JPH04249795A - Handling procedure preparing - 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]

[Purpose of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system for preparing measures to be taken when an abnormality occurs in large-scale plants such as nuclear power plants, thermal power plants, and chemical plants.

0002

[Prior art] When an abnormality occurs in a large-scale plant,
Its effects are often observed as transient changes in multiple signals, and if the changes are large, multiple alarms are generated. Plant operators are required to quickly judge the status of the plant from these multiple alarms and take appropriate measures, but when the scale of the abnormality is large or the propagation of transient phenomena is rapid, The burden placed on the operator becomes excessive and may lead to erroneous judgments. For this reason, an alarm processing system is being developed with the aim of assisting operators in determining the situation in the event of an abnormality. As such alarm processing systems, systems have been developed that determine the cause of an abnormality and the latest alarm, and predict future alarms, but these systems do not have a function to display a manual for handling important alarms.

0003

[Problem to be solved by the invention] In this way, conventionally,
Even if the cause alarm is determined by the alarm processing system,
Subsequent response operations may differ depending on the initiating event, so operators must use their knowledge of the structure and design of the plant and their own experiential knowledge to determine whether the results obtained from the alarm processing system are correct based on the course of the subsequent event. After confirming whether or not the error occurred, the cause of the abnormality had to be determined and an appropriate treatment had to be selected, leaving the possibility of misjudgment. In addition, we have also developed a conventional alarm processing system that stores the pre-assumed order of alarm occurrences as a database for each abnormal event, and determines the cause of the abnormality by comparing the sequence of alarms that occur with the database. However, there are problems in that it is difficult to anticipate all possible events and cannot respond when unexpected events occur, and the cost of creating and managing the database is high.

The present invention has been made in view of the above-mentioned problems, and it is an object of the present invention to provide an abnormality treatment creation device that appropriately supports operators in determining the situation when an abnormality occurs in a large-scale plant where alarms occur frequently. The purpose is to [Structure of the invention]

[0005]

[Means for Solving the Problems] In order to achieve the above object, an abnormality treatment creation device according to the present invention converts knowledge regarding treatment in an abnormality in a large-scale plant into knowledge data for ensuring plant safety. and a knowledge database that is divided into knowledge data for maintaining functions necessary for plant operation and summarized for each alarm, a signal input means for inputting plant data obtained from the plant, and a plant input from this signal input means. a condition monitoring means for detecting an abnormality in the plant and creating plant signal data based on the conditions for determining whether an abnormality has occurred in the knowledge database and a predictive warning; and when an abnormality in the plant is detected by the condition monitoring means a diagnostic means that connects plant signal data in a network based on the knowledge database, determines the cause-and-effect relationship of alarms, creates the predictive alarm, and monitors the operation of the alarm sequence; a countermeasure determining means for grasping the condition and determining a countermeasure to ensure the safety of the plant and a procedure to maintain the functions necessary for the operation of the plant, and a result determined by the countermeasure determining means and a result obtained by the diagnostic means. The present invention is characterized by comprising an output means for outputting the result of monitoring the operation of the alarm sequence.

[0006]

[Operation] In the abnormality treatment creation device configured in this way, the knowledge database includes knowledge regarding the treatment in the event of an abnormality in a large-scale plant, knowledge data for ensuring plant safety summarized for each alarm, and knowledge data for ensuring plant safety that is compiled for each alarm. Knowledge data for maintaining the functions necessary for plant operation are summarized for each alarm generation condition, such as the cause and result of the occurrence of the alarm.In the event of an abnormality, signal input can be performed based on this knowledge database. Based on the plant data inputted by the means, the condition monitoring means determines whether or not an abnormality has occurred in the plant based on the knowledge database and predictive warning, detects the abnormality, and creates plant signal data. Upon detection of this abnormality, the diagnostic means connects the plant signal data into a network based on the knowledge database, determines the cause and effect of the alarm, monitors the operation of the alarm sequence, and creates a predictive alarm. Based on the results obtained by this diagnostic means, the response decision means grasps the plant status, determines measures to ensure plant safety, and measures to maintain functions necessary for plant operation, and uses these results. It is output to the operator using the output means.

