measured only once and the variance may be regarded as zero, so that the measurement may be performed in the same manner as in the case of multiple measurements.

The files 111 and 112 shown in FIG.
.. means one data each. For example, it is a text file of a chromatogram obtained from a certain measurement target, that is, a sample of a certain concentration. One signal is obtained from the peak of the target substance in this file. Figure 4
3 is a flowchart showing a hierarchical processing of signal parameters according to the first embodiment of the present invention.

First, a data analysis method is designated (step 51). For example, whether to integrate the entire peak or a part of the peak, or at which position of the peak the height is measured is input. Next, it is determined whether the signal data contained in the file contains much noise (step 52). If much noise is included, smoothing is performed (step 53).
If a lot of noise is not included or after smoothing is performed, parameters such as the position of the maximum value of the peak, the degree of separation peculiar to chromatography, and the number of theoretical plates are obtained (step 54).

Since one signal is obtained for each file, when there are several data (files) at a certain concentration, the statistical amount of signals at that concentration (average,
Standard deviation SD, RSD) is calculated (step 5)
5). Furthermore, a calibration curve is drawn using the signals at different concentrations or the average value of the signals (step 56).

Therefore, the parameters relating to the signal become hierarchical like the measured value -----> the statistic at one concentration -----> the calibration curve. The calibration curve represents how the magnitude of the signal depends on the concentration. FIG. 5 shows the first of the present invention.
4 is a flowchart of a hierarchical process of noise parameters according to the embodiment of FIG. The noise parameters are processed according to the above theory which handles the nature of noise stochastically.

First, one noise data (file)
By Fourier transforming, the three noise parameters consisting of the standard deviation of white noise, the standard deviation of the Markov process and the autocorrelation parameter are obtained (step 61). The above noise parameters give slightly different noise parameters even for background noise recorded under the same measurement conditions. Therefore, the noise parameter statistics are obtained (step 62). For example, if there are a plurality of 2048-point noise data (files), variations in the standard deviation value of white noise (S
D) is required.

In chromatography, since the shape of the signal is peak-shaped (Gaussian type), the appearance of noise appearing on the signal cannot be observed. Therefore, it is assumed that the signal variation at low concentration is due to the baseline noise, and the variation at high concentration is due to the injection error. Further, it is considered that the magnitude of the baseline noise (three noise parameters) is constant regardless of the density. In the case of HPLC, it is possible to obtain accuracy over a wide range of concentrations based on these assumptions. On the other hand, since the signal of the atomic absorption analysis is a rectangular wave, it is possible to observe signal-like noise. Therefore, the density dependence of the noise parameter is obtained (step 63). For this reason, noise data is classified as “noise density”. In practice, noise data is also signal data of the same concentration, so that the measured value of atomic absorption spectrometry can be obtained by integrating this data in a certain section.

Here, the density dependence of the noise parameter is called dispersiveness. If the noise parameter is constant with respect to density, it is called equal variance, and if there is density dependency, it is called non-uniform variance. In the above example, HPLC is equidisperse and atomic absorption spectrometry is non-disperse. In this way, the dispersiveness represents the concentration dependence of the magnitude of the noise, so the dispersiveness of the noise corresponds to the calibration curve of the signal.

Therefore, the hierarchical structure of the noise parameter is: noise parameter -----> statistic for one density-
---> Expressed like dispersibility. Once the calibration curve and the dispersibility are obtained, it is then possible to obtain the accuracy curve, which is a quantity peculiar to the accuracy prediction theory. FIG. 6 is a graph schematically showing the accuracy curve in the case of HPLC. The accuracy curve shown in the figure shows the measurement accuracy of a sample of a certain concentration. Furthermore,
Detection limit (33% RSD) and quantification limit (10% RS
The concentration of D) is immediately known.

The concepts of dispersibility and calibration curve are both included in the definition of detection limit. Both are important analytical stoichiometry. The detection limit can be calculated from the standard deviation of the measured values by repeating the measurement. But,
Repeated measurement takes too much time because of the measurement. On the other hand, according to the quality control method of the first embodiment of the present invention, it is possible to obtain the detection limit from only one measurement.

As described above, it can be seen that the analytical chemical amount has a hierarchy. To calculate the limit of detection, dispersity and a calibration curve are needed. In order to obtain the dispersibility or calibration curve, it is necessary to measure at different concentrations. FIG. 7 is a scatter diagram showing the correlation between the value obtained by repeated measurement and the value predicted by the accuracy prediction of the first embodiment of the present invention for SD of the internal standard method of HPLC. Referring to the figure, the first embodiment of the present invention is
It can be seen that not only the accuracy of instrumental measurement can be predicted, but also the quantitative accuracy of the internal standard method that combines the addition of an internal standard substance using a pipette and the instrumental measurement can be predicted quite accurately.

