JPH06281544A - Plant monitor and diagnostic apparatus and abnormality indication judgment method - Google Patents

Abstract

PURPOSE:To detect abnormality indication of a plant and to alarm the seriousness of the abnormality indication by a method wherein the abnormality indication is discriminated by analyzing the variation of a measured signal, a predetermined signal and an operation signal and fluctuation convietion level toward abnormality is acquired. CONSTITUTION:A CPU 11 periodically executes an interruption operation at a prescribed time interval. At a sampling time, the CPU inputs a plant measured signal, a predetermined signal and an operation signal to store them into an external memory device 16 via a communication interface 15 and obtains a characteristic parameter by computing a prescribed equation. Next, the CPU 11 fetches discrimination information and a fluctuation conviction degree indicating deviation condition corresponding to a combination of two characteristic parameter values from a table in a system memory 12. A deviation fluctuation conviction degree is determined from a deviation fluctuation related characteristic parameter, an output characteristic fluctuation conviction degree from an output characteristic fluctuation feature parameter, and a conviction degree in relation to a output continuous raising/falling from an output raising/ falling continuous degree feature parameter so that an overall abnormal occurrence conviction degree is computed to be indicated on an indication device 14.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a plant monitoring and diagnosing apparatus for monitoring an operating state of a plant within a normal operating range to detect an abnormal sign and a method for judging an abnormal sign.

[0002]

2. Description of the Related Art A plant control device is known which measures a physical property value indicating an operating state of a plant, such as temperature or pressure, and automatically sets a manipulated variable of the plant based on a measurement result and a control command value of the physical property value to be controlled. Has been. In such a plant control device, it has become possible to execute from the measurement result to the diagnosis of the abnormality and the details of the abnormality. Although various proposals have been made for the abnormality detection method used in the plant control device, they have the following common points.
That is, statistical processing is performed on the measurement signal to create a characteristic parameter that represents the operating state of the plant, and when the parameter value is within a predetermined allowable range, it is determined to be normal, and when the parameter value exceeds the allowable range. This is a point to judge as abnormal. Among such abnormality detection methods, those for the purpose of early detection of abnormality are disclosed in, for example, JP-A-4-3.
There is No. 05794. This proposal discloses an abnormality detection method in which the difference between the standard deviation of the command signal and the standard deviation of the measurement signal is calculated, and when the difference exceeds a certain value, it is judged that an abnormality has occurred.

In many plants, a limit check method is adopted in which a measurement signal indicating the state of the plant is input to a plant control device and an abnormality is determined when the measurement signal deviates from a predetermined reference value.

When an abnormality is detected by the plant control device,
It is important to take appropriate measures against the abnormality.
In many plants, especially in chemical plants, an interlock system that automatically shuts down an apparatus or system in which an abnormality is detected is incorporated in order to give the highest priority to safety.

In the case of a large-scale chemical plant, the shutdown of one plant may induce the shutdown of a plurality of plants connected by a pipeline, which requires extremely high reliability and safety. It is required to detect a symptom of an abnormality, detect the cause of the abnormality, and take corrective action before detecting the abnormality when the interlock system operates.

Therefore, the applicant of the present application detects the abnormal sign by determining that the plant state is located in the abnormal sign detection area provided in the normal range while the plant is operating in the normal range by the measurement signal. Then, a plant monitoring / diagnosing device for identifying the kind of contents is proposed on March 24, 1993 prior to the application of the present application.

[0007]

The abnormal sign indicated by the measurement signal, the setting signal and the operation signal may be directed toward an abnormal state, but may disappear. Therefore, if the abnormality of the plant does not actually occur even if the abnormality sign is detected and the alarm is issued, it may be mistaken for a failure of the plant monitoring and diagnosis apparatus. Moreover, the meaning of the alarm is diminished even if the alarm is issued frequently. Therefore, it is preferable for the user if the user can know the importance of the abnormality sign.

Therefore, in view of the above points, an object of the present invention is to provide a plant monitoring and diagnosing device capable of not only detecting an abnormal sign of a plant but also reporting the importance of the abnormal sign to a user and the abnormality thereof. It is to provide a symptom determination method.

[0009]

In order to achieve such an object, the invention of claim 1 inputs the measurement signal indicating the operating state of the plant and the setting signal and operation signal of the plant control device, Abnormal sign that occurs in the normal operating range of the measurement signal, the setting signal, is identified by analysis of changes in the operation signal, based on the identified abnormal sign, the abnormality sign of the abnormal sign is obtained to determine the fluctuation confidence It is characterized by doing.

