JPH06241956A - Analyzing system for risk of plant - Google Patents

Abstract

PURPOSE:To shorten the time for risk analysis of a plant by selecting easily a group of alternative proposals for disposing of abnormality and, besides, to facilitate determination of a plan of the plant by determining the order of the alternative proposals having an effect of reduction of a risk in the selected group of the alternative proposals for disposing of abnormality. CONSTITUTION:An inference means 2 for inferring the effect of a state of a plant, a risk assessment means 3 for assessing the effect of the risk from the inference data obtained, a risk control means 4 which determines an abnormality cause classification when assessment data exceed a safety level of the plant and extracts alternative proposal for disposing of abnormality in conformity with this abnormality cause classification, and alternative proposal executing means 2 to 4 which execute inference and risk assessment again for the alternative proposal extracted by the means 4 and output the result of the risk assessment for this alternative proposal when the data on the assessment are below the safety level, are provided. Moreover, a level estimating means 5 which determines the order in the degree of reduction of the risk of this alternative proposal on the basis of the result of the risk assessment obtained by the alternative proposal executing means 2 to 4, is provided.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a plant risk analysis system for performing a risk analysis of a plant associated with a sign of abnormality or failure occurring in equipments, parts or other components constituting various plants. When there are abnormal ripples in the inference and risk-evaluated evaluation data, multiple abnormal action alternatives are extracted based on the abnormal cause classification, and the results of implementation of these abnormal action alternatives are compatible with plant safety. At this time, the present invention relates to a plant risk analysis system for ranking the abnormal action alternatives.

[0002]

2. Description of the Related Art Originally, risk analysis consists of risk evaluations related to plant technical items and risk management related to plant management items, but in the case of conventional plant risk analysis systems, the risk evaluation function is the main function. Has become.

Here, the plant risk evaluation means a risk in a technical item or technical area of a plant by a plant engineer from the plant model structure, physical / chemical characteristics / characteristics, and technical operation aspect of the plant. On the other hand, plant risk management is to determine a plant plan based on the risks in the technical domain while considering the risks in the management domain such as plant production costs, maintenance costs, and human safety. Is.

By the way, in recent risk analysis systems, the system itself has a plant management support function, and the risk evaluation function in the management area is considered as part of the risk evaluation function to perform risk evaluation. There is.

[0005]

Therefore, although the conventional plant risk analysis system evaluates the risk in the technical area and the management area of the plant, the plant manager has the following problems.

That is, when an abnormality or failure occurs in a monitored facility or component in a plant, the plant manager substitutes an abnormal action to reduce the risk based on the risk evaluation value obtained by the conventional risk analysis system. You need to come up with a plan. At this time, the plant manager considers a plurality of alternative measures for abnormal actions that are considered to reduce the risk, selects an alternative measure for abnormal actions that is considered to have the highest risk reduction effect, and selects a plant based on the alternatives. Have decided on a plan.

However, it is extremely difficult to select an abnormal treatment alternative having a true risk reduction effect from the plurality of abnormal treatment alternatives as described above. If the degree of risk reduction effect is ignored, the number of abnormal action alternatives for risk reduction will be huge, and it will take a considerably long calculation time to calculate the risk reduction degree of all of these abnormal action alternatives. It takes. As a result, the delay in the implementation of the alternative measures for abnormal measures due to the lost time of the calculation time may increase the spread of abnormalities and failures in the plant, which eventually makes the plant extremely dangerous.

The present invention has been made in view of the above situation, and selects an alternative having a risk reduction effect from a plurality of abnormal treatment alternatives, thereby significantly shortening the risk analysis time of the plant. The purpose is to provide a risk analysis system.

Another object of the present invention is to perform a plant risk analysis for clarifying the rank of abnormal action alternatives by performing risk ranking for alternatives having a risk reduction effect from a plurality of abnormal action alternative groups. To provide a system.

