JPS59211196A - Response abnormality diagnosing equipment for detector - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a detector response abnormality diagnosing device, and more particularly to a detector response abnormality diagnosing device that can be applied to detectors used in nuclear power plants, thermal power plants, and the like.

For example, fluctuations (minor fluctuations) in the process can be used as a method for diagnosing abnormalities in the responsiveness (response time) of a sensor that measures the plant process when it is installed in a plant. In other words, process fluctuations excite the sensor, causing minute fluctuations around the steady state value (this is a characteristic of process noise, called a process characteristic), so the steady state value is removed from the sensor output data and the remaining Abnormalities in sensor responsiveness are diagnosed by enlarging and analyzing minute fluctuations and extracting sensor characteristics (characteristics possessed by sensor self-defense) contained therein.

A specific analysis method in this case will be explained with reference to FIG. In FIG. 1, the autocovariance function of noise data is calculated from data input 1 in step 2.

Next, using this value, a weighting coefficient for fitting the noise time series data to a regression model with a value of 3 is determined. From this coefficient, the impulse response is calculated with 4, the initial response is calculated with 5, and the sensor response time τ is estimated from the time it takes to reach 63.2% of the set value. On the other hand, using a sensor in a normal state, we create an environment in the laboratory that is the same as or close to that in which the sensor is installed in an actual plant, and calculate the normal response time τ of the sensor. Get it. From this, 6 is τ〉α
・τ. (Here, α is a positive constant), it is determined that the response is slower than the normal state, and 7 indicates a "sensor abnormality".
This system generates alarms and provides appropriate instructions to plant operators.

In the above analysis, it is assumed that the process noise characteristics (process fluctuations input to the sensor) are white. Actual process noise has white characteristics (power spectrum @
Degree means a constant value. In other words, there is no problem if the noise includes all frequencies uniformly), but in reality, there are actually very few processes with white characteristics, and most processes (flow rate, pressure, temperature, etc.) have some kind of color noise characteristic ( (meaning anything that is not a white trait). Therefore, since the response time estimation based on the above analysis includes not only sensor characteristics but also process characteristics, there is a drawback that the response time estimation accuracy deteriorates over time.

The present invention has been proposed in view of the above circumstances, and its purpose is to improve the accuracy of estimating response times of detectors and improve the reliability and safety of nuclear power plants. This company provides a response abnormality diagnosis device.

The detector response abnormality diagnosing device according to the present invention has a sensor transmission characteristic when the sensor is normal and a sensor output noise data when the sensor installed in the blank has a normal response. A means for obtaining only the sensor characteristics excluding the process characteristics from the calculation of the output noise data and the above two data, and a means for estimating the response time from the above sensor characteristics obtained by this means, and a means for estimating the response time and the above-mentioned holding means. and a means for comparing the normal response time with a weighted value, and outputs an abnormal signal when the estimated response time is large, and the color noise characteristic of the process is By performing a process of removing data from the detector output signal for each year of data yield, only the sensor characteristics are obtained, thereby increasing the accuracy of estimating the response time of the sensor.

An embodiment of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 2 is a block diagram showing the configuration of an embodiment of the present invention;
FIG. 3 is a flowchart showing the detailed operation of the arithmetic unit shown in FIG. 2.

In FIG. 2, 11 is a noise magnifier that inputs a sensor output electric signal of 1° and magnifies its minute value, and 12 is an A/D that converts the output of the noise magnifier 11 into A/D and stores it electrically.
The converter 13 is an arithmetic unit that performs necessary calculation processing and judgment, and 14 is an output device that displays the calculation results of the arithmetic unit 13.

In FIG. 3, 15 electrically receives and processes the value of 12, and 16 performs calculations using the result of 15 and 1'7 and 18. At 19, the result of 16 is processed electrically, and at 20, the result is further electrically processed. In No. 2, the result of No. 2o is electrically compared with No. 22, and this is input to the output device 14.