[0007]

DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 shows a functional configuration diagram of an abnormality treatment device according to an embodiment of the present invention. In FIG. 1, the abnormality treatment device A detects abnormalities in the plant based on a signal input means 2 that inputs process signals such as alarms and on/off status of equipment from the plant 1, a knowledge database 3, and a predictive alarm 4. and once an abnormality in the plant is detected by the condition monitoring means 5, the knowledge database 3 is used to connect the generated alarms in a network to determine the cause and effect relationship of the alarms. Diagnostic means 6 predicts the next alarm to occur, creates a predictive alarm 4, monitors the operation of the alarm sequence, and grasps the plant status from the results obtained by the diagnostic means 6 to ensure plant safety. It is comprised of a corresponding action determining means 7 that determines the action and the action that maintains the functions necessary for plant operation, and an output means 9 that outputs these results to the operator 8. Here, in the knowledge database 3, knowledge regarding measures to be taken in the event of an abnormality in a large-scale plant such as a nuclear power plant is stored as (a
) Items that ensure plant safety (b) Items that maintain the functions necessary for plant operation

For (a), for each alarm, (
Regarding b), we further summarize each alarm generation condition such as the cause and result of the alarm generation, and combine these with knowledge of the alarm name and the conditions for determining abnormality occurrence, and the safety protection that has been installed in the plant in advance. The type of occurrence for each condition, indicating whether it is due to system, plant interlock mechanism, or physical causal relationship, and the magnitude of the effect that activation/non-operation of the alarm sequence will have on the plant due to the conditions. The information is summarized for each alarm along with its importance level, and is registered and saved as a knowledge database.

In this knowledge database, (a) measures to ensure plant safety, and (b) measures to maintain functions necessary for plant operation, follow a series of alarm sequences determined at the time of plant design. It worked (
This includes not only those during normal operation, but also those during abnormal operation. As an example of such measures, regarding (a) to ensure safety, if the pony motor, which is an auxiliary system for the coolant pump, operates normally during a coolant pump trip in a nuclear power plant, This corresponds to confirming that decay heat is removed by the pony motor, and if the pony motor does not operate normally due to a pump stick or the like, it corresponds to confirming that decay heat is removed by natural circulation. In addition, as a measure to maintain the functions necessary for operation (b), when the oil circulation pump of the oil cooling system that supplies lubricating oil to the motor generator that drives the coolant pump trips, the emergency oil pump If the automatic start of the emergency oil pump is successful, this corresponds to monitoring of oil pressure, bearing temperature, etc., and if the automatic start of the emergency oil pump fails, it corresponds to a manual start operation.

[0011] Therefore, for (a), such measures are summarized for each alarm, and for (b), they are summarized for each occurrence condition along with the importance level that indicates the magnitude of the impact that alarm operation/non-operation has on the plant. Then, in the event of a plant abnormality, the knowledge database is used to identify the progress path of the alarm, and take measures to ensure safety against activation/non-operation of the alarm and measures to ensure the functions necessary for operation in parallel. The information shall be provided to the operator.

[0012] Therefore, for the conditions established as described above, if the alarm operates correctly as designed, a normal treatment is provided, and if not, an abnormal treatment is provided.

[0013] In addition, if the above-mentioned measures are the same regardless of the conditions that occur, the same treatment information should be registered for all conditions, or the information should be provided for activation/non-operation of the alarm regardless of the conditions that occur. Create a common area where the information will be used and register it there.

[0014] Here, the specific structure of the knowledge database will be explained using FIG. Figure 2 shows an example of the structure of the knowledge database. The knowledge data 20 registered in the knowledge database is organized for each plant alarm. This knowledge data 20 includes an alarm name 21, attribute data 22,
It mainly consists of occurrence condition data 23. The attribute data 22 stores knowledge of measures to ensure safety regarding abnormality occurrence conditions for alarm generation and plant safety measures for operation or non-operation of a series of alarm sequences determined at the time of plant design. In addition, the occurrence condition data 23 includes data 24 for each occurrence condition that indicates the type of occurrence such as the cause and result of the occurrence, the delay time of alarm occurrence, and the magnitude of the influence that the occurrence of the alarm has on the operation of the plant. Knowledge regarding the degree of importance and plant operation measures to be taken in response to the activation or non-activation of a series of alarm sequences determined at the time of plant design is compiled and stored.

Next, knowledge regarding plant safety measures and operational measures will be explained. Knowledge about safety measures includes ensuring plant safety, such as checking decay heat removal by a pony motor when a coolant pump trips, and checking when isolation valves fail to close automatically due to isolation. such as manual closing operation of
This corresponds to something that must be carried out regardless of the event that occurs.