[0010]

In order to solve the above-mentioned problems, the invention according to claim 1 uses a state influence inference means for inferring the state influence of a plant from the state quantity of the plant, and the state influence reasoning means. Risk assessment means that evaluates risk spread from the inferred inference data, and it is judged whether the assessment data obtained by this risk assessment means exceeds the preset plant safety level, and the safety level is exceeded. If there is, a risk management means for judging the abnormality cause classification of the evaluation data, and extracting an abnormality treatment alternative plan which is stored in a database in advance based on this abnormality cause classification, and an abnormality treatment alternative extracted by this risk management means The inference means and the risk evaluation means are implemented for the plan, and the risk evaluation data of the abnormal action alternative plan is A plant risk analysis system provided with the alternative embodiment means for determining whether or not entered a safe level within the plant.

Next, in the invention corresponding to claim 2, in addition to the constituent features of the invention according to claim 1, the risk evaluation data of the abnormal treatment alternative newly obtained by the alternative implementing means is the safety of the plant. When it is judged that it is within the level,
It is a plant risk analysis system in which level evaluation means for deciding the order of risk reduction degree for the abnormal measure alternatives for which the risk evaluation has been performed is added.

[0012]

Therefore, the invention corresponding to claim 1 takes the above-mentioned means to infer the state spread of the state quantity of the plant and evaluate the risk spread of the inferred data. Thereafter, the risk management means compares the evaluation data with the safety level of the plant, and when the evaluation data exceeds the safety level, the abnormality cause classification of the evaluation data is determined, and the database is preliminarily based on this abnormality cause classification. Extract the alternatives for the abnormal measures that have been implemented.

Then, the inference of state spread and the risk spread evaluation are carried out again for the abnormal action alternatives extracted from the database, and the data of the evaluation result is compared with the safety level of the plant. Since the treatment alternative is output as an appropriate one, the risk analysis time can be shortened, and the abnormal treatment alternative can be easily selected.

Next, in the invention corresponding to claim 2, if the re-evaluated evaluation data of the abnormal action alternatives are within the safety level, the risk is reduced after the level evaluation means receives the abnormal action alternatives. Since the order of the degree is determined and output, the plant manager can select the abnormal action alternative according to the order and determine the plan of the plant.

[0015]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a functional block diagram showing an embodiment of a plant risk analysis system according to the present invention. This system consists of a state quantity input means 1 for taking in the state quantity of the plant from sensors, switches, etc. provided in equipment to be monitored, parts and other components of the plant, and a state quantity a from the state quantity input means 1. Function / performance degradation of monitored equipment, deterioration state, type / part of abnormality / fault,
State spread inference means 2 for inferring the state spread of the plant due to a sign of abnormality / failure, and the function spread / deterioration data b inferred by this state spread inference means 2 from the state / function deterioration / deterioration state of the equipment to be monitored, A risk evaluation means 3 for calculating / evaluating the risk ripple that occurs with the subsequent temporal changes in the types / parts of abnormalities / failures, signs of abnormalities / failures, and the like. Result data c, that is, whether the risk of state spread is within a predetermined safety level threshold, and if it is not within the safety level threshold, the abnormal spread data is extracted. After the cause of the abnormality is classified, a necessary alternative group is read out from the abnormal action alternative group stored in advance and sent to the state influence inference means 2 as an inference initial value to perform the same process again. Risk management means 4 for performing a risk assessment by the risk management means 4 and the state spread data within the safety level threshold value sent from the risk management means 4 are output as they are, and risk reduction is performed for a necessary abnormal action alternative group. And a level evaluation means 5 for determining and outputting the order of degrees.

In the risk management means 4, the branch control means 41 which determines the transmission destination by comparing the state spread risk c from the risk evaluation means 3 with a preset plant safety level threshold value. , An abnormal cause classification judging means 42 for judging the abnormal cause classification of the abnormal state spread based on the state spread risk c by the branch control means 41 when the safety level threshold is exceeded, and the abnormal cause classifications A to E, for example.
An abnormal action alternative group database 43 in which abnormal action alternatives are grouped and stored for each (see FIG. 4),
From this database 43, the abnormality cause classification judging means 4
The abnormal action alternative group f corresponding to the abnormal cause classification e of No. 2 is read out and sent to the state influence reasoning unit 2 and the like.