The invention of claim 2 is characterized in that the fluctuation certainty factor is further displayed.

According to a third aspect of the present invention, input means for inputting a measurement signal indicating an operating state of the plant and a setting signal and an operation signal of the plant control device, and an abnormal sign occurring within the normal operating range of the plant are measured signal. , The setting signal, the identification means for identifying by analyzing the change of the operation signal, and the calculation determination processing means for determining based on the identified abnormality symptom, the degree of certainty that the abnormality symptom changes toward abnormality is obtained. Is characterized by.

[0012]

According to the present invention, when the plant monitoring / diagnosing apparatus detects an abnormal sign by analyzing the change of the measurement signal, the setting signal, and the operation signal, the probability that the abnormal sign is abnormal, that is, the variation certainty factor is acquired, and the signal output or display is performed. The user can be notified in the form of output.

[0013]

Embodiments of the present invention will now be described in detail with reference to the drawings.

Prior to the description of the present invention, the principle of the abnormality sign judging method of this embodiment will be described.

In this embodiment, relative deviation variation, absolute deviation variation, output difference relative variation, output difference absolute variation, output characteristic variation,
Abnormal signs are detected for six characteristics of the power rising / falling continuity.

A) Relative deviation variation characteristic parameter DV. T
RS, absolute deviation variation feature parameter DV. ABS FIG. 2 shows the area provided for the detection of changes in the measurement signal and abnormal signs. In FIG. 2, S indicates a state setting amount of the plant, for example, a control setting level that is a control target of temperature. XH and XL are a first upper limit threshold value and a first lower limit threshold value for detecting abnormal signs, which are fixed threshold values.

VH and VL are a second upper limit threshold value and a second lower limit threshold value for detecting abnormal signs, which are fluctuation threshold values. As is well known, the fluctuation threshold value is obtained by adding / subtracting a fixed value to the average (called a moving average) of measured values from the present time to a fixed period before. YH and YL are an upper limit threshold and a lower limit threshold for abnormality detection. Further, a level YH or higher and a level YH or lower are called an abnormal region, and the level Y
A region between H and XH and a region between levels YL and XL will be referred to as a high level sudden change region. Further, the area between the levels XH and XL will be referred to as a low level sudden change area.

In this embodiment, the measured value is the fluctuation threshold V.
When H and VL are exceeded, it is considered that an abnormal sign of variation in relative deviation with respect to the moving average has occurred. The position determination of whether the position of the measured value at this time is in the low-level sudden change region or in the high-level sudden change region is the next absolute deviation variation feature parameter DV. It is done by ABS.

Characteristic parameter DV. TRS, DV. AB
The formula for calculating S is as follows.

[0020]

[Formula 1] Deviation at time t DV (t) = Measured value at time t PV (t) -Control set value at time t SV (t)

[0021]

[Formula 2] Upper fluctuation threshold value VH (t) at time t = moving average of measured values at time t + constant value

[0022]

## EQU00003 ## Lower fluctuation threshold value VL (t) at time t = moving average value of measured values at time t-constant value Deviation value DV (t) at time point (t) and fluctuation threshold value VH
(T) and VL (t), the relative deviation variation feature parameter DV. TRS is

[0023]

[Equation 4] DV.TRS (t) = If VL (t) ≤ DV (t) ≤ VH (t) NOR (no abnormal sign) If VH (t) <DV (t) UP (low level) If VL (t)> DV (t), it can be obtained from the logical relational expression of DOWN (fluctuation toward falling at low level). As can be seen from (Equation 4), the characteristic parameter DV.TRS is a parameter that indicates that the measured value exceeds the range between the fluctuation thresholds and, if it exceeds, the direction.

DV. When TRS becomes UP or DOWN, it is determined that an abnormal sign has occurred.

Absolute deviation variation feature parameter DV. ABS
Is calculated from the following formula.

[0026]

[Equation 5] DV.ABS (t) = If XH ≥ DV (t) ≥ XL, NOR (no abnormal sign) If XH <DV (t), HIGH (variation at high level) XL> DV ( At the time of t) LOW (falling fluctuation at high level) Here, XH and XL are first threshold values for abnormality sign detection (see FIG. 2). DV. When ABS (t) becomes HIGH or LOW, it indicates that the measured value is located in the high level sudden change region of FIG.

FIG. 1A shows the relationship between the characteristic parameters related to the deviation of the measurement signal and the deviation state of the measured value. By determining what kind of combination the values indicated by the characteristic parameters are in FIG. 1A, it is detected whether the deviation state of the measured values matches the change pattern of normal to high level sudden change. be able to.

