JPS6278610A - Plant diagnosing device - Google Patents

Abstract

PURPOSE:To have the proper diagnosis for the plant abnormality where the reference value has the big fluctuation by integrating the deviations of the process signals sent from a plant and deciding the process abnormality from said integrated deviation value. CONSTITUTION:The deviation and its integrated value between the process signal sent from a plant 1 and the reference value registered at a reference value register part 12 are calculated at a deviation integrating part 11. While the prescribed value is registered at a prescribed value register part 13 for decision of the abnormality of the integrated value of deviation. A comparison part 14 compares said prescribed value with the integrated value obtained from the part 13. The result of this comparison is given to an abnormality deciding part 15 for decision of an abnormal state. If an abnormal state is decided, the factor of the abnormality is decided by an abnormality factor deciding part. Thus it is possible to diagnose properly such plant abnormality where the reference value has the big fluctuation.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field of the Invention] The present invention relates to a plant diagnostic device suitable for diagnosing plant abnormalities.

[Technical background of the invention and its problems] In general, in a plant, the process amount is compared with a limit value in order to monitor its condition, and when the process amount deviates from the limit value, an alarm is issued by an annunciator, It is output from output devices such as displays and typers.

In this case, as shown in FIGS. 7(a) and 7(b), the limit value is often a constant value, or even if it is a variable, the amount of change is relatively small.

Incidentally, as shown in FIG. 7(c), among the process quantities, abnormality of the bran 1- may be determined based on the magnitude of the deviation of the current process quantity from the reference value.

In this case, it is necessary to make a judgment based on the size of the overall deviation between the current value of the process quantity and the reference value in a predetermined area a. The method of determining abnormality based on this method had the problem that appropriate plant abnormality diagnosis could not be performed.

[Object of the Invention] An object of the present invention is to provide a plant diagnosis device that can solve the problems of the prior art described in (a) and appropriately determine abnormalities even when the reference value fluctuates to the same extent as the process amount. shall be.

[Summary of the Invention] The present invention integrates deviations of process signals input from a plant, and determines an abnormality in the process signal and its cause based on this integrated deviation signal.

[Embodiments of the Invention] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 shows a configuration diagram of a plant diagnostic device according to an embodiment of the present invention.

In the figure, a process signal from a plant 1 is input to an input processing device 3 of a computer 2. The reference value of the process quantity (signal) is registered in the reference value registration section 12 of the plant diagnostic device 10, and the deviation between the input process signal and the reference value and the integrated value of this deviation are stored in the deviation integration section 11.
It is calculated by

On the other hand, a specified value for determining abnormality in the deviation integrated value is registered in the specified value registration section 13, and the integrated value calculated by the deviation integration section 11 and the specified value are compared by the comparison section 14.

The comparison result by the comparing section 14 is added to the abnormality determining section 15, and it is determined whether or not an abnormal state exists.

When this determination result indicates an abnormal state, the cause is further determined by the abnormality cause determining section 16, and this determination result is input to the arithmetic processing section 4 of the computer 2.

The above-mentioned abnormal condition and cause of the abnormality are notified from the arithmetic processing section 4 to the output processing section 8, and are thereby outputted to the output machines of the typer 7, display 8, and annunciator 9, and are displayed.

Now, in a plant, noise specific to the process amount is superimposed on each process signal.

When the power spectrum of this noise component is analyzed as the signal strength for each frequency band, the power spectrum exhibits approximately constant characteristics under normal conditions.

Figure 2 shows the power spectrum when the neutron flux is normal in the nuclear reactor in the nuclear couplant. According to this power spectrum, the intensity of the noise component has a substantially constant value in the frequency band below IHz, and the intensity of the noise component decreases in the frequency band below that.

That is, when the noise component exhibits such a power spectrum, it can be determined that the states of the reactor fluid, fuel structure, etc. are normal.

Incidentally, the actual power spectrum distribution fluctuates, for example, as shown by the broken line in FIG.

Therefore, the power spectrum distribution under normal conditions is used as the reference value, and
By integrating the deviation between the actually obtained noise power spectrum, that is, the current value, and its reference value,
The current state of the plant can be determined.

In other words, if the integrated value of the deviation is larger than the specified value, the current value exhibits different characteristics (power spectrum) in one of the frequency regions than the reference value, and in this case, the process It can be determined that some abnormality has occurred in the state.

In addition, when the deviation integrated value is small, the current value exhibits characteristics that are almost similar to the reference value, so it can be determined that the process state is normal.

Note that, for example, when the deviation suddenly increases as shown in the part of FIG. 3, if the process state is judged to be abnormal based only on the amount of deviation, an erroneous judgment may be made. In such cases, the frequency of occurrence must also be used as a factor in determining abnormality.

In this embodiment, the above-mentioned deviation integrated value Q is calculated using the following equation (I).

Q=Σ(log(Pi/PBi))2..."(1) Here, Pat is the reference value of the power spectrum, and Pi is the current value of the power spectrum.

Furthermore, if the specified value for determining that a process state is abnormal is ε, then the process state is determined to be abnormal if the following relationship is satisfied: Q>ε...(II). Note that this specified value ε is set empirically depending on the plant.

FIG. 4 shows a process for determining an abnormality in the process state by the method described in -.

First, a process amount (signal) is read from the input processing device 3 (process 101). Next, based on this input process amount, the power spectrum described above is calculated for each frequency band to form a power spectrum distribution (process 10).
2).

