JPS61156312A - Abnormality diagnosis system of process - Google Patents

Abstract

PURPOSE:To study early a fundamental factor that produced the operation variance by obtaining a stability coefficient from the measured value of each process variable and displaying these coefficients in the form of a pattern. CONSTITUTION:When either one of process variables reaches an alarm level, a CPU22 produces an alarm. At the same time, the CPU22 calculates the stability coefficients before 1, 2 and 3 minutes from the alarm produced point for each process variable and displays these coefficients in the order of larger absolute value and in the form of a pattern on a CRT display device 25. Further, a fault state of each instrument is displayed on a CRT display device 25. Then the CPU22 calculates the stability coefficient of each process variable every time the countermeasure enable time, e.g., 1min elapses, and absolute value of the stability coefficient is displayed in the display device 25 as pattern in order from large value at each point of time.

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Application Field] The present invention relates to a process abnormality diagnosis system, and can be used for early investigation of the cause of abnormality during plant operation.

[Background Art and its Problems] In recent years, plant operations have become more and more sophisticated, and in response to demands for rationalization and labor savings, fewer people are required to operate the plants. For this reason, plant operation is also monitored.

From operation monitoring based on panel display to computer CR
There is a shift to driving monitoring centered on the T console.

However, with conventional CRT displays, alarms are only displayed individually when each process variable measurement value exceeds a preset upper or lower alarm level, or before it exceeds a preset upper or lower alarm level. The drawback was that it took time to find out what the root cause was.

For example, if there are two or more alarms displayed at the same time, or even one alarm, the process variable for which the alarm was triggered is not the root cause, but the alarm is triggered in relation to operating fluctuations in other process variables. When a driver wakes up, simply looking at the warning display on the CRT display often takes time and effort to determine the root cause of the driving fluctuation.

[Object of the Invention] The object of the present invention was to eliminate such conventional drawbacks, and to provide a plant abnormality diagnosis system that can quickly investigate the root cause of operational fluctuations. There is a particular thing.

[Means and actions for solving problems] Therefore 1
In the present invention, stability coefficients are obtained from the measured values of each process variable, and by displaying these in a pattern,
This makes it possible to quickly investigate the root cause of operational fluctuations.

Specifically, it is an abnormality diagnosis system for detecting abnormalities in a process that includes multiple types of process variables, which measures each of the process variables at a predetermined sampling period, and determines the current process from each of these measured values. In addition to finding the rate of change of the variable, find the level difference between each measured value and the limit warning level, divide each level difference by an arbitrarily set response time, and calculate the predicted average rate of change after that time has elapsed. The method is characterized in that stability coefficients are obtained by dividing the current process variable change rate obtained from each of the measured values by the predicted average change rate, and these stability coefficients are displayed in a pattern.

[Example] Hereinafter, an example in which the present invention is applied to a distillation plant will be described with reference to the drawings.

Figure 1 shows the distillation system flow. In the same figure, the raw material stored in the receiver tank of the front thread passes through a flow rate regulating valve 2 controlled by a flow rate detector 1 to a distillation column 3.
supplied to

A part of the product extracted from the top of the distillation column 3 is transferred to the heat exchanger 4.
The signal is sent to the receiver tank 5 via . The remainder is extracted through a flow rate regulating valve 8 whose opening is adjusted by a top pressure detector 6 and a flow rate detector 7 provided in the middle of the line from the top of the distillation column 3 to the heat exchanger 4. . When a predetermined amount or more of product is stored in the receiver tank 5, the product in the receiver tank 5 passes through the distillation column through a flow rate regulating valve 11 whose opening is adjusted by a liquid level detector 9 and a reflux flow rate detector 10. Reflux to the top of 3.

Note that the temperature at the top of the distillation column 3 is detected by a temperature detector 12.

