JP2002228495A - Meter evaluation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a meter evaluation system capable of accurately evaluating the past calibration data to estimate a meter characteristic value and capable of accurately judging the renewing period of a meter to extend the calibration cycle of the meter. SOLUTION: When a meter characteristic value is operated on the basis of the past calibration data (S300), a correlation coefficient is operated (S500) and it is judged whether there is the correlation with time in the meter characteristic value (S600). When there is correlation, a regression straight line is operated (S700) and it is judged whether there is a deterioration tendency in the meter (S800). When there is the deterioration tendency, meter renewal judging processing A is carried out (S1100). When there is no deterioration tendency, meter renewal judging processing A is carried out (S900) and next time calibration omitting advisabilty judging processing A is carried out (S1000). When there is no correlation, meter renewal judging processing B is carried out (S1200) and next time calibration omitting advisability judging processing is carried out (S1300).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an instrument evaluation system for analyzing a change with time of an instrument characteristic value representing an input / output characteristic of an instrument to evaluate a tendency of the instrument.

[0002]

2. Description of the Related Art Periodic inspection of equipment is indispensable for maintaining stable operation of a plant, and inspection and calibration of instruments are important items for maintaining stable operation. For example, an instrument calibration data system that visualizes and displays an accuracy graph based on calibration data at the time of each periodic inspection is known. In general, the timing and contents of the inspection and calibration of instruments can be determined by the user's judgment and responsibility except for instruments that have legal requirements, but in practice, the inspection and calibration of all instruments are uniformly performed at each periodic inspection. Had been implemented. However, the user wants to perform an inspection calibration appropriate for the condition of the instrument. For example, an inspection calibration cycle extension method that extends the inspection calibration cycle within a range where the indication error of the instrument does not exceed the required value (accuracy in operating conditions), or an instrument update that rationally determines the instrument update time Users are demanding a method of determining the timing and a method of improving the inspection and calibration method.

Here, in the method of extending the inspection and calibration cycle, instruments are grouped according to common terms such as types and operating conditions, and tens to hundreds of points of data in the same group are statistically processed. The instrument calibration value is predicted based on the processing result, and the inspection and calibration cycle is extended. In the method of determining the instrument update time, the accuracy error amount is converted into a point every time, and the update time is determined based on the accumulated value. On the other hand, an improvement method of the inspection calibration method can be realized by analyzing the inspection calibration data, but at present, the user does not have the method.

[0004]

However, according to the conventional method of extending the inspection calibration cycle, when the calibration data is analyzed by grouping the instruments into groups classified by type and capsule range,
Due to large variation in instrument characteristic values within the group,
A valid instrument characteristic value could not be predicted. For this reason, in the conventional method of extending the inspection calibration cycle, it is not realistic to predict the instrument characteristic value based on the analysis of the group data.

Further, in the conventional method of determining the update time of an instrument, the accuracy error amount is converted into a score every time, and the update time is determined based on the accumulated value. Was apparently not working. For this reason, at present, an instrument update plan is actually drafted based on the instrument importance and the budget frame considered by the user. On the other hand, for example, the number of electronic pressure transmitters used in one plant is about 600, the number of inspection points per unit is nine, and the number of past inspection calibrations is nine.
The number of calibration history data is 600 × 9 × 9 = 48
600. However, there is no instrument evaluation system that analyzes and evaluates such a huge amount of inspection calibration data.

SUMMARY OF THE INVENTION It is an object of the present invention to appropriately evaluate past calibration data to predict an instrument characteristic value, and to accurately determine an update time of an instrument and extend a calibration cycle of the instrument. It is to provide an evaluation system.

[0007]

The present invention solves the above-mentioned problems by the following means. Note that the description will be given with reference numerals corresponding to the embodiments of the present invention, but the present invention is not limited to this. The invention according to claim 1 is an instrument evaluation system for analyzing a change with time of an instrument characteristic value representing an input / output characteristic of an instrument to evaluate a tendency of the instrument, wherein a phase of the instrument characteristic value and the time is analyzed. Calculate the relation number (S
500) a correlation coefficient calculating section (9), and a correlation determining section for determining whether or not the meter characteristic value has a correlation with the time based on the calculation result of the correlation coefficient calculating section (S600). (10) An instrument evaluation system (1) including:

According to a second aspect of the present invention, in the instrument evaluation system according to the first aspect, when the correlation coefficient is larger than a predetermined value, the correlation determining section determines whether or not the correlation between the instrument characteristic value and the time is provided. The instrument evaluation system is characterized in that the instrument characteristic value is judged not to be correlated with the time when the correlation coefficient is determined to be present and the correlation coefficient is smaller than a predetermined value.

[0009] The invention of claim 3 is claim 1 or claim 2.
Wherein the regression line calculation unit (700) calculates a regression line between the meter characteristic value and the time (S700) when the meter characteristic value has a correlation with the time; Based on the calculation result of the straight line calculation unit, it is determined whether or not the meter has a tendency to deteriorate (S8).
00) is an instrument evaluation system including a deterioration tendency determination unit (12).

According to a fourth aspect of the present invention, in the instrument evaluation system according to the third aspect, the deterioration tendency judging section judges that the instrument has a tendency to deteriorate when the slope of the regression line is larger than a predetermined value. If the slope of the regression line is smaller than a predetermined value, it is determined that the regression line does not tend to deteriorate.

[0011] The invention of claim 5 is the invention of claims 1 to 4.
In the instrument evaluation system according to any one of the above, the instrument characteristic value at the next inspection is predicted and calculated based on the instrument characteristic value up to the current inspection (S2000, S4000).
An instrument evaluation system comprising a characteristic value prediction calculation unit (13).

According to a sixth aspect of the present invention, in the instrument evaluation system according to the fifth aspect, when the characteristic value predicting operation unit has a correlation with the time, the characteristic value predicting operation unit includes the regression line and the instrument characteristic. Based on the standard error with the value and the slope of the regression line, the instrument characteristic value at the next inspection is predicted and calculated (S2000). When the instrument characteristic value has no correlation with the time, the average of the instrument characteristic value is calculated. Based on the value and the standard deviation, the instrument characteristic value at the next inspection is predicted (S4
000).

[0013] The invention of claim 7 is the invention of claim 5 or claim 6.
In the instrument evaluation system described in the above, the characteristic value prediction calculation unit, when it is predicted that the instrument characteristic value at the next inspection is within the allowable range, based on the instrument characteristic value up to the current inspection, at the time of the second inspection Calculation of the instrument characteristic value (S23)
00, S4300).