The operation of the above embodiment of the present invention will be explained. The sensor output electrical signal 1o is input to the noise magnifier 111. The noise magnifier 11 removes the steady value and magnifies only the variation. This is converted into a digital value by a converter 12 and stored as noise data. In step 15, the data y(t) is Fourier transformed to obtain Y(jw). Furthermore, Y(
Convert Jw) → Y(!I). 171 stores the normal sensor characteristic Ho(s). 18 is noise data Y in the normal state of the sensor. (s). Let this value be H(s). In 19, H(s) is replaced with H(jw) and inverse Fourier transform is performed to obtain the impulse response h(t).
Walk around. In step 20, h(t) is integrated to obtain the initial response 5(t), and the response time τ of the sensor is obtained from 63.2% of the set value. 22 is the sensor response time τ during normal operation. and weighting coefficient α, and τ and α·τ at 21. Compare. τ
When 〉α・τ0, the value of τ and a warning are outputted from the output device 14, and τ〉α・τ.

If not, only the value of τ is output, the next noise data is input, and the above process is repeated.

Here, H8(s) is the transfer characteristic when the sensor is normal, τ is the response time when the sensor is normal, yo (t) is the noise data when the sensor is normal, and Yo(s) is the Fourier transform of the noise data when the sensor is normal ( jw-+s) and G(s) are process transfer characteristics, the output noise when the sensor is normal is expressed by the following equation.

Yo(s) = Ho(s)・Xo'(S)=Ho(s
)・G(s)・Xo(s)・・・・・・(1) Here
X. '(s): Process noise X input to the sensor. ′
(t) Fourier transform (jw-+5) On the other hand, X(s) is obtained from noise data x(t) at the time of diagnosis of the plant sensor by Fourier transformation thereof. From the Fourier transform of the output y(t), Y(s) expressed by the following equation is obtained.

Y(s) = H(s) ・X'(s) = H(a)
・G(s) ・X(s) --<2) where H(s): Sensor transfer characteristic during diagnosis X'(s): Fourier transform of process noise (jw-+5) Equation (1) and (2) ) From the formula, X here. (s), X because we assumed that X(s) is white noise. /X=C (9 comparisons).

Therefore, from this equation (4), the normal sensor characteristic ■(.(s),!
: Noise data Y during normal printing. (s) is used to obtain the sensor characteristics at the time of diagnosis by removing process color noise from the noise data at the time of diagnosis. Therefore, is it better than H(s)? The expected response time does not include process characteristics and depends purely on sensor characteristics, so it is recommended! Accuracy can be improved.

From the above, the present invention can improve the accuracy of estimating the response time of a detector, thereby providing an excellent effect of providing a detector response abnormality diagnosis device that can improve the reliability and safety of nuclear power plants, etc. It is something to play.

[Brief explanation of drawings]

FIG. 1 is a flowchart for explaining F'l quasi-determination when the sensor responds to a grounder, and FIG. 2 is a block line section I% showing the configuration of an embodiment of the present invention. FIG. 2 is a flow diagram showing detailed operation of the computing unit of FIG. DESCRIPTION OF SYMBOLS 10... Sensor output return air signal, 1, f... Noise expander, 12... A/D converter, 1.9... Arithmetic unit, Z4... Output device. Applicant's sub-agent Patent attorney Takehiko Suzue Figure 1 Figure 2 10 it 12 - (Figure 3 11)

Claims (1)

[Claims] Means for holding sensor transfer characteristics when the sensor is normal and sensor output noise data when the sensor installed in the plant responds normally, and a process from calculating the sensor output noise data and the above two data when diagnosing sensor response abnormality. A means for obtaining only the sensor characteristics excluding the characteristics, and a value obtained by adding the response time from the sensor characteristics obtained by this means and multiplying this by weighting the normal response time held by the holding means. and means for comparing;
A detector response abnormality diagnosing device characterized in that an abnormality signal is output when the estimated response time is long.