A repoiler 13 is connected to the bottom of the distillation column 3, and a bottom liquid extraction line 14 is also connected thereto. On the primary side of the repoiler 13, a flow rate detector 15 and a repoiler steam regulating valve 17 whose opening degree is adjusted by the flow rate detector 15 and a bottom temperature detector 16 for detecting the bottom temperature of the distillation column 3 are provided. It has been inserted. Further, in the middle of the bottom liquid extraction line 14, the opening is adjusted by a flow rate detector 18 and a liquid level detector 19 that detects the flow rate detector 18 and the bottom liquid level of the distillation column 3. A flow rate regulating valve 20 is inserted respectively.

FIG. 2 shows an abnormality diagnosis device for the distillation system. In the figure, each of the detectors 1, 6, 7°9, 10, 12,
The signals detected at 15, 16, 18, and 19 are each converted into a digital signal by an A/D converter 21 at a predetermined sampling period, and then taken into a central processing unit (hereinafter referred to as CPU) 22. It will be done. Here, the feed flow rate data (A) detected by the flow rate detector 1, the tower top pressure data (B) detected by the pressure detector 6, and the top extraction flow rate detected by the flow rate detector 7 are shown. data (C), receiver level data (D) detected by the liquid level detector 9, reflux flow rate data detected by the flow rate detector IO (
E), tower top temperature data (F) detected by the temperature detector 12, reboiler steam flow rate data (G) detected by the flow rate detector 15, bottom temperature data detected by the temperature detector 16 ( H), the bottom level data (I) 8 detected by the flow rate detector 18 and the bottom level data (J) detected by the liquid level detector 19 are now taken into the CPU 22 as process variables. ing.

The CPU 22 includes a keyboard 23 for inputting various constants, etc., and a storage device 24 for storing various constants input from the keyboard 23, measurement data, calculation data, etc.
and a CRT display device 25 are connected. here,
The storage device 24 stores the upper and lower alarm levels H and L of the measured value set for each process variable, the permissible rate of change ΔPV of the measured value set for each process variable, and the permissible upper and lower limits of the manipulated output. MW, ML, allowable rate of change of manipulated output ΔMY, allowable range of each detector, and sample time Δ
t, the response time t determined for each process variable in the event of an abnormality, taking into consideration the arrival time of the operator to the operation pan & measurement end and the operation end, and the operation time required for emergency measures.
0, etc. are stored respectively.

The CPU 22 stores various constants given from the keyboard 23 in the storage device 24, and takes in measured values from the detector given from the A/D converter every predetermined sampling period, so that each of the measured values is It is determined whether the upper limit or lower limit alarm level H or L has been reached. Here, if any process variable reaches the upper or lower limit alarm level H or L, an alarm is issued and at the same time the stability coefficient for each process variable is calculated 1.2.3 minutes before the time of the alarm. After calculating the stability coefficients, the stability coefficients are displayed in a pattern on the CRT display device 25 in descending order of absolute value at each time point. Furthermore, the failure status of each instrumentation device is CR
It is displayed on the T display device 25. Thereafter, the stability coefficients for each process variable are calculated every time 1, for example, 1 minute passes, and the stability coefficients are displayed on a CRT display screen in descending order of absolute value at each time point. 2
5. Display the pattern.

Calculation of the stability coefficient is performed in a first-order procedure. Now, as shown in Fig. 3, if the captured measured value is PVn, find the difference between the measured value PV (n - 1) and the measured value PVn from one sample before, and the difference ΔPVn = (PV
n − PV < n −+ )) divided by the sample time Δt to obtain the process variable change rate ΔP at the current time, that is, at the time of measurement.
Find Vn/Δt.

In addition, it is determined whether this process variable change rate is in the positive direction or in the negative direction. For example, if it is in the positive direction, the upper limit alarm is set in advance in consideration of the limit value of the process variable that may cause a problem in plant operation, the operation rate, etc. The level difference between the level H (in the case of a negative direction, the lower limit alarm level L) and the measured value PVn is determined, and this level difference (H-PVn) is calculated for the possible response time t.
Divide by 0 to obtain the predicted average rate of change (H-PVn)/l after the elapse of that time t0.

Here, the stability coefficients are obtained by dividing the process variable change rate ΔPVn/Δt by the predicted average change rate (H-PVn)/t. Now, if the upper limit alarm level side of this stability coefficient is α and the lower limit alarm level side is β, then α
Or, when β is 0, the plant is in the most stable operating state, α→+1.