According to an eighth aspect of the present invention, in the instrument evaluation system according to the seventh aspect, when the characteristic value predicting operation section has a correlation with the time, the characteristic value predicting operation section includes the regression line and the instrument characteristic. Based on the standard error with respect to the value and the slope of the regression line, the instrument characteristic value at the time of the second inspection is predicted and calculated (S2300), and when the instrument characteristic value has no correlation with the time, the average of the instrument characteristic value is calculated. The instrument evaluation system is characterized in that the instrument characteristic value at the time of the second inspection is predicted and calculated (S4300) based on the value and the standard deviation.

[0015] The invention of claim 9 is the invention of claim 7 or claim 9
In the meter evaluation system described in (1), it is determined whether or not the meter needs to be updated based on the calculation result of the characteristic value prediction calculation unit (S2100, S2400, S410).
0, S4400), which is an instrument evaluation system.

According to a tenth aspect of the present invention, in the instrument evaluation system according to the ninth aspect, the update availability determination unit determines whether or not the instrument characteristic value at the next inspection is out of an allowable range. An instrument evaluation system characterized in that it is determined that it is necessary to immediately update (S2200, S4200).

According to an eleventh aspect of the present invention, in the instrument evaluation system according to the ninth or tenth aspect, the update availability determination unit determines whether the instrument characteristic value at the time of the next inspection is out of the allowable range. It is determined that the instrument needs to be updated at the next inspection (S2900, S4900),
An instrument evaluation system characterized in that when it is predicted that the instrument characteristic value at the time of the next inspection is within the allowable range, it is determined that the instrument need not be updated at the next inspection (S2800, S4800).

According to a twelfth aspect of the present invention, in the instrument evaluation system according to the ninth or tenth aspect, when the instrument characteristic value at the time of the next inspection is predicted to be within an allowable range, the instrument is evaluated up to the current inspection. It is determined whether the drift directions of the characteristic values are the same and whether the sum of the drift amounts of the instrument characteristic values up to the time of this inspection exceeds a predetermined value (S2600).
An instrument evaluation system is provided with a drift amount accumulation determining unit (14).

According to a thirteenth aspect of the present invention, in the instrument evaluation system according to the twelfth aspect, the renewal determination section determines that when the drift direction is the same and the sum of the drift amounts exceeds a predetermined value. It is determined that the instrument needs to be updated at the next inspection (S2700, S470)
0) Then, if the drift directions are not the same and the sum of the drift amounts is less than a predetermined value, it is determined that the instrument need not be updated at the next inspection (S280).
0, S4800).

According to a fourteenth aspect of the present invention, in the meter evaluation system according to any one of the ninth to thirteenth aspects, when the meter does not have a tendency to deteriorate, it is based on the meter characteristic values up to the present inspection. The instrument evaluation system further includes an error prediction operation unit (16) for predicting and calculating (S3100, S5100) the instrument error at the time of successive inspection.

According to a fifteenth aspect of the present invention, in the instrument evaluation system according to the fourteenth aspect, when the instrument characteristic value has a correlation with the time, the error predicting operation section includes the regression line and the instrument characteristic value. Is calculated based on the standard error of the regression line and the standard error of the regression line (S3100). When there is no correlation between the instrument characteristic value and the time, the average value of the instrument characteristic value is calculated. Based on the standard deviation, predictive calculation of the instrument error at the time of successive inspection (S
5100).

According to a sixteenth aspect of the present invention, in the instrument evaluation system according to the fourteenth or fifteenth aspect, it is determined whether or not calibration of the instrument can be omitted at the next inspection based on a calculation result of the error prediction calculation unit. (S3000, S32
(00, S5000, S5200) is an instrument evaluation system characterized by including a calibration omission determination section (17).

According to a seventeenth aspect of the present invention, in the instrument evaluation system according to the sixteenth aspect, the calibration omission determination unit determines that the instrument error at the time of the next inspection is within the allowable range, and the next time the inspection is performed. It is determined that the calibration of the instrument can be omitted (S3300, S5300), and if it is predicted that the instrument error at the time of the second inspection is outside the allowable range, it is determined that the calibration of the instrument cannot be omitted at the next inspection (S3400, S3400). S5400).

According to an eighteenth aspect of the present invention, in the instrument evaluation system according to the sixteenth aspect, the calibration omission determination unit determines the number of times of the next inspection (n is 2) based on the calculation result of the error prediction calculation unit. An instrument evaluation system characterized in that it is determined whether calibration of the instrument can be omitted based on the above integer).

According to a nineteenth aspect of the present invention, in the instrument evaluation system according to the seventeenth aspect, the calibration omission determination section predicts that the instrument error at the time of the (n + 1) -time inspection is within an allowable range. Sometimes, it is determined that the calibration of the instrument can be omitted at the time of the nth inspection, and when the instrument error at the time of the (n + 1) th inspection is expected to be out of the allowable range, at the time of the nth inspection, An instrument evaluation system characterized in that it is determined that calibration of the instrument cannot be omitted.

[0026]

Embodiments of the present invention will be described below in more detail with reference to the drawings. FIG. 1 is a configuration diagram of an instrument evaluation system according to an embodiment of the present invention. FIG. 2 is a configuration diagram of a calibration system of the instrument evaluation system according to the embodiment of the present invention. Instrument evaluation system 1
Is a system for analyzing a change of an instrument characteristic value representing an input / output characteristic of an instrument with time and evaluating a tendency of the instrument.

The information transmitting means 3 shown in FIG. 1 is means for transmitting the calibration data from the calibration system 2 to the analysis system 4. The information transmitting means 3 transmits information via a network or the like, for example.

The analysis system 4 is a system for analyzing calibration data. As shown in FIG. 1, the analysis system 4 includes a data input device 5 and a data processing device 6. The data input device 5 is a device that reads out the calibration data using the information transmission means 3 and outputs the data to the data processing device 6.

FIG. 3 is a block diagram of an analysis system of the instrument calibration system according to the embodiment of the present invention. The data processing device 6 is a device for analyzing the instrument calibration data and evaluating the tendency of the instrument. As shown in FIG. 4, the data processing device 6 includes an instrument characteristic value calculator 7, an importance classifier 8, a correlation coefficient calculator 9, a correlation determiner 10, a regression line calculator 11, Trend determination unit 12 and characteristic value prediction calculation unit 13
, Drift amount accumulation determining unit 14, and update availability determining unit 15
, An error prediction operation unit 16 and a calibration omission determination unit 17
And a display unit 18 and a printing unit 19.