It is known that even if the calibration curve is created under the same measurement conditions, it will vary little by little as it is created. This variation corresponds to the daily variation of the calibration curve. This daily variation can be predicted statistically or according to the accuracy prediction of the first embodiment of the present invention, and is referred to as the confidence interval of the calibration curve. FIG. 8 is an example of 95% confidence intervals, which are indicated by the dotted lines. When a large number of calibration curves are created under the same conditions, 95% of all the calibration curves are included in this confidence interval. Since the calibration curve varies so as to rotate around the middle point (x, y), the confidence interval becomes narrow in the middle. In order to predict this confidence interval, it is necessary to use the concept of noise dispersion. Therefore, the confidence interval of the calibration curve is at the highest level higher than the calibration curve in terms of dispersibility.

While the first embodiment of the present invention has been described by taking liquid chromatography in the field of separation analysis as an example, the quality control method of the present invention can be applied to a wide field of instrumental analysis. The present invention is not limited to the above description of the first embodiment. The quality control method of the present invention includes the above-mentioned separation analysis, spectroscopic analysis, mass spectrometry, or NM.
It is applied to equipment analysis such as R. In particular, separation analysis includes liquid chromatography, capillary electrophoresis and gas chromatography. As a detector in liquid chromatography, a photomultiplier tube, a photodiode array, a differential refractometer, an electric conductivity meter or an electrochemical detector can be used.

Further, the spectroscopic analysis to which the quality control method of the present invention can be applied includes atomic absorption, fluorescence analysis, visible / ultraviolet absorption analysis and ICP emission analysis. FIG. 9 shows the second embodiment of the present invention.
FIG. 3 is a configuration diagram of a quality control system for an analytical instrument according to the example of FIG. As shown in the figure, the quality control system includes an analytical instrument 10 whose accuracy is to be controlled, a calibration device 40, for example,
It consists of a recorder 42 such as an integrator and a printer 44. The recorder 42 is used for the analytical instrument 10 during normal operation.
And records the signal output from the analytical instrument 10.

The calibration device 40 receives the signal from the analytical instrument 10 and outputs it as a measured value, and the accuracy management unit 14 that receives the measured value output from the multimeter 12 and predicts the accuracy of the analytical instrument. Have and. The accuracy management unit 14 performs the accuracy prediction described in the first embodiment of the present invention. The calibration device 40 further includes a function generator 15 connected between the quality control unit 14 and the recorder 42 and supplying a signal to the recorder 42. The accuracy management unit 14 causes the function generator 15 to generate a pseudo signal in order to confirm the accuracy of the recorder 42. The pseudo signal generated from the function generator 15 is input to the recorder 42 to operate the recorder 42. The accuracy of the recorder 42 is confirmed by monitoring the operation of the recorder 42 with respect to the pseudo signal.

The printer 44 is provided to print the data processed by the accuracy prediction unit 14. Calibration device 40
Is covered with a heat insulating material, the humidity is adjusted by the humidity adjusting sheet, and the temperature is adjusted by the temperature sensor. The temperature sensor is, for example, Pt.
It is formed by a resistance temperature detector such as 100, a thermocouple or a thermistor, and is controlled within a range of ± 0.1 ° C.

The calibration device 40 according to the second embodiment of the present invention is portable, with the multimeter 12, the function generator 15, and the quality control unit 14 including, for example, a personal computer, integrally built therein. As a result, it is possible to bring the calibration device 40 to the place where the analytical instrument 10 whose quality is to be controlled is installed and perform objective and accurate quality control.

FIG. 10 is a block diagram of a quality control system for electrical measurement according to the third embodiment of the present invention. The quality control system for electrical measurement shown in the figure investigates and calibrates the quality of the modem transmission line. The calibration device 40 includes a multimeter 12 and a quality control unit 14. The multimeter 12
It is connected to the receiving section 46 of the modem 45 so as to measure the analog signal output from the separation amplifier of the receiving section 46 of the modem 45. According to such a configuration, the quality control unit 14
Via the multimeter 12 to the receiving section 4 of the modem 45.
It is possible to measure 6 signals and base noise.