Further, the more the measurement signal is located in the high level sudden change region of FIG. 2, the higher the probability that the measurement signal will move to the abnormal region of FIG. Therefore, the probability that the measurement signal shifts to the abnormal region is set in advance by statistical analysis of past plant operation data and the like. This probability is associated with the deviation state as shown in FIG. 1A, and when the variation pattern of the deviation state is determined, the corresponding probability is used as the deviation variation certainty factor.

B) Relative output difference variation characteristic parameter ΔM
V. TRS, absolute output difference variation feature parameter ΔMV. A
BS relative output difference variation characteristic parameter ΔMV. The TRS is a characteristic parameter indicating how much the change amount (or change rate) of the operation signal changes with respect to the average change amount (or average change rate). Characteristic parameter ΔMV. The TRS is calculated as follows (here, for the sake of explanation, the measured value of FIG. 2 is described as an output difference and S is replaced with 0).

[0030]

[Expression 6] Output difference ΔMV (t) at time t = manipulated value MV (t) at time t-manipulated value MV (t-1) at time (t-1)

[0031]

[Equation 7] Upper fluctuation threshold VH (t) at time t = moving average value of output difference at time t + constant value

[0032]

## EQU00008 ## Lower fluctuation limit threshold VL (t) at time t = moving average value of output difference at time t-constant value Output difference .DELTA.MV (t) at time (t) and fluctuation threshold VH
(T) and VL (t), the relative output difference variation characteristic parameter ΔVV. TRS is

[0033]

[Formula 9] ΔMV.TRS (t) = If VL (t) ≤ ΔMV (t) ≤ VH (t) NOR (no abnormal sign) If VH (t) <ΔMV (t) UP (low level) If VL (t)> ΔMV (t), DOWN (variation of manipulated variable toward low level) Absolute output difference variation characteristic parameter ΔMV. The ABS is used for position determination as to whether the fluctuation of the manipulated variable is in the high level sudden change region. Characteristic parameter ΔMV. ABS is determined by the following equation.

[0034]

[Formula 10] ΔMV.ABS (t) = If XH ≧ ΔMV (t) ≧ XL, NOR (no abnormal sign) If XH <ΔMV (t), HIGH (variation of operation amount toward high level rise) When XL> ΔMV (t) LOW (Variation of manipulated variable toward high level drop) Characteristic parameter ΔMV. TRS, ΔMV. FIG. 1B shows the relationship between the output (operation signal) change state related to the measurement signal determined by the combination of the ABS values and the output fluctuation certainty factor (abnormality occurrence probability) toward the abnormal state corresponding to each state. Here, it goes without saying that the output fluctuation certainty factor may act in the direction of suppressing the fluctuation of the measurement signal.

C) Output characteristic variation characteristic parameter ΔPV
C. ABS Here, the output characteristic is a characteristic value (referred to as a process value) indicating a certain process state obtained by calculation (design condition formula or statistical empirical formula) from a measured value different from the measured value at this time, and It means the difference from the measured value. The output characteristic fluctuation state is determined by the following equation.

[0036]

[Equation 11] ΔPVC.ABS = If lower threshold value ≤ output characteristic value ≤ upper threshold value NOR (no abnormal sign) If upper threshold value <output characteristic value HIGH (abnormal sign) If lower limit When the threshold value> the output characteristic value, LOW (there is an abnormality sign) With respect to the value of the output characteristic variation characteristic parameter, the variation certainty that shifts to the abnormality is determined corresponding to the values of NOR, HIGH, and LOW.

D) Output rise / fall continuity feature parameter M
VC. ITS Here, the output increase / decrease continuity means the number of times the operation signal continuously increases or decreases. A characteristic parameter MVC. ITS is determined by the following equation.

[0038]

[Math. 12] MVC.ITS = If lower threshold value ≤ output increase / decrease continuity ≤ upper limit threshold value NOR (no abnormality sign) If upper threshold value <output increase / decrease continuous UP (manipulation amount continuous increase fluctuation) ) If the lower limit threshold value> output increase / decrease continuity DOWN (manipulation amount continuous decrease fluctuation) The characteristic parameter MVC. Also for ITS, the value of the certainty factor with which the state values NOR, UP, and DOWN shift abnormally is determined.

Since the combinations of the above six kinds of fluctuation parameter values are determined corresponding to the respective changes of the measurement signal as shown in FIGS. 2 to 5, by identifying the contents of the combinations, the presence / absence of the abnormality sign and the abnormality The type of symptom content is identified.