The instrument characteristic value calculation section 7 is an operation section for calculating an instrument characteristic value representing input / output characteristics of the instrument for each instrument.
The instrument characteristic value computing section 7 computes zero drift, span drift, linearity, hysteresis, and static pressure characteristics for each instrument. Here, the zero drift is the amount of change in the measured value lower limit from the previous calibration to the current calibration. The span drift is the amount of change in the lower limit of the measured value and the upper limit of the measured value from the previous calibration to the current calibration. The linearity is a deviation amount of the measured value from a straight line connecting the measured value lower limit value and the measured value upper limit value. The hysteresis is the amount of deviation between the measured value at the time of rising and the measured value at the time of falling. The static pressure characteristic is a pressure difference between the high-pressure diaphragm and the low-pressure diaphragm when the same pressure is applied to the transmitter. Instrument characteristic value calculator 7
Outputs information on the instrument characteristic value to the correlation coefficient operation unit 9, the regression line operation unit 11, the characteristic value prediction operation unit 13, the drift amount accumulation determination unit 14, and the error prediction operation unit 16.

The importance classifying section 8 is a block for classifying instruments according to their importance. The importance classifying unit 8, for example,
The instruments are classified into three ranks of importance A, B, and C based on whether the function of the equipment stops due to a failure or whether the instrument stops due to a failure or repair.

The correlation coefficient calculator 9 is a calculator for calculating a correlation coefficient between an instrument characteristic value and time. Correlation coefficient calculator 9
Calculates the correlation coefficient between the instrument characteristic value and time for each instrument, and outputs information on the correlation coefficient to the correlation determination unit 10.

The correlation judging section 10 is a judging section for judging whether or not the instrument characteristic value has a correlation with time based on the calculation result of the correlation coefficient calculating section 9. When the correlation coefficient is larger than a predetermined value, the correlation judging unit 10 judges that the instrument characteristic value has a correlation with time, and when the correlation coefficient is smaller than the predetermined value, the correlation between the instrument characteristic value and the time is determined. Judge that there is no. The correlation determination unit 10 outputs the information on the presence or absence of the correlation to the characteristic value prediction calculation unit 13 and the error prediction calculation unit 16.

FIG. 4 is a diagram for explaining a judgment method of the correlation judgment unit of the instrument evaluation system according to the embodiment of the present invention. FIG. 4A shows a case where there is a correlation between the instrument characteristic value and time. FIG. 4B shows a case where there is no correlation between the instrument characteristic value and time. The vertical axis shown in FIG. 4 is a span drift which is one of the instrument characteristic values, and the horizontal axis is the number of days. FIG.
As shown in FIG. 4A, when the correlation coefficient is large, the instrument characteristic value has a correlation with time, and as shown in FIG.
When the correlation coefficient is small, the instrument characteristic value has no correlation with time. In this embodiment, the standard of the threshold value (predetermined value) for the presence or absence of correlation is set to 0.7 (absolute value), and this absolute value is determined by evaluating an actual measurement value.

The regression line calculation unit 11 shown in FIG. 3 is a calculation unit that calculates a regression line between an instrument characteristic value and time when the instrument characteristic value has a correlation with time. Regression line calculation unit 1
1 calculates a regression line between the instrument characteristic value and time for each instrument, and outputs information on the regression line to the deterioration tendency determination unit 12.

The deterioration tendency judging section 12 includes a regression line calculating section 1
A determination unit that determines whether or not the meter has a tendency to deteriorate based on the result of the calculation of (1). The deterioration tendency judging unit 12 judges that the instrument is in the tendency of deterioration when the slope of the regression line is larger than a predetermined value, and judges that the instrument is not in the tendency of deterioration when the inclination of the regression line is smaller than the predetermined value. The deterioration tendency determining unit 12 outputs information on the presence or absence of the deterioration tendency to the characteristic value prediction calculating unit 13 and the update availability determining unit 15.

FIG. 5 is a diagram for explaining a judgment method of the deterioration tendency judging section of the instrument evaluation system according to the embodiment of the present invention. FIG. 5 (A) shows a case where there is a deterioration tendency.
FIG. 5B shows a case where there is no deterioration tendency. The vertical axis shown in FIG. 5 is a span drift which is one of the instrument characteristic values, and the horizontal axis is the number of days. As shown in FIG. 5 (A), when the slope of the regression line is large, the instrument tends to deteriorate, and as shown in FIG. 5 (B), when the slope of the regression line is small, the instrument has no tendency to deteriorate and the time dependency There is. In this embodiment, a level at which the amount of change during 900 days exceeds 50% of the instrument accuracy is set as the threshold value (standard value). Where 90
0 days is the number of days corresponding to two times when the interval of the periodic inspection is 450 days, and when the calibration is omitted once (skipped), the amount of change in the instrument characteristic value is 5 times the instrument accuracy.
A level of 0% was assumed. Further, in this embodiment, the monitoring level which has a time-dependent variation of 50% to 15% of the instrument accuracy is time-dependent and required.

As shown in FIG. 5A, the deterioration tendency judging section 12 calculates the slope m of the regression line m = 2.9 × 10 ⁻⁴ (% / day).
, The change for 900 days (instrument accuracy ± 0.
5%) = 2.9 × 10 ⁻⁴ × 900 = 0.26, so it is determined that there is a tendency for deterioration. On the other hand, the deterioration tendency determining unit 1
2 is the slope m of the regression line, as shown in FIG.
In the case of 1.2 × 10 ⁻⁴ (% / day), the amount of change during 900 days (instrument accuracy ± 0.5%) = 1.2 × 10 ⁻⁴ × 9
00 = 0.11 and it is determined that there is a time dependency instead of a deterioration tendency.

The characteristic value predicting / calculating section 13 shown in FIG. 3 is a calculating section for predicting and calculating the instrument characteristic value at the next inspection based on the instrument characteristic value up to the current inspection. When the instrument characteristic value at the time of the next periodic inspection is predicted to be within the allowable range, the characteristic value prediction calculation unit 13 calculates the instrument characteristic value at the time of the next periodic inspection based on the instrument characteristic value up to the current periodic inspection. Perform prediction operation. When there is a correlation between the instrument characteristic value and the time, the characteristic value prediction calculation unit 13 determines the instrument characteristic value at the next inspection and the next and next inspection based on the standard error between the regression line and the instrument characteristic value and the slope of the regression line. Is calculated. On the other hand, when there is no correlation between the instrument characteristic value and the time, the characteristic value prediction computing unit 13 predicts and computes the instrument characteristic value at the next inspection and at the next inspection based on the average value and the standard deviation of the instrument characteristic value. I do.