[0016]Furthermore, knowledge regarding plant operation measures is for maintaining the functions necessary for plant operation.For example, if the condition that caused the "coolant pump trip" alarm was caused by the power source of the pump power source. If the cause is an equipment abnormality or a power outage due to a power abnormality in upstream equipment, it is appropriate to inspect the power equipment mentioned above, and if the power equipment that is the cause of the abnormality has been identified by determining the cause at the alarm level. For example, this corresponds to measures related to investigating the cause, such as inspecting the power line from the power supply equipment to the pump power source. In addition, the emergency oil pump of the oil cooling system, which supplies lubricating oil to the motor generator that drives the coolant pump, can be manually started when automatic startup fails, and the furnace vessel can be used for early restart after a scram. Return to normal conditions such as securing water level/
Measures related to recovery operations also correspond to knowledge regarding measures related to plant operation. A processing method of the abnormality handling device according to the embodiment of the present invention, which is equipped with such a knowledge database, will be described with reference to a processing flowchart shown in FIG.

The abnormality handling device is activated at regular time intervals, and receives plant alarm signals, equipment status signals, and process signals from the plant through the signal input means 2 at a signal input 100.
be done. The condition monitoring means 5 uses input alarm signals, equipment status signals, and process signals to determine whether an abnormality has occurred in the plant or not based on the knowledge of the conditions for determining whether an abnormality has occurred in each signal registered in the knowledge database 3. The presence or absence of a new alarm 130 is checked, and the value of each signal is saved as plant signal data 4 together with the determination result. Furthermore, the occurrence of the predictive alarm 9 predicted by the diagnostic means 6 before the previous diagnostic cycle is checked. This counts down the delay time of the predictive alarm 9, and determines whether or not the alarm will occur after a predetermined time has passed.
Check 10. Here, if the alarm has not occurred as predicted, it is determined that the sequence is abnormal, and sequence abnormality display data to be displayed by the output processing means described later is set.

The diagnostic means 6 is activated when an abnormality is detected in the condition monitoring means 5. Here, based on the knowledge regarding the causes and results of alarm occurrences registered in the knowledge database 3, the progress path of the alarm occurrence in the plant signal data is created in a network form, the alarm progress path is identified 140, and the Determine the causal relationship between As a result, the cause alarm determination 150 is performed with the most upstream alarm on the route as the cause alarm. Next, prediction 150 of the next alarm is performed. This means that when two alarms A1 and A2 occur, the causal relationship between these two alarms is such that, for example, if a "coolant pump trip" occurs as alarm A1, a "reactor scram" as alarm A2 occurs. As shown in the figure, there are two cases in which the occurrence of alarm A1 causes alarm A2 to occur with a 100% probability due to the normal sequence operation of the safety protection system or plant interlock mechanism, and one in which alarm A2 occurs with a 100% probability even if "low coolant flow rate" occurs as alarm A1. There are two types of cases in which there is a physical cause-and-effect relationship, such as ``low/low coolant flow rate'' of alarm A2 does not necessarily occur, and in the former type, after the occurrence of alarm A1, a predetermined Alarm A2 even after the delay time has elapsed
If this does not occur, a sequence error occurs. Therefore,
Register the type of alarm in the knowledge database, including the delay time if it is caused by a sequence operation, and check whether there is an alarm A2 generated by the sequence operation from the newly generated alarm, and if there is, This is determined to be a predictive warning and is registered along with the delay time. As described above, from the next diagnostic cycle onwards, the condition monitoring means 5 checks whether a predictive alarm has occurred after a predetermined period of time has elapsed.

As mentioned above, the knowledge database includes the name of each alarm in the plant, the cause and result of the alarm, and the importance level and abnormality judgment for each occurrence condition indicating the magnitude of the influence that the occurrence of the alarm has on the operation of the plant. Knowledge regarding plant safety measures for conditions, operation or non-operation of a series of alarm sequences determined at the time of plant design, and knowledge regarding plant operation measures are stored.

In the countermeasure determining means 7, the condition monitoring means 5
Based on the sequence abnormality alarm determined in step 170, the alarm progression path identified in the diagnostic means 6, and the determined cause alarm, a corresponding action is determined based on the knowledge database 3, that is, a action to ensure safety is determined 170; A decision 180 is made on measures to maintain the functions necessary for operation. These are dynamically determined from occurrence alarms or sequence abnormality alarms, and those related to plant safety are provided for each alarm, and those related to operation are provided for each established condition. In particular, the latter involves a wide variety of tasks, such as investigation of the cause and return/recovery operations to normal conditions, so we use importance levels for each condition that represent the magnitude of the impact that activation/non-activation of the alarm will have on the plant. and provide treatment for the condition with the highest importance among the identified pathways. The output processing means 8 displays diagnostic results 190 such as countermeasures and cause warnings.
This output process is performed.

[0021] Here, when a "coolant pump trip" alarm occurs in a nuclear power plant, a treatment guide determined by the abnormality treatment preparation device and provided to the operator will be described below.