This shows that the plant becomes unstable as it approaches β→-1 and is gradually approaching its limit.

The stability coefficients of each process variable determined in this manner are displayed as a bar graph on the CR7 display device 25 in descending order of absolute value at each time point.

FIG. 4 shows the screen configuration of the CR7 display device 25. As shown in FIG. On the same screen, there are three cause diagnosis display sections 31+ in the upper row that display events occurring before the alarm is issued over time.
, 312, 313, and each display section 31+ is displayed in the middle row.
, 312 and 313, three failure display units 32+ and 322 display the failure status of the instrumentation equipment within that time.
．． 323, and three treatment confirmation display sections 33+, 332.332.323 and 332.332.
333 are provided respectively.

In each of the cause diagnosis display sections 31+, 312, and 313, the stability coefficients of each process variable at each time point before the alarm issuance, calculated by the CPU 22, are displayed in the form of a bar graph in descending order of absolute value. . Here, display section 3
1+ displays an event 1 minute before the alarm is issued, a display section 312 displays an event 2 minutes before the alarm, and a display section 313 displays an event 3 minutes before the alarm.゛In addition, the failure display sections 32+, 322 and 323 have the following information:
For example, ■ A measured value change rate limit alarm that warns that the rate of change of each process variable measured value has reached the permissible change rate ΔPv of the measured value; ■ The manipulated output has reached the permissible upper and lower limits MH and ML of the manipulated output. Manipulated output upper/lower limit alarm that warns that the manipulated output upper and lower limit alarm has been reached, ■ The rate of change of the manipulated output is the allowable change rate ΔM of the manipulated output.
A manipulated output change rate alarm that warns that Y has been reached, a detector error alarm that warns that the output from the detector exceeds the allowable range of the detector, and a CPU error are provided. ing.

In addition, each treatment confirmation display section 33+, 332333
, the stability coefficients of each process variable at each point in time after the alarm is issued, calculated by the CPυ 22, are displayed in the form of a bar graph in descending order of absolute value. Here, the 1 display section 33+ displays the event 1 minute after the alarm is issued, the display section 332 displays the event 2 minutes after the alarm is issued, and the display section 333 displays the event 3 minutes after the alarm is issued. be done. In this case, the contents displayed on each display section 33+, 332, 333 are 1
The frame is advanced to the display section on the right side of the figure every minute.

In such a configuration, if an alarm regarding any of the process variables is now issued, 3.2. At the same time, the stability coefficients from i minutes ago are displayed in a pattern on the cause diagnosis display sections 311 to 313, and at the same time, the failure information at each point in time is displayed on the failure display sections 32+ to 313.
323.

For example, when an upper limit alarm for tower top pressure (B) is issued, the stability coefficient 3.2.1 minutes before the alarm is raised to 5th.
If a pattern is displayed as shown in FIG. 5(A) and failure information is displayed at the same time as shown in FIG. 5(B), the operator can diagnose the cause of the abnormality from this information.

First, by looking at the three display sections 31+, 312, and 313, it is possible to clearly determine the change over time in the stability coefficient, so it is possible to determine what caused the alarm. In this case, in the illustrated example, the top extraction flow rate (C) is displayed as the first alarm two minutes before the upper limit alarm for the tower top pressure (B) is triggered, so this is the root cause. It can be estimated that Generally, in the initial state of operational fluctuations, one or two alarms are issued, and it is rare that three or more alarms are issued at the same time. As the driving fluctuations progress further, the related alarms will gradually increase. Therefore, in diagnosing abnormalities in movement fluctuations, it is extremely important to know what the first alarm is.

In addition, if failure alarms are simultaneously issued on the display sections 32+ and 322.32a.

It becomes extremely easy to investigate the cause using the display units 31+ to 313, and it is useful for narrowing down the root cause.

In the illustrated example, the operation output has reached the upper limit.

Since the top extraction flow rate (C) is decreasing, the following is considered to be the root cause.