Since the noise of the base measured in the third embodiment of the present invention has the property of continuously changing from white noise to 1 / f fluctuation, the quality control method of the present invention is applied to the modem. It is possible to carry out a test, for example, to investigate the error occurrence rate. In the above description, the electrical measurement quality control system according to the third embodiment of the present invention is applied to the test of the modem, but the present system is not limited to such an embodiment. As listed, it is widely applied to communication quality tests in transmission systems. (1) Investigation of error occurrence rate of communication equipment such as modems in metal transmission lines (electric wires), quality inspection of calibration / metal transmission path itself, quality investigation and calibration of reception / transmission portions of communication equipment such as calibration / modems (2) Investigation of error occurrence rate of communication devices such as modems in optical fiber transmission lines, quality inspection of calibration / optical fiber transmission lines themselves, quality inspection of light emitting parts and light receiving parts of communication devices such as calibration / modems,
Calibration (3) Investigation of error occurrence rate of communication equipment such as modem in electromagnetic wave transmission, quality investigation of calibration / electromagnetic wave transmission itself, quality investigation of transmitter and receiver of communication equipment such as calibration / modem,
Calibration FIG. 11 is a perspective view showing the outer shape of the calibration device according to the fourth embodiment of the present invention. As shown in the figure, the calibration device 5
0 is a case 51 with built-in air conditioning unit, a function generator 53, a multimeter 54, an air conditioning system 55.
And a handle 57.

[0043]

As described above, according to the present invention,
When managing the quality of equipment, calibration items are automated and standardized, and there is an advantage that equipment quality control traceable to national measurement standards can be performed. Further, a highly accurate calibration room that can be brought into the examination room can be obtained. Further, according to the present invention, since accuracy management is automated, it is possible to obtain an objective accuracy evaluation of the device in which individual errors and device differences are eliminated.

[Brief description of drawings]

FIG. 1 is a diagram illustrating the principle of the present invention.

FIG. 2 is a principle configuration diagram of a device quality control apparatus according to the present invention.

FIG. 3 is a diagram showing a hierarchical structure of analytical capability parameters according to the first embodiment of the present invention.

FIG. 4 is a flow chart of hierarchical processing of signal parameters according to the first embodiment of the present invention.

FIG. 5 is a flowchart of hierarchical processing of noise parameters according to the first embodiment of the present invention.

FIG. 6 is an example of an HPLC accuracy curve.

FIG. 7 is a scatter plot for SD of HPLC internal standard method.

FIG. 8 is a diagram showing an example of confidence intervals of a calibration curve.

FIG. 9 is a block diagram of a quality control system for analytical instruments according to a second embodiment of the present invention.

FIG. 10 is a configuration diagram of a quality control system for electrical measurement according to a third embodiment of the present invention.

FIG. 11 is an outline view of a calibration device according to a fourth embodiment of the present invention.

[Explanation of symbols]

2 Quality control device 10 equipment 12 Multimeter 14 Accuracy evaluation means 15 Function generator 16 Portable calibration means 18 Temperature control means 20 Humidity adjustment means 22 Signal integration means 24 Signal statistics acquisition means 26 Signal measurement object dependency acquisition means 28 Fourier transforming means 30 noise parameter acquisition means 32 Noise Parameter Statistics Obtaining Means 34 Noise parameter measurement target dependency acquisition means 36 Accuracy acquisition means 40,50 Calibration device 42 recorder 44 printer 45 modem 46 Receiver 51 Case with built-in air conditioning unit 53 Function Generator 54 Multimeter 55 Air conditioning system 57 handle

Continuation of the front page (56) Reference JP-A-2-242120 (JP, A) Bunseki, Japan, The Japan Society for Analytical Chemistry, March 1995, March 1995, pages 195-200, 1995 Drug Discovery Chemistry Research Report, Japan, Human Science Foundation, October 23, 1996, pp. 248-256, Analytical Chemistry, USA, American Chemical Society, September 15, 1994, Vol. 66 No. 18, 2874-2881 (58) Fields investigated (Int.Cl. ⁷ , DB name) G01D 3/00-3/028 G01R 35/00

Claims (5)