FIG. 6 is a diagram for explaining a prediction method of the characteristic value predicting operation unit of the instrument evaluation system according to the embodiment of the present invention. FIG. 6A shows that the instrument characteristic value has time dependency. FIG. 6B shows a case where the instrument characteristic value has no time dependency (no correlation). The vertical axis shown in FIG. 6 is a span drift which is one of the instrument characteristic values, and the horizontal axis is the number of days. The characteristic value prediction calculation unit 13 is configured as shown in FIG.
As shown in (A), when there is time dependence, the range (predicted value) F of the instrument characteristic value at the next periodic inspection is calculated by the following equation 1 based on the slope of the regression line and the standard error. . F = E + m * T ± SE * P (Equation 1) where m is the slope of the regression line, SE is the standard error between the regression line and the actually measured value, and T is the interval (day) for one periodic inspection. Where E is a calculated value (regression value) at the time of the regular inspection this time, and P is a coefficient that determines the range of prediction.

On the other hand, the characteristic value prediction calculation unit 13
As shown in (B), when there is no time dependency, the predicted value F at the next periodic inspection is based on the average value and the standard deviation.
Is calculated by the following equation (2). F = Ave ± σ * Q (Equation 2) where Ave is an average value, σ is a standard deviation,
Q is a coefficient that determines the width of the prediction.

When judging whether or not to update the meter, it is necessary to predict the next (one after another from the present time) meter characteristic value, assuming that the calibration was correctly performed at the next periodic inspection.
As shown in FIG. 6A, when there is a time dependency, the characteristic value prediction calculation unit 13 doubles the interval T for one periodic inspection and calculates the predicted value F at the time of the next periodic inspection as Is calculated by F = E + m * (T * 2) ± SE * P (Equation 3) On the other hand, as shown in FIG. 6B, when there is no time dependency, the prediction value at the next periodic inspection is the prediction value at the next periodic inspection. Same as value. The characteristic value prediction calculation unit 13 calculates by varying the coefficients P and Q according to the importance of the instrument.

The drift amount accumulation judging section 14 shown in FIG.
When it is predicted that the instrument characteristic value at the time of the next inspection is within the allowable range, the drift direction of the instrument characteristic value up to the current inspection is the same, and the sum of the drift amounts of the instrument characteristic value until the current inspection is obtained. Is greater than a predetermined value (a predetermined multiple of the instrument precision). The drift amount accumulation calculating unit 15 outputs information on the drift amount accumulation to the update availability determination unit 15.

The update permission / inhibition judging section 15 is a judgment section for judging whether or not the instrument needs to be updated based on the operation result of the characteristic value prediction operation section 13. Update availability determination unit 15
Determines that the instrument needs to be updated immediately when the instrument characteristic value at the next periodic inspection is predicted to be out of the allowable range. Further, when it is predicted that the instrument characteristic value at the time of the next periodic inspection is out of the allowable range, the update availability determination unit 15 determines that the instrument needs to be updated at the next periodic inspection, and the meter at the time of the next periodic inspection. When the characteristic value is predicted to be within the allowable range, it is determined that there is no need to update the instrument. On the other hand, if the instrument characteristic values to be evaluated are the zero drift and the span drift, the drift directions are the same, and the sum of the drift amounts exceeds a predetermined value, the Is determined to be necessary, and if the drift directions are not the same and the sum of the drift amounts is less than a predetermined value, it is determined that the instrument need not be updated at the next inspection.

The error prediction calculating section 16 is a calculating section for predicting and calculating the meter error at the time of the next and subsequent inspections based on the instrument characteristic values up to the current inspection, when the instrument is not in a tendency to deteriorate. When there is a correlation between the instrument characteristic value and the time, the error prediction calculating unit 16 predicts and calculates the instrument error at the time of successive inspection based on the standard error between the regression line and the instrument characteristic value and the slope of the regression line. When there is no correlation between the characteristic value and the time, an instrument error at the time of the second inspection is predicted and calculated based on the average value and the standard deviation of the instrument characteristic value. Error prediction operation unit 1
6 is a unit 17 for determining whether or not calibration error can be omitted.
Output to

When the instrument characteristic values are zero drift and span drift and the instrument characteristic values have a correlation with time, the error prediction calculation unit 16 performs the next and subsequent periodic inspections based on the slope of the regression line and the standard error. Drift prediction value (instrument error prediction value) D is calculated by the following equation (4). D = (E + m * T) * A ± SE * B (Equation 4) Here, A is a probability coefficient of the drift amount one after another,
B is a coefficient that determines the prediction width one after another. The error prediction calculation unit 16 multiplies the drift value (E + m * T) by k1 and the prediction width (± SE * P) by k2 based on the next drift prediction value shown in Expression 1. In this embodiment, k1 and k2 = 2 are set as standard values.

On the other hand, when the instrument characteristic values are linearity, hysteresis, and static pressure characteristics and the instrument characteristic values have a correlation with time, the error prediction calculation unit 16 repeats one after another based on the slope of the regression line and the standard error. The instrument error prediction value D at the time of the periodic inspection is calculated by the following equation (5). D = m * (T * 2) + E ± SE * B (Equation 5)

When the instrument characteristic value is zero drift and span drift and there is no correlation between the instrument characteristic value and time, the error prediction calculation unit 16 calculates the instrument error at the time of the next periodic inspection based on the average value and the standard error. The predicted value D is expressed by the following Equation 6.
Is calculated by D = Ave * X ± σ * Y (Equation 6) Here, X is a probability coefficient of the drift amount one after another,
Y is a coefficient that determines the prediction width one after another.

On the other hand, when the instrument characteristic values are linearity, hysteresis, and static pressure characteristics and the instrument characteristic values do not correlate with time, the error prediction calculation unit 16 performs a periodic inspection based on the average value and the standard error one after another. Instrument error prediction value D
Is calculated by the following equation (7). D = Ave ± σ * Y (Equation 7)

The calibration omission determination section 17 determines whether or not the calibration of the instrument can be skipped (skipped) at the next inspection based on the calculation result of the error prediction calculation section 16. The calibration omission determination unit 17 determines that the maximum error up to the time of this periodic inspection is the instrument accuracy / predetermined value (within a predetermined range)
Is determined. When it is predicted that the instrument error at the time of the next inspection is within the allowable range, the calibration omission determination section 17 judges that the calibration of the instrument can be omitted at the next inspection, and the instrument error at the time of the next inspection is allowed. If it is predicted to be out of the range, it is determined that the calibration of the instrument cannot be omitted at the next inspection.