Therefore, the level evaluation means 5 infers the state spread of the state quantity of the plant based on the abnormality countermeasure alternatives from the input / output means 44, and the risk evaluation means 3 evaluates the risk spread and safety It is judged whether or not it is within the level threshold value, and if it is within the threshold value, the risk of the abnormal treatment alternative group f is ranked according to the risk level of the result data h, and this is ranked. Abnormality treatment alternative group i
Is output. Next, the operation of the system configured as described above will be described according to the flow of FIG.

First, in the state quantity input means 1, the state quantity a necessary for expressing the characteristics of the plant or the state quantity a after converting the state quantity from the plant into an appropriate signal is sent to the state influence inference means 2. Input (S1). In addition, this state quantity a
Is not limited to a quantitative state value, and may be a qualitative state value.

Here, the state influence inference means 2 receives the state quantity a of the plant as an inference initial value, and then the state quantity a.
Infer the plant state ripple due to the deterioration of function / performance, deterioration state, type / part of abnormality / fault, sign of abnormality / fault, etc. of the equipment to be monitored corresponding to (S2). This inference method is determined by the nature of the data processed in the inference process. For example, qualitative inference or quantitative inference is executed depending on whether the data is qualitative value or quantitative value. Any method is possible.

The state influence data b inferred by the state influence inference means 2 as described above is sent to the risk evaluation means 3. This risk evaluation means 3 uses the state spread data b
Calculate and infer the risk ripple that corresponds to. In this risk spread calculation / inference method, for example, a risk function representing a relationship between an input factor corresponding to state spread data input from the inference means 2 in advance in a risk evaluation database (not shown) and the risk spread is defined. A risk function is extracted from the evaluation matrix based on the input factor corresponding to the state ripple data, and is calculated / evaluated (S3).

These series of steps S1, S2, S3 constitute a risk evaluation process P1. Then, the state spread data and the risk spread data obtained by the risk evaluation process P1 are sent to the branch control means 41.

In the branching control means 41, a threshold value corresponding to the safety level of the plant is set in advance, and the state spread data and the risk spread data c obtained in the risk evaluation process P1 and the safe level threshold value are set. Are compared with each other, and it is determined whether or not an abnormal action alternative plan is selected (S4). Here, if the data c is within the threshold of the safety level, it is judged that it is not necessary to select the abnormality countermeasure alternative, and the data c is sent to the level evaluation means 5 as h.

On the other hand, when the data c exceeds the threshold of the safety level, the state spread data and the risk spread data d obtained in the risk evaluation process are classified into abnormal causes in order to select an alternative measure for the abnormal treatment. It is sent to the determination means 42. The abnormality cause classification judging means 42 judges the abnormality cause classification of the abnormal spread inferred by the state spread reasoning means 2 from the data d exceeding the safety level input from the branch control means 41 with reference to FIGS. 3 and 4. Yes (S5). Note that FIG. 3 is a determination flowchart of abnormality cause classification, and FIG. 4 is a diagram showing the existence degree of abnormality causes referred to in the abnormality cause classification determination.

That is, in this abnormality cause classification determination method, the abnormality level threshold value is set in advance, and the branch control means 4 is used.
After determining the data d group of which the condition spread data and the risk spread data sent from 1 are above the abnormal level threshold as abnormal spread data (S11), the abnormality degree of the extracted abnormal spread data is calculated. (S12). Although there are various definitions of the abnormality degree, for example, the degree of deviation of the abnormality spread data from the abnormality level threshold value may be used as the abnormality degree.

When the degree of abnormality is calculated in this manner, the degree of presence of abnormality is extracted with reference to the abnormality cause presence degree table H1 in FIG. 4 (S13). This abnormality cause existence degree table H1
Indicates the abnormality cause existence degree (numerical value) corresponding to the nodes N1 to N6, which mean each component, component, or state quantity measuring point, and each of the abnormality cause classifications AE. This abnormality cause dissimilarity (numerical value) defines the probability of becoming an abnormality cause in the abnormality cause classification for each node.