Next, a plant control system for detecting and diagnosing an abnormal symptom by using the above-described method for determining the type of abnormal symptom will be described. The circuit configuration of the plant control system is shown in FIG.

In FIG. 6, the plant 30 receives an operation control signal from the plant controller (DCS) 20 and is operated with a predetermined operation amount. State quantities such as temperature and pressure (hereinafter referred to as control quantities) indicating the operating state of the plant 30 are measured by a measuring instrument, and a measurement signal indicating the measurement result is DCS2.
It is output to 0. The DCS 20 variably sets the manipulated variable based on the measurement signal so that the controlled variable fluctuates along a predetermined response characteristic (including a fixed set value). The plant monitoring / diagnosing device 10 operates as an abnormal sign detecting device, an abnormal sign diagnostic device, and an abnormal detecting device in the plant control device.

In the plant monitoring / diagnosing device 10, the following components are connected to a common bus.

Central processing unit (CPU) 11: executes abnormality sign identification processing, abnormality sign diagnosis processing, and abnormality detection processing based on the system program stored in the system memory 12. As will be described later, the CPU 11 operates as the identification means and the calculation determination processing means of the present invention.

System memory 12: A system program that defines the processing procedure executed by the CPU 11 is stored for each processing content. It also temporarily stores work data related to arithmetic processing. A program for determining an abnormal sign according to the present invention, a combination of a variation pattern of measured values and operation values and a value of a characteristic parameter and a certainty factor of variation, and a corresponding cause of an abnormal sign as shown in FIGS. 1A and 1B. And corresponding actions are also stored in the system memory 12.

Keyboard 13: Inputs operation instructions to the CPU 11.

Display device 14: Displays input information from the keyboard and calculation results of the CPU 11 under the control of the CPU 11.

Communication interface (I / F) 15: C
Signals are transferred between the PU 11 and the DCS 20 as an input means of the present invention. From the DCS 20, the control amount measurement signal acquired from the plant 30 and the setting signal and operation signal included in the DCS 20 are received, and a new setting signal or operation signal is transmitted to the DCS 20.

External storage device 16: The measurement signal, the setting signal, the operation signal, and the abnormality sign diagnosis result obtained by the input means are stored in the floppy disk (FD) or the hard disk (HD).

The abnormality sign determination related processing executed in such a circuit configuration will be described with reference to FIG. Figure 7 is C
7 shows a processing procedure of abnormality sign identification processing and abnormality sign diagnosis processing executed by the PU 11. It is stored in the system memory 12 in advance in the form of a programming language. This processing procedure is executed by the CPU 11 by interrupt processing at regular intervals.

At a certain sampling time, the CPU 1
1 inputs the plant measurement signal, the setting signal, and the operation signal via the I / F 15 and stores them in the external storage device 16 (S10). Next, the CPU 11 performs calculations using the equations 1 to 12 to obtain the values of the above-mentioned 6 types of characteristic parameters (S20).

Next, the CPU 11 obtains the identification information indicating the deviation state (that is, the change pattern) and the variation certainty factor corresponding to the combination of the values of the two characteristic parameters from the table in the system memory 12 (S30). Furthermore, the cause of failure corresponding to the identified change pattern is the CPU
It is read from the system memory 12 by 11. Also,
In the present embodiment, the deviation variation-related feature parameter DV. TR
S, DV. The deviation variation certainty factor (see FIG. 1A) is determined from the ABS, and the output variation certainty factor (see FIG. 1B) is determined from the output difference variation related feature parameter. Further, the output characteristic variation characteristic parameter determines the output characteristic variation certainty factor, and the output increase / decrease continuity characteristic parameter determines the certainty factor of continuous output increase / decrease. These certainty factors are substituted into a predetermined arithmetic expression, and the overall abnormality occurrence certainty factor is calculated by the CPU 11.

As described above, the cause of failure and the overall certainty of occurrence of abnormality are displayed on the display screen of the display device 14 in the form of a graphic according to an instruction from the CPU 11. FIG. 8 shows an example of the display.

In the example of FIG. 8, the process equipment controlled by the DCS 20 and its control system are graphically displayed, and the fact that there is an abnormal sign in the automatic flow rate control valve found as the cause of the failure is represented by a graphic P of a specific color. The overall probability of abnormality occurrence is represented by the shade of a specific color.

Thereafter, the CPU 11 executes the above-described processing procedure at regular intervals and repeats the identification of the change state of the measured value.