FIG. 7 is a diagram for explaining a determination method of the calibration omission determination section of the meter evaluation system according to the embodiment of the present invention. The vertical axis shown in FIG. 7 is a span drift which is one of the instrument characteristic values, and the horizontal axis is the number of days. As shown in FIG. 7, the calibration omission determination unit 17 determines that the drift amount for one periodic inspection interval is within the range of the next predicted width, and the drift amount for two periodic inspection intervals is within the range of the next predicted width. If, it is determined that the calibration at the next periodic inspection can be omitted.

The display section 18 shown in FIG. 3 is an apparatus for displaying on the screen an instrument chart which is basic information on the instrument, an instrument replacement history, a calibration record, whether or not calibration can be skipped and an update time. The printing unit 19 is a device that prints an instrument chart.

Next, the operation of the instrument evaluation system according to the embodiment of the present invention will be described. FIG. 8 is a flowchart for explaining the operation of the meter evaluation system according to the embodiment of the present invention. Step (hereinafter referred to as S) 100
In, the calibration data is processed. The data processing device 2a shown in FIGS. 1 and 2 processes the past calibration data and outputs it to the database 2b, and the data output device 2c.
And the data output device 2c outputs the calibration data to the information transmitting means 3.

At S200, instrument calibration data is read. The data input device 5 reads out the calibration data recorded in the information transmitting means 3 shown in FIG. 1 and outputs it to the data processing device 6, and the data processing device 6 reads the calibration data.

In S300, an instrument characteristic value is calculated. The instrument characteristic value computing section 7 computes zero drift, span drift, linearity, hysteresis, and static pressure characteristics for each instrument based on the calibration data output from the data input device 5.

In S400, the degree of importance is classified.
The importance classifying unit 8 classifies the respective instruments into three stages of A, B, and C according to the importance.

In S500, a correlation coefficient is calculated. The correlation coefficient calculator 9 calculates a correlation coefficient based on the information on the instrument characteristic value output from the instrument characteristic value calculator 7.

In S600, it is determined whether or not the instrument characteristic value has a correlation with time. As shown in FIG. 4, the correlation determining unit 10 determines whether or not the instrument characteristic value has a correlation with time based on the information on the correlation coefficient output from the correlation coefficient calculating unit 9. When the correlation coefficient calculator 9 determines that there is a correlation, the process proceeds to S700, and when the correlation coefficient calculator 9 determines that there is no correlation, the process proceeds to S1200.

In S700, a regression line is calculated. The regression line calculation unit 11 calculates a regression line based on the information on the instrument characteristic value output from the instrument characteristic value calculation unit 7.

In S800, it is determined whether or not there is a tendency for deterioration. As illustrated in FIG. 5, the deterioration tendency determining unit 12 determines whether or not the meter has a deterioration tendency based on the information on the regression line output by the regression line calculation unit 11. When the deterioration tendency determining unit 12 determines that there is no deterioration tendency, the process proceeds to S900, and when the deterioration tendency determining unit 12 determines that there is a deterioration tendency, the process proceeds to S1100.

At S900, an instrument update determination process A is executed. The characteristic value prediction calculation unit 13 predicts and calculates an instrument characteristic value according to Equations 1 and 3, and calculates the drift amount accumulation determination unit 1
4 calculates the drift direction and the drift amount,
The update availability determination unit 15 determines whether the instrument can be updated.

In step S1000, a next calibration skip determination processing A is executed. Equation 4
The instrument error is calculated using Equation 5 and Equation 5, and the calibration omission determination section 17 determines whether the instrument calibration can be omitted at the next periodic inspection.

In S1100, the instrument update determination processing A
Is executed. If the instrument is in a deteriorating tendency, S90
As in the case of 0, the instrument update determination processing A is executed. However, since the instrument is in the caution state, the next calibration skip availability determination processing A is not executed.

In S1200, the instrument update determination processing B
Is executed. The characteristic value prediction calculation unit 13 predicts and calculates an instrument characteristic value according to Equation 2, the drift amount accumulation determination unit 14 calculates the drift direction and the drift amount, and the update availability determination unit 15 determines whether the instrument can be updated.

In S1300, a next calibration skipping / non-permission determining process B is executed. Equation 6
The instrument error is calculated using Equation 7 and Equation 7, and the calibration omission determination section 17 determines whether the instrument calibration can be omitted at the next periodic inspection.

Next, a description will be given of an instrument update determination process A of the instrument evaluation system according to the embodiment of the present invention. FIG. 9 is a flowchart for explaining the instrument update determination processing A of the instrument update system according to the embodiment of the present invention. S2
000, the next characteristic value prediction A is executed. FIG.
The characteristic value prediction calculation section 13 shown in (1) predicts and calculates the instrument characteristic value at the time of the next periodic inspection based on the instrument characteristic value calculated by the meter characteristic value calculation section 7 using Equation 1.

In S2100, it is determined whether or not the next characteristic value prediction is within an allowable range. Update availability determination unit 1
5 determines whether or not the instrument characteristic value at the time of the next periodic inspection is within an allowable range, based on the instrument characteristic value at the time of the next periodic inspection, which is predicted and calculated by the characteristic value prediction operation unit 13. When it is determined that the instrument characteristic value at the next inspection is not within the allowable range, the process proceeds to S2200, and when it is determined that the instrument characteristic value at the next inspection is within the allowable range, the process proceeds to S2300.

In S2200, immediate update is recommended. When it is predicted that the instrument characteristic value at the time of the next inspection exceeds the allowable range, the update availability determination unit 15 recommends that the instrument be replaced immediately.

In S2300, characteristic value prediction A
Is executed. The characteristic value prediction calculating section 13 predicts and calculates the instrument characteristic value at the time of the second periodic inspection based on the instrument characteristic value calculated by the meter characteristic value calculating section 7 according to Equation 3.

At S2400, it is determined whether the characteristic value prediction is within the allowable range one after another. The update availability determination section 15 determines whether or not the instrument characteristic value at the time of the second inspection is within the allowable range based on the instrument characteristic value at the time of the second inspection, which is predicted and calculated by the characteristic value prediction operation section 13. When it is determined that the instrument characteristic value at the time of the second inspection is within the allowable range, the process proceeds to S2500, and when it is determined that the instrument characteristic value at the time of the second inspection is not within the allowable range, the process proceeds to S2900.