Therefore, when the abnormality degree is calculated, the abnormality cause classification determining means 42 uses the calculated abnormality degree of the abnormality spread data as a weighting element, and sets the weighting element and the abnormality cause of the node which is the state quantity measuring point. The classification is multiplied by the abnormality cause dependency (S14). This is performed for each node in which each abnormal ripple data occurs. The abnormality cause dependence weighted in this way is added for each abnormality cause classification unit (S1
5) The added value is used as an abnormality cause classification determination value in each abnormality cause classification. Then, of the abnormality cause classification determination values, for example, only the abnormality cause classification e within the top 20% is output as the abnormality cause, and the other determination values are rejected (S16).

Therefore, when the input / output unit 44 receives the abnormal cause classification e of abnormal ripples from the abnormal cause classification determination unit 42 as described above, it is grouped in the abnormal action alternative database 43 in units of the abnormal cause classification e. The abnormal action alternative plan group f is read out (S6) and sent to the state influence inference means 2 as an inference initial value. Therefore, from step S4
By S6, it is possible to narrow down and select the abnormal action alternatives corresponding to the abnormal spread of the plant (process P).
2).

Here, the state influence inference means 2 infers the state influence on the abnormal action alternative plan g received from the input / output means 44. If it is assumed that the result of this inference causes a level reduction of the abnormal state, then Since the risk evaluation unit 3 calculates and evaluates the risk spread due to the reduction in the level of the abnormal state, it is possible to estimate the risk reduction degree by the implementation of the abnormal action alternative plan (process P1). Then, if the level of risk spread evaluated by the processes P2-P1 is within the threshold of the safety level, the distributed control means 41 sends the risk evaluation data h of the relevant abnormal action alternative g to the level evaluation means 5. (S4).

Therefore, the data h input to the level evaluation means 5 is the risk evaluation data obtained as a result of the process P1 inferring the plant state quantity a as the inference initial value, or the abnormal action alternative database 43 abnormal action substitution. Plan f
Is data as a result of inference in the process P1 with the inference initial value as. In the case of the former data, this level evaluation means 5 outputs the data i as it is without any processing or processing, but in the case of the latter data, the risk evaluation of the abnormal action alternative in the data. Based on the values, the abnormal action alternatives are sorted in ascending order of risk level, that is, in the order of high risk reduction degree, and the abnormal action alternatives i sorted in this risk level are output (S7).

Therefore, according to the configuration of the above-described embodiment, the state spread data obtained as a result of inference using the state quantity of the plant is guided to the risk evaluation means 3, and the level of the risk evaluation value obtained here is set. If the plant safety level threshold is exceeded, the abnormality cause classification determination unit 42 obtains the abnormality cause classification, and the abnormalities grouped based on the abnormality cause classification from the abnormal action alternative plan database 43 stored in advance. Since the treatment alternative group is read out, it is possible to narrow down and select the abnormal treatment alternatives to be risk-evaluated, and it is possible to avoid difficulty in selecting the abnormal treatment alternatives. In addition, risk analysis time can be significantly shortened because only a limited number of alternatives for abnormal measures are evaluated for risk.

Further, since the narrowed abnormal action alternatives are classified into the risk ranks, the abnormal action alternatives can be clarified according to the risk reduction level, which greatly contributes to the risk reduction. Next, FIG. 5 is a functional block diagram showing another embodiment of the system of the present invention.

This system is based on the risk evaluation means 3 of FIG.
In place of the above, the risk group evaluation means 6 having a plurality of sub 1 to sub n risk evaluation means 61 to 6n for calculating and evaluating risks for various risk items, and each sub 1 to sub n risk evaluation means 61 to 6n. Result data j1 calculated and evaluated by
Risk management control means 7 for selectively outputting jn is provided.

Here, the risks of sub 1 to sub n are, for example, a risk of capability deterioration, failure risk, environmental pollution risk and other risks related to the technical field, output cost risk, maintenance cost risk, human life risk and other risks related to the management field. Means

Next, the operation of the system of another embodiment as described above will be described with reference to the flow chart of FIG. In addition,
In the figure, steps S1 to S7 have the same processing functions as those in FIG. 2, and therefore, the same reference numerals are given and steps S8 and S9 are added to the newly added processing functions.