Next, determine whether a reference value has already been set (
Judgment 103). If the reference value has been set, the process branches to process 106, but if it has not been set, the operator determines whether or not the power spectrum distribution calculated this time is to be adopted as the reference (determination 104). . Here, the only time the reference value is not set is when the plant is started up for the first time, and if the reference value is registered, the above-mentioned judgment by the operator is unnecessary. Therefore, the result of decision 103 is usually '/ES.

Now, if the result of judgment 103 is No and the result of judgment 104 is No, processing 10 for inputting the process amount
Return to 1. If the result of determination 104 is YES, the power spectrum distribution data calculated this time is registered as a reference value (process 105).

Next, it is determined whether or not the process amount is abnormal based on the formula (IN) (process 106), and the result is output to the output device (process 107).

Next, when it is determined that the current power spectrum distribution is abnormal, a method of performing SK+ to determine which part of the nuclear reactor equipment is abnormal will be described.

Now, among the behaviors inside a nuclear reactor, the causes that induce abnormal phenomena are vibration of the fuel structure and core instability due to an imbalance between the fluid region inside the reactor and the neutron flux.
The power spectral distributions when different types of phenomena occur are different.

FIG. 5(a) shows the power vector distribution in the case of fuel structure vibration, in which a peak is found in the frequency band of 1° OHZ or higher.

Figure (b) shows the power spectrum distribution in the case of core instability, and in this case, from Oll to 1. , OHZ frequency band.

Therefore, the cause of the process state abnormality can be determined using these two characteristics.

In this case, in step 106 in FIG. 4, the formula (II
) to determine abnormalities in the process state from the distribution state of the power spectrum, and then subdivide the frequency band.
The magnitude of Q is determined according to the above equation (1), and its maximum value Qmax is calculated. This maximum value Qmax is 0°1~
If it exists in the 1.0Hz frequency band, it can be determined that the cause of the abnormality is core instability. exists in a frequency band of 1°01)7 or more,
It can be determined that the cause of the abnormality is fuel structure vibration.

FIG. 6 is a flowchart for realizing this cause determination process.7 Note that this figure shows the process after point G in FIG. is the same as in Fig. 4, so it is omitted.

First, the deviation integrated value Q is calculated using the formula (I) (process 110), and it is determined whether the power spectrum distribution is normal or abnormal (process 111).

If the determination result is normal, the result is output (process 115), but if it is abnormal, the process proceeds to a cause determination routine.

In this cause determination routine, first, the power spectrum is measured from 0 to 0.1Hz, O61 to 1.0 [(z and 1.0f
(Divided into three stages of z~, the deviation integrated value Q1 in each frequency band is calculated based on the above formula (I) (process 1.12).

Next, the magnitude of this integrated deviation value is compared and the largest one is selected as 0□8 (113), and this Qoi
The cause of the process abnormality is determined using the above-mentioned determination criteria (processing 114), and the determination result is output (processing 115).

In this way, the cause of the process amount abnormality and the child abnormality can be determined.

J9. In the above embodiment, the integrated deviation value is calculated by comparing the power spectrum distributions, but the data for calculating the integrated deviation value is not limited to this.

Further, the present invention can also be applied to a driving training simulator. In this case, the characteristics of the main process quantities obtained through the model operation by the instructor and the characteristics of the same process quantities obtained when the trainees operated may be compared using the method according to the present invention.

[Effects of the Invention] As explained above, according to the present invention, the integrated deviation value is calculated by comparing the characteristics of the process quantities, and abnormalities in the process are determined based on the calculated value, so that the standard value This makes it possible to appropriately diagnose plant abnormalities that cause large fluctuations.

[Brief explanation of drawings]

Fig. 1 is a block diagram of a device for plant diagnosis according to an embodiment of the present invention, Fig. 2 is a graph showing the power spectrum distribution of process quantities under normal conditions, and Fig. 3 is a diagram showing the relationship between the reference value and the current value. A graph diagram for explaining the relationship, FIG. 4 is a flowchart showing an example of processing, and FIG. 5(a) is a graph diagram showing the power spectrum distribution when an abnormality occurs due to fuel structure vibration. Figure 7 (b) is a graph showing the power spectrum distribution when an abnormality occurs due to core instability; Figure 6 is a flowchart showing another example of processing; Figure 7 (
a). (b) and (C) are graph diagrams showing conventional examples of monitoring aspects of process amounts. 2...Electronic computer, 3...Input processing device, 4...
Arithmetic processing unit, 10... Plant diagnosis device, 11...
- Deviation accumulation section, 12... Reference value registration section, 13... Standard value registration section, 14... Comparison section, 15... Abnormality determination section, 16... Abnormality cause determination section. (7317) Agent Patent Attorney Noriyuki Chika (8
105) Written by Hiroshi Wang Mata Figure 1 (Hz) Figure 2 (Hz) Dictionary 1 People n Figure 4 [Bird (''! 7A If the animal is kinetic 1 (Hz) Figure 5 (a) E In the case of No'do/Shiboshi 1F students 1 (Hz) Figure 5 (b) Figure 7 (a) Figure 7 (b) Figure 7 (c)

Claims (1)

[Claims] A plant diagnosis device that diagnoses plant abnormalities by inputting various process signals of the plant includes a calculation means for performing a predetermined calculation based on the process signals, a calculation value outputted by the calculation means, and a corresponding one of the calculation values. a deviation accumulating means for accumulating the deviation from a reference value; a comparing means for comparing the accumulated deviation value outputted by the deviation accumulating means with a specified value corresponding to the accumulated deviation value; A plant diagnostic device comprising: abnormality determination means for determining an abnormality in the calculated value and its cause.