In S2500, it is determined whether the evaluation item is zero draft or span drift. The update availability determination unit 15 determines whether the evaluation item is zero draft or span drift, and proceeds to S2600 when the evaluation item is zero draft or span drift, and proceeds to S2800 when the evaluation item is not zero draft or span drift. .

At S2600, it is determined whether the drift directions are the same and the sum exceeds a predetermined value. The drift amount accumulation determination unit 14 determines whether the drift direction of the instrument characteristic value is the same up to the current periodic inspection and whether the sum of the drift amounts of the instrument characteristic value up to the current periodic inspection has exceeded a predetermined value. to decide. When the drift directions are the same and the sum of the drift amounts exceeds a predetermined value, the process proceeds to S2700, and when the drift directions are not the same and the sum of the drift amounts is less than the predetermined value, the process proceeds to S2800.

At S2700, the next update is recommended. The update permission / inhibition judging unit 15 judges from the drift tendency so far and recommends that the instrument be updated at the next periodic inspection.

In S2800, it is determined that the next update is unnecessary. The update availability determination unit 15 determines that it is not necessary to update the instrument at the next periodic inspection because the instrument characteristic value is predicted to be within the allowable range at the next periodic inspection and at the next periodic inspection.

In S2900, the next update is recommended. Even if the instrument is correctly calibrated at the next periodic inspection, the update availability determination unit 15 recommends updating the instrument at the next periodic inspection because the instrument characteristic value is expected to exceed the allowable range at the next periodic inspection.

Next, the next calibration skip determination processing A of the instrument evaluation system according to the embodiment of the present invention will be described. FIG. 10 is a flowchart for explaining the next calibration skipping possibility determination process A of the instrument updating system according to the embodiment of the present invention. In S3000, it is determined whether or not the maximum error is within a predetermined range. The calibration omission determination section 17 determines whether or not the maximum error up to the current periodic inspection is within a predetermined range. When the maximum error up to the current periodic inspection is within the predetermined range, the process proceeds to S3100, and when the maximum error up to the current periodic inspection is outside the predetermined range, the process proceeds to S3400.

In S3100, error prediction A is performed one after another. The error prediction calculation section 16 predicts and calculates the meter error at the time of the next periodic inspection based on the instrument characteristic values calculated by the instrument characteristic value calculation section 7 using Equations 4 and 5.

At S3200, it is determined whether the error prediction is within an allowable range one after another. The calibration omission determination section 17 determines whether or not the instrument error at the time of the next periodic inspection is within an allowable range, based on the instrument error predicted and calculated by the error prediction calculation section 16. If the instrument error at the time of the second periodic inspection is within the allowable range, the process proceeds to S3300, and if the instrument error at the time of the second periodic inspection is not within the allowable range, the process proceeds to S3300.
Proceed to 3400.

In S3300, it is determined that the next calibration skip is possible. The calibration omission determination section 17
If the instrument characteristic values up to this time of the periodic inspection are good and the instrument does not have a tendency to deteriorate, and it is predicted that the instrument error at the next periodic inspection is within the allowable range, it is possible to omit the calibration of the instrument at the next periodic inspection. to decide.

In S3400, it is determined that the next calibration skip is not possible. Calibration omission determination section 17
If the maximum error up to the current periodic inspection exceeds the range of instrument accuracy / predetermined value, or if the instrument error during the next periodic inspection exceeds the allowable range, it is necessary to omit calibration of the instrument at the next periodic inspection. to decide.

Next, a description will be given of an instrument update determination process B of the instrument evaluation system according to the embodiment of the present invention. FIG.
It is a flowchart for demonstrating the instrument update determination process B of the instrument update system which concerns on embodiment of this invention. The instrument update determination processing B includes S4000 and S4000 corresponding to S2000 and S2300 of the instrument update determination processing A shown in FIG.
4300 is different from the prediction calculation method. Hereinafter, only S4000 and S4300 shown in FIG. 11 will be described, and the same steps as those shown in FIG. 9 will be denoted by the same reference numerals and detailed description thereof will be omitted.

In S4000, next characteristic value prediction B is executed. When there is no correlation between time and the instrument characteristic value computed by the instrument characteristic value computing section 7, the characteristic value prediction computing section 13 shown in FIG.

In S4300, characteristic value prediction B
Is executed. The characteristic value predicting operation unit 13 predicts and calculates the instrument characteristic value at the time of the next periodic inspection based on the instrument characteristic value calculated by the instrument characteristic value calculating unit 7 according to Equation 2.

Next, the next calibration skip determination processing B of the instrument evaluation system according to the embodiment of the present invention will be described. FIG. 12 is a flowchart for explaining the next calibration skipping availability determination process B of the instrument updating system according to the embodiment of the present invention. The next calibration skip enable / disable determination process B is a next calibration skip enable / disable determination process A shown in FIG.
Is different from S5100 corresponding to S3100 of FIG. Hereinafter, only S5100 shown in FIG. 12 will be described, and the same steps as those shown in FIG. 10 will be denoted by the same reference numerals and detailed description thereof will be omitted. S5
At 100, the error prediction B is performed one after another. When there is no correlation between the instrument characteristic value computed by the instrument characteristic value computing section 7 and time, the error prediction computing section 16 predicts and computes the instrument error at the time of the second periodic inspection by the following equations (6) and (7).

FIG. 13 is a diagram showing a prediction result of the instrument characteristic value of the instrument updating system according to the embodiment of the present invention.
The prediction result shown in FIG. 13 is a result of predicting the instrument characteristic value at the time of the ninth regular inspection without considering the instrument importance based on the calibration data at the time of the past eight regular inspections. FIG.
3 (A) is a prediction result based on the latest three calibration data, FIG. 13 (B) is a prediction result based on the latest five calibration data, and FIG. 13 (C) is a prediction result based on the latest seven calibration data. It is. Here, “A. With time dependency (with correlation)” is a prediction result by Expression 1, and “B. Without time dependency (without correlation)” is a prediction result by Expression 2,
“A + B” is the sum of these prediction results. k = 1
k = 1.5 and k = 2 are coefficients P and Q shown in Equations 1 and 2.
Corresponding to Evaluation item Z is zero drift, S is span drift, H is hysteresis, and L is linearity. The number of hits is the number (the number of tags) and the ratio (%) in which the actual measurement value at the time of the nine regular inspections falls within the prediction range at the time of the nine regular inspections. As shown in FIG. 13, the prediction accuracy increases as the number of calibration data items increases. Also,
In the case of k = 1 where the width of prediction is narrow and strict, the number included in the prediction range is smaller and the ratio is smaller than in the case of k = 2 where the width of prediction is wide and gradual.