That is, in this embodiment, after the state influence inference means 2 infers the state quantity of the plant to obtain the state influence data b (S1, S2), this state influence data b
For each of the sub 1 to sub n risk evaluation means 61 to 6n, the risk is evaluated for each risk item (S8). Then, the result data j1 to jn calculated and evaluated by these sub-risk evaluation means 61 to 6n are sent to the risk management control means 7.

In this risk management control means 7, risk items subject to risk management are set in advance or arbitrarily,
Result data j1 from the sub-risk evaluation means 61 to 6n
Only the result data c1 of the risk items to be risk-managed from jn are sequentially output (S9), and the branch control means 41 is provided.
Send to. Subsequent processing is performed similarly to FIG.

Therefore, according to the configuration of this embodiment, the required risk items can be set in each of the sub 1 to sub n risk evaluation means 61 to 6n, and the risk management control means 7 can manage the risk items to be managed. Only the result data can be evaluated, and moreover, abnormal action alternatives focusing on specific risk items can be selected and risk can be classified. The present invention can be variously modified and implemented without departing from the scope of the invention.

[0039]

As described above, according to the present invention, the following various effects are exhibited.

According to the invention of claim 1, an abnormal action alternative having a risk reducing effect is selected from a plurality of abnormal action alternative groups based on the abnormal spread data among the plant risk evaluation data. Abnormality treatment alternatives can be selected, and the risk analysis time of the plant can be greatly shortened.

Further, according to the invention of claim 2, since the risk ranking is carried out in the order of the abnormal action alternatives having the risk reducing effect from the plurality of abnormal action alternative groups, the plant manager carries out the abnormal action according to the order. Alternatives can be selected to determine plant plans.

[Brief description of drawings]

FIG. 1 is a functional block diagram illustrating an embodiment of a plant risk analysis system according to the present invention.

FIG. 2 is a flowchart illustrating a processing procedure of the plant risk analysis system shown in FIG.

FIG. 3 is an operation explanatory diagram for determining an abnormality cause classification from the abnormal spread data when the risk evaluation data is abnormal spread in FIG. 2;

FIG. 4 is a diagram showing a dependency degree of an abnormality cause that is referred to during determination of the abnormality cause classification of FIG.

FIG. 5 is a functional block diagram for explaining another embodiment of the plant risk analysis system according to the present invention.

FIG. 6 is a flowchart illustrating a processing procedure of the plant risk analysis system shown in FIG.

[Explanation of symbols]

1 ... state input means, 2 ... state influence reasoning means, 3 ... risk evaluation means, 4 ... risk management means, 5 ... level evaluation means,
6 ... Risk group evaluation means, 7 ... Risk management control means, 41
... Branch control means, 42 ... Abnormality cause classification determination means, 43 ...
Abnormality treatment alternative group database.

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁵ Identification code Internal reference number FI technical display location G08B 31/00 A 9377-5G

Claims (2)

[Claims] 1. A state spread inference means for inferring a state spread of a plant from a state quantity of a plant, a risk evaluation means for evaluating a risk spread from inference data inferred by the state spread inference means, and a risk evaluation means It is judged whether the obtained evaluation data exceeds the safety level of a predetermined plant, and when it exceeds the safety level, the abnormality cause classification of the evaluation data is determined, and based on this abnormality cause classification A risk management means for extracting an abnormal treatment alternative stored in a database in advance, the inference means and the risk evaluation means for the abnormal treatment alternative extracted by the risk management means, and the abnormal treatment alternative Alternative risk assessment data to determine whether the risk assessment data of A plant risk analysis system characterized by the above. 2. The invention according to claim 1, wherein when it is determined that the risk evaluation data of the abnormal action alternative obtained by the alternative implementing means is within the safety level of the plant, the risk is evaluated. A plant risk analysis system, further comprising level evaluation means for determining a rank of risk reduction degree for the abnormal action alternative plan.