JPS61264410A - Plant diagnosing device - Google Patents

Abstract

PURPOSE:To deliver the information of high density by a trend display of the important process quantity through a plant diagnosing device after the factor of a fault is identified. CONSTITUTION:A plant diagnosing device supplies the plant data supplied from a plant to a plant fault diagnosing part 2 and displays a message on a CRT display part 14 via a message processor 3 after a plant fault is diagnosed. Here a deciding part 5 for important process quantity is added together with the 1st and 2nd process trend collecting parts 6 and 12, estimation simulating parts 10 and 20 and a CRT display part 15. Thus a physical model is selected and decided together with decision of an operating amount according to the result of the part 2. At the same time, the data on the simulation results obtained from both parts 10 and 20 are collected via the part 5. Then process trend and the result of each simulation result are finally displayed on the part 15.

Description

[Detailed Description of the Invention] [Field of Industrial Application] The present invention relates to a plant diagnostic device that identifies abnormal events in a plant online in real time in order to improve the operational reliability and availability of large-scale plants. It is something.

[Conventional technology]

Once an abnormality occurs in a plant, conventional plant diagnosis equipment immediately adds up the cause of the abnormality and displays it on a cathode ray tube display along with operation guides and predictions of chain events that will occur. It was something to do. In other words, they have not taken even a single step towards countermeasures against abnormal events that should be taken against predicted data.In other words, they have only provided a means of providing operational guidance for phenomena when the above predictions become reality. There wasn't.

[Problem that the invention seeks to solve]

Conventional plant diagnosis devices have functions such as adding together causes of abnormalities, predicting and displaying the causes of abnormalities, operation guides, and events that will occur in a chain reaction. However, it does not have a function to display trends in the important process volume that is most affected by the cause of the abnormality, so it is difficult to quickly understand changes in the process volume after an abnormality or after recovery operations. The problem was that it was difficult to

Further, there was a problem in that it was difficult for the operator to grasp the set meal nature of the operation guide.

This invention was made in order to eliminate the above-mentioned conventional problems, and when an abnormality occurs, it is possible to arbitrarily select several types of set meal characteristics based on the trend of important process quantities in the actual plant and the operation guide. Also, depending on the abnormality,
It is an object of the present invention to provide a plant diagnosis device that selects and determines the optimum physical model that predicts the plant state most quickly and accurately, and displays the trend of the predictive simulation results on a cathode ray tube display device.

[Means for solving problems]

The plant diagnosis device according to the present invention has a function of determining the process quantity most likely to be affected by the occurrence of an abnormality and the process quantity to be monitored during a recovery operation, and collecting trend data of the actual plant process quantity. ,
When an operation guide is displayed after an abnormality occurs, select several quantitative points for the operation and calculate how each abnormality will develop if each operation is performed based on the operation guide. Select and decide on the predictive simulation function to predict or the most suitable physical model to perform the prediction most quickly and accurately according to the abnormality, and use the predictive simulation results to determine the trend of the process amount.
Data is collected and the process quantities of the actual plant, process quantities of simulation results, etc. are displayed on the same graph.

[Effect]

When necessary plant data is input from the plant, the plant diagnostic device of this invention identifies the cause of the abnormality, the abnormal location, the size of the abnormality, etc. in the plant abnormality diagnosis section, and then determines it in the important process quantity determination section. File trend data for processes that have been updated. On the other hand, a physical model is selected/determined and a manipulated variable is determined based on the results of the plant abnormality diagnosis section, and data is collected from the determination section with the simulation results predicted by each predictive simulation section, and finally the above-mentioned The current trend and each simulation result trend are displayed on the same cathode ray tube.

〔Example〕

An embodiment of the present invention will be described below with reference to the drawings. In the figure, 1 is plant data input from the plant, 2
3 is a message processor for displaying a message to the operator after diagnosing a plant abnormality; 4 is a message file; 5 is an important process quantity determination unit that is activated after the plant abnormality diagnosis is successful; 6 and 12 are (
(first and second) process trend collection units; 7 is a parameter file for displaying process trends; 8
, 13 are (first and second) trend data files,
Reference numeral 9 denotes a manipulated variable determination unit which inputs the operation guide information from the plant abnormality diagnosis unit 2 and arbitrarily selects several quantitative types of operation guide; 10.20 determines the plant state in parallel for several types of manipulated variables; a plurality of (first and second) predictive simulation units for predicting fluctuations in the data; 11 is a data file /I/ for executing the predictive simulation;
.

Reference numeral 15 represents a cathode ray tube display unit, and reference numeral 16 represents a selection/determination unit for selecting and determining an optimal physical model that can predict the most quickly and accurately in accordance with the abnormality that has occurred. Further, 17 is a normal plant data file in which normal plant data periodically outputted from the plant abnormality diagnosis section 2 is stored.