■Stuck in the top extraction valve■Clogged in the top extraction line■Pressure rise at the extraction destinationTherefore, we will check the cause of ■～■ at the site and take corrective action.Then, every minute after the corrective action has elapsed, The fluctuation of the process variable is displayed on the display section 33. 333, so the operator can check the process status after the corrective operation.

Therefore, according to this embodiment, the stability coefficient is calculated from the measured values of each process variable measured at each predetermined sampling period, and the
．． 2. Since the stability coefficients from one minute ago are displayed in a pattern in descending order of absolute value, it is possible to determine what caused the alarm by looking at them. Therefore, the cause of the operational fluctuation can be quickly investigated, and appropriate measures can be taken quickly and appropriately when the operational fluctuation occurs.

Furthermore, since failures of instrumentation equipment are displayed together with these stability coefficients, causes can be easily determined based on the stability coefficients, and the root cause can be narrowed down.

In addition, the stability coefficient after the correction operation is displayed, so that the status of the process after the correction operation can be confirmed.

Furthermore, since the stability coefficients are displayed in the form of a bar graph in descending order of absolute value, the root cause of the driving fluctuation can be identified at a glance.

In addition, in addition to the bar graph described in the above example, polygon graphs (radar charts), polar coordinate graphs, pie graphs, and
In the above embodiment, the condition that the measured value of the process variable reaches the preset upper and lower alarm levels H and L is set in advance. The stability coefficient for each process variable is now calculated and the stability coefficient pattern is displayed.
These calculations and pattern displays may be determined based on other factors, or may be performed at regular intervals. These include the allowable upper and lower limits, the allowable rate of change of the manipulated output, the allowable range of the detector, etc.

In addition, although the above embodiment describes the case of detecting the cause of an abnormality in a distillation column, the present invention is not limited to this, but can be applied to a general system for investigating the cause of an abnormality in a process including a plurality of process variables. can do.

[Effects of the Invention] As described above, according to the present invention, it is possible to provide a plant abnormality diagnosis system that can quickly investigate the root cause of operational fluctuations.

[Brief explanation of drawings]

The figures show one embodiment of the present invention; Fig. 1 is a system diagram showing a general distillation plant, Fig. 2 is a block diagram showing an abnormality diagnosis device, and Fig. 3 is a predicted state diagram of measured values of process variables. 4 is a screen configuration diagram of a CRT display device, and FIG. 5 is an enlarged view of a diagnostic display section and a failure display section. H, L...Upper and lower alarm levels, PV, PVn. PV <n −1)...Process variable measurement value, Δt・
...sample interval, to...predetermined time, a, β...
- Stability coefficient.

Claims (6)

[Claims] (1) An abnormality diagnosis system for detecting abnormalities in a process that includes multiple types of process variables, which measures each of the process variables at a predetermined sampling period, and calculates the current rate of change of the process variable from each of these measured values. At the same time, the level difference between each measured value and the limit warning level is determined, and each level difference is divided by an arbitrarily set response time to determine the predicted average rate of change after the elapse of that time. A process abnormality diagnosis system, characterized in that stability coefficients are obtained by dividing the current process variable change rate obtained from each measurement value by the predicted average change rate, and these stability coefficients are displayed in a pattern. (2) In claim 1, when any of the process variable measurement values reaches a limit alarm level, stability coefficients for all process variables are determined, and then these stability coefficients are displayed in a pattern. A process abnormality diagnosis system characterized by: (3) A process according to claim 1 or 2, characterized in that when displaying the stability coefficient, a history of past stability coefficients and a current stability coefficient are both displayed in a pattern. abnormality diagnosis system. (4) A process abnormality diagnosis system according to any one of claims 1 to 3, characterized in that the stability coefficient and the failure state of the instrumentation equipment are displayed on the same screen. (5) A process abnormality diagnosis system according to any one of claims 1 to 4, characterized in that the pattern display is in the form of a bar graph. (6) A process abnormality diagnosis system according to claim 5, characterized in that the stability coefficients are displayed in descending order of absolute value.