(57) [Claims] 1. Outputting a measured value including signal and noise
To evaluate the accuracy of the equipment to ensure the normal operation of the equipment
For equipment verification / calibration systemsQuality control method
And Use the above equipment to measure the background
Stochastic by measuring the power spectrum of the noise
To get the noise parameter to From the above noise parameters obtained for the measurement target
Obtain statistics of noise parameters for the measurement target
Then Statistics of the above noise parameters obtained for the measurement target
The above noise parameters can be measured by combining the quantities.
Get the quantity that represents the target dependency, Measure the sample for the measurement target using the above equipment
To get the above signal, From the signal obtained for the measurement target, the measurement pair
Get signal statistics about the elephant, Combining the statistics of the above signals obtained for the measurement target
By combining them, the dependence of the above signals on the measurement target can be displayed.
Get the amount forgotten, Measurement of the above signals obtained hierarchically with respect to the signal
A hierarchical amount of noise and a quantity that represents the dependency
Shows the dependence of the obtained noise parameters on the measurement target.
To obtain the accuracy of the above equipment, A quality control method for equipment, which is characterized in that 2.Generates electrical signals including signals and noise
Evaluate the accuracy of the applied device and guarantee the normal operation of the device
Equipment quality control equipment in equipment verification / calibration systems
The location, Electrical signals connected to the above equipment and output from the above equipment
Of the electric signal and generates a measurement value corresponding to the above electrical signal.
A lutimeter, Connected to the above multimeter and above
Accuracy evaluation means for receiving the measured values and obtaining the accuracy of the above equipment
When, Housing the above multimeter, temperature control means and humidity control
Portable calibration means provided with means, Is provided, The accuracy evaluation means, For the measurement target, the measurement value received from the above multimeter
Integrating means for generating an integrated amount of the included signal, From the integrated amount of multiple signals obtained for the measurement target
Means to obtain signal statistics, Statistics of the above signals obtained for multiple targets
To obtain a quantity indicating the dependence of the signal on the measurement target
When, Of the noise contained in the measurement value received from the above multimeter
Fourier transform means for generating a power spectrum, Obtained by the above Fourier transform means for the measurement object
Means for obtaining the noise parameter from the power spectrum, Multiple noise parameters obtained for the measurement target
Means for obtaining the statistics of the noise parameter from The above noise parameters obtained for multiple measurement targets
From the statistics of the
A means to obtain Obtained separately and hierarchically in terms of signal and noise
The above-mentioned noise
Combining quantities that represent the dependence of parameters on measurement targets
And means for obtaining the accuracy of the above equipment, Has, A quality control device for equipment, which is characterized in that 3.In transmission systems including transmission lines and communication equipment
A method of testing communication quality according to The noise of the base of the signal transmitted by the above transmission system
Probabilistically by measuring the power spectrum
Parameters, From the noise parameters obtained for the signal, the signal
To get the noise parameter statistics for the The noise obtained for the signal transmitted by the transmission system.
The above parameters can be combined by combining the statistical parameters.
To the shape of the signal for which the noise parameter is measured Dependency of
To get the quantity Measure the sample for the signal transmitted by the above transmission system.
To get the signal, From the above signal obtained for the signal,
Get statistics for all signals, The sig obtained on the signal transmitted by the transmission system.
By combining the null statistics,
Obtains a quantity that represents the dependence on the shape of the signal being measured
Then Signals of the above signals obtained hierarchically with respect to the signal
Hierarchy in terms of noise and noise that expresses the dependence on the shape of the signal
To the signal shape of the above noise parameters obtained
Communication products of the above transmission system in combination with quantities that express dependence
A method characterized by investigating quality. 4.In transmission systems including transmission lines and communication equipment
A device for testing the communication quality of Communication that is connected to the communication device and supports received signals
Measure the analog electrical signal from the device and
A multimeter that produces a measured value corresponding to the Connected to the above multimeter and above
Accuracy control to receive the measured values and obtain the communication quality of the above transmission system
Means and Is provided, The quality control means, The noise of the base of the signal transmitted by the above transmission system
Probabilistically by measuring the power spectrum
Parameters, From the noise parameters obtained for the signal, the signal
To get the noise parameter statistics for the The noise obtained for the signal transmitted by the transmission system.
The above parameters can be combined by combining the statistical parameters.
Dependence of noise parameter on signal shape to be measured
To get the quantity Measure the sample for the signal transmitted by the above transmission system.
Signal by To get From the above signal obtained for the signal,
Get statistics for all signals, The sig obtained on the signal transmitted by the transmission system.
By combining the null statistics,
Obtains a quantity that represents the dependence on the shape of the signal being measured
Then Signals of the above signals obtained hierarchically with respect to the signal
Hierarchy in terms of noise and noise that expresses the dependence on the shape of the signal
To the signal shape of the above noise parameters obtained
Communication products of the above transmission system in combination with quantities that express dependence
A device characterized by investigating the quality. 5. Outputting an electrical signal including signal and noise
Evaluate the accuracy of the applied device and guarantee the normal operation of the device
In the equipment verification / calibration systemA multimedia device that is connected to the equipment and measures the electrical signals.
The measurement target from The signal included in the measurement
An integration process that produces an integral quantity of From the integrated amount of multiple signals obtained for the measurement target
The process of getting signal statistics, Statistics of the above signals obtained for multiple targets
To obtain a quantity that represents the dependence of the signal on the measurement target.
Processes, Of the noise contained in the measurement value received from the above multimeter
Generate a power spectrum,UpPowers generated
Noise parameters from the vectorStochasticallyPro to get
Seth, Multiple noise parameters obtained for the measurement target
The process of getting the statistics of the noise parameter from The above noise parameters obtained for multiple measurement targets
From the statistics of the
The process of gainingMeasurement of the above signals obtained hierarchically with respect to the signal
A hierarchical amount of noise and a quantity that represents the dependency
Got Shows the dependence of the above noise parameters on the measurement target.
Combined with the capacity of the
Seth, A quality control program for equipment characterized by having
Recording medium recorded.