Next, the operation will be explained. First, when necessary information such as plant data 1 from an actual plant is input, the plant abnormality diagnosis section 2 identifies the cause of the abnormality, the abnormality location, the size of the abnormality, etc. Determine wax events, etc.

According to this operation, the message processor 3 receives the information from the plant abnormality diagnosis section 2, and sends a message 7i,
A message is output and displayed on the cathode ray tube display section 14 using Q/4. Subsequently, the important process quantity determining unit 5 is activated upon receiving a signal from the plant abnormality diagnosis unit 2 indicating that the cause of the abnormality has been successfully identified, and determines the process quantities affected by the cause of the abnormality and the processes to be monitored during recovery operations. Determine the amount, including priority. The (first) process trend collection unit 6 takes in the data from the plant data 1 regarding the process quantities determined by the important process quantity determination unit 5, and performs process trend collection. Create trend data file 8. It was. The operation amount determination unit 9 takes in the operation guide signal from the plant abnormality diagnosis unit 2 and the current operation amount of the equipment corresponding to the operation guide from the plant data 1, and calculates the operation amount from the current operation amount and the maximum possible operation amount of the equipment. Several types of operations ′jl are determined.

Next, the physical model selection/determination unit 16 takes in the cause of the abnormality, the abnormal location, and the size of the abnormality from the plant abnormality diagnosis unit 2, and based on this information, performs a physical The optimal model is selected and determined by considering the modeling method of the model, the number of node divisions of the model, the number of A/-buses, etc. The normal plant data file 1γ stores and updates the plant data periodically outputted by the abnormality diagnosis section 2, and is constantly updated by comparing it with the previously stored plant data. Stores plant data. Multiple predictive simulation units 1
0.20 receives the cause of the abnormality, the abnormality location, and the size of the abnormality from the plant abnormality diagnosis section 2, and also inputs the optimum model A/ from the physical model selection/determination section 16 and the normal plant data. A plant observation signal is taken in from the 7-eye/L 17, an initial state of the prediction simulation is set and stored, and then a plurality of predictions are made for each operation amount by receiving the operation signal from the operation amount determining section 9. Simulation units 1G and 2 (start up at the same time and simulate how the plant status changes after an abnormality occurs in parallel at high speed.
and quantitatively predict.

The predictive simulation described above is executed using the data file 11. (Second) process trend collection unit 1
2 collects trend data regarding the process amount from the important process amount determination unit 5 using the data file 11 that is the result of the predictive simulation;
A second) trend data file 13 is created. Said (first) trend data file8. The (second) cathode ray tube display section 1 uses the (second) trend file 13 and the parameter file A/7 for trend display.
The process trend and the trend of each simulation result are displayed on the same graph of 5.

〔Effect of the invention〕

As described above, according to the present invention, the diagnostic device is configured so that the trend of one important process quantity can be displayed after the cause of the abnormality is identified. Therefore, the quantitative nature of the operation guide can be easily grasped, and the operator can use it as a man-machine system. This has the effect of outputting highly dense information.

[Brief explanation of drawings]

The figure is a configuration diagram of a plant diagnostic device showing an embodiment of the present invention. In the figure, ゛, 1 is the plant data, 2 is the plant abnormality diagnosis section, 5 is the important process quantity determination section, 6゜12 is the first
．． The second process trend collection section, 10°20, is the first.
2nd prediction simulation section, 9 is a manipulated variable determination section, 1
5 is a cathode ray tube display section, and 16 is a physical model selection/determination section. Patent Applicant Mitsubishi Electric Corporation Agent Patent Attorney 1) Hiroshi Sawa (2 others)

Claims (1)

[Claims] An important process quantity determining unit determines the process quantity that is most affected by the cause of the abnormality in the plant and the process quantity that should be monitored during recovery operations for the cause of the abnormality, and the important process quantity determining unit determines the actual plant process quantity. a process trend collection unit that collects trend data; a manipulated variable determining unit that selects several quantitative aspects of the operation guide when an operation guide is output after an abnormality occurs in the plant; A first prediction simulation part that predicts how the anomaly will develop if the prediction is carried out; and a physics part that selects and determines the optimal physical model to carry out the prediction most quickly and accurately according to the anomaly. a model selection/determination section, a second prediction simulation section that predicts the physical model, a process trend collection section that collects trend data of the process amount based on the results of the second prediction simulation, and the actual plant. and a cathode ray tube display section for displaying trend data of the process trend collection section of the predicted simulation results and trend data of the process trend collection section of the predicted simulation results on the same graph.