[0022] When some kind of abnormality occurs in the flow rate control system of the coolant pump, a ``coolant pump rotation speed low'' alarm occurs, and a ``coolant pump trip'' is issued to prevent damage to the coolant pump due to a drop in flow rate. Assume that an alarm also occurs. At this time, since the coolant pump tripped, the decay heat was removed by the pony motor.

[0023] In the abnormality treatment creation device, first, the signal input means receives a "coolant pump rotation speed low" alarm from the plant;
Alarm data for a "coolant pump trip" alarm is input. The condition monitoring means determines whether these alarms are new alarms or predicted alarms, and creates plant signal data. Next, the diagnostic means connects the plant signal data, "coolant pump trip" and "coolant pump rotation speed low" to the network based on the knowledge data in the knowledge database, and determines the cause of the alarm. Furthermore, the response decision means asks the operator to take measures to ensure the safety of the warning "coolant pump trip" registered in the knowledge database, such as confirming the automatic startup of the pony motor and confirming decay heat removal. Provided to.

[0024] Here, if the "refrigerant flow control system abnormality" alarm has occurred and the diagnostic means determines that it is the cause alarm, then the alarm "coolant flow control system abnormality" registered in the knowledge database will be checked. We also provide treatment guides for maintaining the functions necessary for plant operation based on data for each occurrence condition, and investigation of the coolant flow control system.

Furthermore, it is assumed that after the occurrence of the above-mentioned "coolant pump trip" alarm, a "coolant pump rotational speed low/low" alarm is also generated. In this case, the above-mentioned "coolant pump rotation speed low/low" alarm has occurred, and the pump bearing may be stuck, so the pony motor will not remove the decay heat due to the protection mechanism of the pump bearing. . Here, as described above, the condition monitoring means and the diagnosis means perform processing based on the knowledge database, and finally, the countermeasure determining means performs processing based on the knowledge data registered in the knowledge database.
A guide to measures to ensure plant safety, such as confirming the removal of decay heat through natural circulation, and a guide to maintaining functions necessary for plant operation, such as confirming the stoppage of the pony motor based on generation condition data and investigating pump bearings. provided to the operator.

[0026] Therefore, when an abnormality alarm occurs, the response measures are determined based on the knowledge database, and operators are required to take measures to ensure plant safety and maintain functions necessary for plant operation. Since the information is provided to the operator, it can support the operator's countermeasures, make the operator's judgment of the situation more reliable, reduce the possibility of erroneous operation, and even shorten the time spent on recovery. play.

[0027]

[Effects of the Invention] As described above, according to the present invention, it is possible to determine measures to ensure plant safety and maintain functions necessary for plant operation, and to support operators in taking measures. As a result, the operator's judgment of the situation becomes more reliable, the possibility of erroneous operation is reduced, and the time spent on recovery can be shortened.

[Brief explanation of the drawing]

FIG. 1 is a functional configuration diagram of an abnormality procedure creation device according to an embodiment of the present invention.

[Fig. 2] An example of the configuration of the knowledge database of the abnormality treatment creation device according to the embodiment of the present invention.

FIG. 3 is a processing flowchart of the abnormality procedure creation device according to the embodiment of the present invention.

[Explanation of symbols]

1... Knowledge database, 2... Plant, 3
... Signal input means 4 ... Plant signal data, 5 ... Condition monitoring means, 6 ... Diagnosis means 7 ... Prediction alarm, 8 ... Corresponding action determining means, 9
... Output processing means

Claims (1)

[Claims] [Claim 1] Knowledge regarding measures to be taken in the event of an abnormality in a large-scale plant is divided into knowledge data for ensuring plant safety and knowledge data for maintaining functions necessary for plant operation, and summarized for each alarm. A knowledge database, a signal input means for inputting plant data obtained from the plant, and the plant data inputted from the signal input means are used to detect abnormalities in the plant based on conditions for determining the presence or absence of an abnormality in the knowledge database and predictive warnings. a condition monitoring means for detecting and creating plant signal data; and when an abnormality in the plant is detected by the condition monitoring means, the plant signal data is connected in a network based on the knowledge database to determine the causal relationship of the alarm. diagnostic means for creating the predictive alarm and monitoring the operation of the alarm sequence;
A response action determining means that grasps the plant status from the results obtained by this diagnostic means and determines actions to ensure plant safety and maintain functions necessary for plant operation; 1. An abnormality treatment creation device, comprising: an output means for outputting the results of the diagnosis and the results of monitoring the operation of the alarm sequence obtained by the diagnosis means.