In addition to this embodiment, the following example can be implemented.

1) In this embodiment, at least one of the six abnormal parameters is UP, DOWN, HIGH, LO.
When any one of the change patterns of W is shown, it is determined that there is an abnormal sign, and only the cause (apparatus or event causing the abnormal sign) is displayed. In addition to this, it is also possible to display, for example, a message as to the determination result of the type content of the abnormal sign. In this case, the message information corresponding to the type of abnormality sign is stored in the system memory 12, and the message information corresponding to the determined abnormality sign is stored in the CPU 1.
It is read by 1 and displayed on the display device 14.

2) The above six types of characteristic parameters may be calculated at different time intervals. Also, desired characteristic parameters may be selected and calculated according to the contents of the plant to be controlled.

3) As a characteristic indicating an abnormal sign, a characteristic conventionally used for judging abnormality can be used, but the important point here is in the change pattern of the measurement signal indicated by the abnormal characteristic. The point is to use the part handled as the normal operating range as the characteristic parameter of the abnormal sign.

4) It is also possible to detect the abnormality sign and the abnormality at the same time.

In this case, the CPU 11 causes the CPU 11 to determine that the abnormality is abnormal when the total abnormality reliability reaches the maximum value (for example, 100%). Further, in the case of abnormal sign detection, the display device 14
By displaying only the alarm and outputting an alarm from the display device 14 and a speaker (not shown) when an abnormality is detected, the user can be surely notified of the abnormality.

5) In the display of the above-mentioned comprehensive abnormality certainty, image display showing the magnitude of the value such as color display, graph display, graphic display, numerical display, etc. can be performed in addition to the color shading display.

6) The higher the above-mentioned comprehensive abnormality certainty factor, the more likely an abnormality is to occur in the plant. Also, for example, FIGS.
There are also types of abnormality signs such that abnormalities are likely to occur rapidly, such as the change pattern of. Therefore, a formula for calculating the degree of urgency associated with the total abnormality certainty factor and the type of abnormality symptom may be set, and the degree of urgency may be calculated by the CPU 11 and displayed on the display device 14 to inform the user. In the case of a plant control device installed in a place where no operator is present, it is possible to further execute plant control according to the comprehensive abnormality certainty factor.

[0063]

As described above, according to the present invention,
Since the abnormality certainty factor is obtained according to the detection of the abnormality symptom, the user can know the degree of importance of the abnormality symptom based on the abnormality certainty factor.

[Brief description of drawings]

FIG. 1 is a diagram showing the contents of a table used for matching change patterns.

FIG. 2 is a waveform diagram showing a waveform of a measurement signal having no abnormal sign according to the embodiment of the present invention.

FIG. 3 is a waveform diagram showing an abnormal sign and an abnormal sign process of an embodiment of the present invention.

FIG. 4 is a waveform diagram showing an abnormal sign and an abnormal sign process of an embodiment of the present invention.

FIG. 5 is a waveform diagram showing an abnormal sign and an abnormal sign process of the embodiment of the present invention.

FIG. 6 is a block diagram showing a system configuration of an embodiment of the present invention.

FIG. 7 is a flowchart showing a processing procedure executed by the CPU 11 of FIG.

FIG. 8 is an explanatory diagram showing an example of a warning display of abnormal signs.

[Explanation of symbols]

 10 Plant Monitoring / Diagnostic Device 11 CPU 12 System Memory 13 Keyboard 14 Display Device 15 I / F 16 External Storage Device 20 DCS 30 Plant

Claims (3)

[Claims] 1. A measurement signal indicating an operating state of a plant and a setting signal and an operation signal of a plant control device are input, and an abnormal sign occurring within a normal operating range of the plant is measured signal, the setting signal, and the operation signal. Of the plant and the plant control apparatus, characterized in that it is identified by analyzing the change of the above, and based on the identified abnormality symptom, the degree of certainty of variation in which the abnormality symptom is abnormal is acquired and determined. 2. The abnormality sign determination method according to claim 1, wherein the variation certainty factor is displayed. 3. Input means for inputting a measurement signal indicating an operating state of a plant and a setting signal and an operation signal of a plant control device; and an abnormal sign occurring within a normal operating range of the plant, wherein the measurement signal, the setting signal, A plant characterized by comprising identification means for identifying by analysis of changes in the operation signal, and operation determination processing means for determining and acquiring a variation certainty factor for the abnormality sign based on the identified abnormality sign. Monitoring and diagnostic equipment.