The calibration omission determination section can omit the calibration of the meter based on the calculation result of the error prediction calculation section not only at the next time but also at the time of n-times inspection (n is an integer of 2 or more). It may be determined whether or not.

Further, the calibration omission / non-judgment determining section is not limited to the successive times, and when the instrument error at the time of the inspection after (n + 1) times is predicted to be within the allowable range, the calibration of the meter at the time of the n times inspection is performed. May be omitted, and when it is predicted that the instrument error at the time of the (n + 1) -time inspection and inspection is out of the allowable range, it may be determined that the calibration of the instrument cannot be omitted at the time of the n-th inspection. .

The following is a supplementary explanation of terms used in the embodiments.

Mean Represents the arithmetic mean (arithmetic mean).

[Formula 1]

Standard Deviation The standard deviation for the population is expressed.

[Formula 2] Standard deviation is a measure of how widely a statistically significant value is distributed from its average

Slope of regression line A regression line is obtained from the known x and y data by the least square method.

[Equation 3] The slope of the regression line is given by the above equation

Standard deviation This is a measure for measuring the degree of error between the predicted value of y and the actually measured value with respect to the individual value of x.

(Equation 4)

Correlation coefficient The correlation coefficient is used to determine the relationship between two characteristics (X, Y). The correlation coefficient is in the range of +1 to -1, and the closer the absolute value is to 1, the stronger the correlation.

(Equation 5)

The meter evaluation system according to this embodiment has the following effects. (1) In this embodiment, a correlation coefficient between an instrument characteristic value and time is calculated to determine whether or not the instrument characteristic value has a correlation with time. As a result, it is possible to clarify the maintenance guidelines and the like of the instrument by analyzing the history data relating to the inspection and calibration of the instrument, and to correctly recognize the behavior and tendency of the instrument.

(2) In this embodiment, the instrument characteristic values at the next periodic inspection are predicted and calculated based on the instrument characteristic values up to the current periodic inspection. As a result, it is possible to predict instrument characteristic values from past calibration data to quantify the time dependence of instrument characteristic values, and to model and quantify the predictive calculation of instrument characteristic values at the next periodic inspection. can do.

(3) In this embodiment, it is determined whether or not the instrument needs to be updated based on the result of the prediction calculation of the instrument characteristic value. As a result, it is possible to accurately determine and determine the update time of the instrument.

(4) In this embodiment, it is determined whether or not the calibration of the instrument can be omitted at the next periodic inspection based on the calculation result of the instrument error prediction. As a result, the inspection and calibration cycle of the instrument can be extended.

(5) In this embodiment, five instrument characteristic values of zero drift, span drift, linearity, hysteresis, and static pressure characteristic are evaluated. As a result, it is possible to clarify the evaluation items of the instrument characteristics, not just the evaluation of the instrument accuracy, and accurately evaluate the instrument characteristic values from the past calibration data.

The present invention is not limited to the embodiment described above, but can be variously modified or changed.
These are also within the scope of the present invention. For example, in this embodiment, the threshold (standard value) is set to a level at which the amount of change for 900 days exceeds 50% of the instrument accuracy, but the threshold may be re-evaluated and updated by future trend analysis. Good. Further, the instrument characteristic values at the time of the N regular inspections and at the time of the N + 1 regular inspections may be predicted and calculated to determine whether or not the N regular inspections can be updated and whether or not the calibration can be omitted. Further, the calibration system 2 and the analysis system 4 may be integrated, or the calibration system 2 and the analysis system may be connected by communication means other than the information recording medium.

[0100]

As described above, according to the present invention, the correlation coefficient between an instrument characteristic value and time is calculated to determine whether or not the instrument characteristic value has a correlation with time. Calibration data can be accurately evaluated.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of an instrument evaluation system according to an embodiment of the present invention.

FIG. 2 is a configuration diagram of a calibration system of the instrument evaluation system according to the embodiment of the present invention.

FIG. 3 is a block diagram of an analysis system of the instrument calibration system according to the embodiment of the present invention.

FIG. 4 is a diagram for explaining a judgment method of a correlation judgment unit of the instrument evaluation system according to the embodiment of the present invention;
(A) is a case where there is a correlation between the instrument characteristic value and time,
(B) is a case where there is no correlation between the instrument characteristic value and time.

FIG. 5 is a diagram for explaining a judgment method of a deterioration tendency judgment unit of the instrument evaluation system according to the embodiment of the present invention;
(A) shows a case where the image has a tendency to deteriorate, and (B) shows a case where the image does not have a deterioration tendency.

6A and 6B are diagrams for explaining a prediction method of a characteristic value prediction calculation unit of the instrument evaluation system according to the embodiment of the present invention. FIG. 6A illustrates a case where the instrument characteristic value has a time dependency (correlation exists). (B) is a case where the instrument characteristic value has no time dependency (no correlation).

FIG. 7 is a diagram for explaining a determination method of a calibration omission determination section of the meter evaluation system according to the embodiment of the present invention.

FIG. 8 is a flowchart for explaining the operation of the meter evaluation system according to the embodiment of the present invention.

FIG. 9 is a flowchart illustrating an instrument update determination process A of the instrument update system according to the embodiment of the present invention.

FIG. 10 is a flowchart for explaining a next calibration skip possibility determination process A of the instrument updating system according to the embodiment of the present invention.

FIG. 11 is a flowchart illustrating an instrument update determination process B of the instrument update system according to the embodiment of the present invention.

FIG. 12 is a flowchart for explaining a next calibration skip possibility determination process B of the instrument updating system according to the embodiment of the present invention.

FIG. 13 is a diagram showing a prediction result of an instrument characteristic value of the instrument updating system according to the embodiment of the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Instrument evaluation system 2 Calibration system 3 Information transmission means 4 Analysis system 6 Data processing device 7 Instrument characteristic value operation part 9 Correlation coefficient operation part 10 Correlation judgment part 11 Regression line operation part 12 Deterioration tendency judgment part 13 Characteristic value prediction operation part 14 Drift amount accumulation determination unit 15 Update availability determination unit 16 Error prediction calculation unit 17 Calibration omission availability determination unit

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Tomonori Teramon 1-6-1, Otemachi, Chiyoda-ku, Tokyo Japan Nuclear Power Co., Inc. (72) Ryohei Kita 6-3-1, Sakaemachi, Tachikawa-shi, Tokyo No. Yokogawa Engineering Service Co., Ltd. (72) Inventor Hiroshi Itakura 1-3-1, Sakaemachi, Tachikawa-shi, Tokyo (72) Inventor Hironobu Sonoda 6 Sakaemachi, Tachikawa-shi, Tokyo No. 1-3, F-term in Yokogawa Engineering Service Co., Ltd. (reference) 2F076 AA00 BA12 BA16 BA18

Claims (19)

[Claims] 1. An instrument evaluation system for analyzing a change with time of an instrument characteristic value representing an input / output characteristic of an instrument to evaluate a tendency of the instrument, wherein a correlation coefficient between the instrument characteristic value and the time is provided. A correlation coefficient calculating unit that calculates the correlation coefficient calculating unit; and a correlation determining unit that determines whether the meter characteristic value has a correlation with the time based on the calculation result of the correlation coefficient calculating unit. system. 2. The instrument evaluation system according to claim 1, wherein the correlation determining unit determines that the instrument characteristic value has a correlation with the time when the correlation coefficient is larger than a predetermined value; When the correlation coefficient is smaller than a predetermined value,
Determining that the instrument characteristic value has no correlation with the time. 3. The instrument evaluation system according to claim 1, wherein when the instrument characteristic value has a correlation with the time, a regression line for calculating a regression line between the instrument characteristic value and the time. An instrument evaluation system, comprising: an operation unit; and a deterioration tendency determination unit that determines whether or not the instrument has a deterioration tendency based on the operation result of the regression line operation unit. 4. The instrument evaluation system according to claim 3, wherein the deterioration tendency judging section judges that the instrument is deteriorating when the slope of the regression line is larger than a predetermined value, and determines the regression line. When the slope of the instrument is smaller than a predetermined value, it is determined that the apparatus does not tend to deteriorate. 5. The method according to claim 1, wherein:
2. The instrument evaluation system according to claim 1, further comprising: a characteristic value predicting operation unit that predicts and calculates an instrument characteristic value at the next inspection based on the instrument characteristic value up to the current inspection. 6. The instrument evaluation system according to claim 5, wherein the characteristic value prediction calculation unit is configured to determine a standard error between the regression line and the instrument characteristic value when the instrument characteristic value has a correlation with the time. And, based on the slope of the regression line, predictive calculation of the instrument characteristic value at the next inspection, when the instrument characteristic value has no correlation with the time, based on the average value and the standard deviation of the instrument characteristic value A predictive calculation of an instrument characteristic value at the next inspection; 7. The instrument evaluation system according to claim 5, wherein the characteristic value predicting operation unit determines that the instrument characteristic value at the time of the next inspection is within the allowable range, and that the characteristic value prediction operation unit performs the current inspection. A predictive calculation of the instrument characteristic value at the time of the second inspection based on the instrument characteristic value up to and including: 8. The instrument evaluation system according to claim 7, wherein the characteristic value predicting / calculating section includes a standard error between the regression line and the instrument characteristic value when the instrument characteristic value has a correlation with the time. And, based on the slope of the regression line, to predict and calculate the instrument characteristic value at the time of the second inspection, when the instrument characteristic value has no correlation with the time, based on the average value and the standard deviation of the instrument characteristic value A predictive calculation of an instrument characteristic value at the time of successive inspections. 9. The instrument evaluation system according to claim 7, wherein whether or not the instrument needs to be updated is determined based on a calculation result of the characteristic value prediction calculation unit. An instrument evaluation system, comprising: 10. The instrument evaluation system according to claim 9, wherein the update availability determination unit needs to immediately update the instrument when it is predicted that the instrument characteristic value at the next inspection is out of an allowable range. Determining that there is a meter evaluation system. 11. The instrument evaluation system according to claim 9, wherein the update availability determination unit is configured to perform the update at the next inspection when it is predicted that the instrument characteristic value at the time of the next inspection is out of an allowable range. When it is determined that the instrument needs to be updated and the instrument characteristic value at the time of the next inspection is predicted to be within the allowable range,
Determining that there is no need to update the instrument at the next inspection. 12. The instrument evaluation system according to claim 9, wherein when the instrument characteristic value at the time of the second inspection is predicted to be within an allowable range, the drift direction of the instrument characteristic value until the current inspection. And a drift amount accumulating judging unit for judging whether or not the sum of the drift amounts of the instrument characteristic values up to the current inspection exceeds a predetermined value. 13. The instrument evaluation system according to claim 12, wherein the update availability determination unit is configured to perform the update at the next inspection when the drift direction is the same and the sum of the drift amounts exceeds a predetermined value. When the drift direction is not the same and the sum of the drift amounts is less than a predetermined value, it is determined that it is not necessary to update the instrument at the next inspection. Instrument evaluation system. 14. The instrument evaluation system according to any one of claims 9 to 13, wherein when said instrument is not in a tendency to deteriorate, said instrument is inspected one after another based on instrument characteristic values up to the present inspection. An instrument evaluation system, comprising: an error prediction operation unit that predicts and calculates the instrument error. 15. The instrument evaluation system according to claim 14, wherein, when the instrument characteristic value has a correlation with the time, a standard error between the regression line and the instrument characteristic value. Based on the slope of the regression line, an instrument error at the time of successive inspections is predicted and calculated. A predictive calculation of an instrument error at the time of inspection; 16. The instrument evaluation system according to claim 14, wherein the calibration of the instrument can be omitted at the next inspection based on a calculation result of the error prediction calculation unit. An instrument evaluation system, comprising: an availability determination unit. 17. The instrument evaluation system according to claim 16, wherein the calibration omission determination section performs calibration of the instrument at the next inspection when it is predicted that the instrument error at the next inspection is within an allowable range. If it is judged that it can be omitted and the instrument error at the time of the second inspection is expected to be out of the allowable range,
Determining that calibration of the instrument cannot be omitted at the next inspection. 18. The instrument evaluation system according to claim 16, wherein the calibration omission / non-possibility determining unit performs n-times inspection (n is an integer of 2 or more) based on a calculation result of the error prediction calculation unit. Determining whether or not calibration of the instrument can be omitted. 19. The instrument evaluation system according to claim 17, wherein the calibration omission determination unit determines that the instrument error at the time of the (n + 1) -time inspection is within an allowable range.
Judging that the calibration of the instrument can be omitted at the time of the subsequent inspection,
If the instrument error at the time of the (n + 1) -time inspection is predicted to be outside the allowable range, it is determined that the calibration of the instrument cannot be omitted at the time of the n-th inspection.