Automatic generating method for FTA real-time dynamic tree based on fault knowledge base

Abstract

To automatically generate an FTA real-time dynamic tree based on a fault knowledge base.SOLUTION: In step 1, an FTA logic model is newly constructed by a method for generating an FTA real-time dynamic tree based on a fault knowledge base. In step 2, a fault knowledge base model is selected based on a logical device. In step 3, a fault library is constructed based on the FTA logic model to generate a logic rule for an FTA model, and the fault knowledge base model is processed to perform decomposition-mapping into an FTA logic fault tree model. In step 4, the fault diagnosis tool for the event node is set. In step 5, a formation of an FTA logic fault tree is completed. In step 6, the FTA logic model is published, and the FTA logic model is instantiated. In step 7, a scheduling task is configured. In step 8, the configured scheduling task performs a periodic fault diagnosis and issues a fault alarm.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention belongs to the field of industrial Internet platform, and particularly relates to a method for automatically generating FTA real-time dynamic tree based on fault knowledge base. [Background technology]

[0002] With the improvement of the safe and stable operation, standardization, standardization and precise management level of power grids and power plants, the demand for intelligent and advanced fault diagnosis methods for electromechanical devices in power plants is becoming more and more urgent. Gradually, the fault tree (FTA) model is introduced to perform the diagnosis analysis of the cause of device failure in the reverse direction, which has an intelligent and advanced logical reasoning mechanism and high diagnostic accuracy. However, in this process, the creation of FTA fault tree still needs to be done by humans, and a complete fault tree model can only be obtained after five steps, such as professional personnel who are familiar with the system and process flow investigate the accident, determine the top event, determine the target value, investigate the cause event and create the fault tree. Secondly, the traditional FTA fault tree model requires the creation personnel to determine the probability of occurrence of all basic events in advance, otherwise quantitative analysis cannot be performed, and thus the FTA fault tree is limited to static fault analysis.

[0003] Through analysis of existing technologies, the following shortcomings were identified: 1. FTA's ability to analyze the causes of accidents is a strength, but to quantitatively analyze a system, the probability of all basic events occurring must be determined in advance, otherwise quantitative analysis cannot be performed. 2. The analyst must be familiar with the system being analyzed and be able to apply the analysis method accurately and skillfully. It is common for the fault tree created by different analysts to differ from the analysis results. 3. For complex systems, analysts must go through many steps to create a fault tree. The created fault tree is often huge and the calculations are complex, making it difficult to perform qualitative and quantitative analysis. Summary of the Invention

[0004] In view of the technical problems existing in the background art, the method of automatically generating FTA real-time dynamic tree based on fault knowledge base provided by the present invention reduces the requirements for fault tree construction personnel, reduces the construction workload, and shortens time costs.By binding fault node devices and setting event node fault diagnosis tools, realizing real-time dynamic fault diagnosis analysis.

[0005] In order to solve the above technical problems, the present invention adopts and realizes the following technical solutions. A method for automatically generating an FTA real-time dynamic tree based on a fault knowledge base, comprising: Step 1: constructing a new FTA logic model by generating an FTA real-time dynamic tree based on a fault knowledge base; Step 2 of selecting a fault knowledge base model based on a logical device; Step 3: building a fault library based on the FTA logic model to generate logic rules for the FTA model, and decomposing and mapping the fault knowledge base model into an FTA logic fault tree model; Step 4: Setting up the fault diagnosis tool for the event node; Step 5 to complete the creation of the FTA logical fault tree; Step 6 of publishing the FTA logic model and instantiating the FTA logic model; Step 7: Configuring the Scheduling Task; and step 8 of periodically performing fault diagnosis and issuing a fault alarm according to the configured scheduling task.

[0006] Preferably, in step 1, the purpose of generating an FTA real-time dynamic tree based on a fault knowledge base is to eliminate the analysis process of manually identifying top events, intermediate events, basic events and event-related logic gates, and the process of stepwise drawing the fault tree by dragging on a drawing board.

[0007] Preferably, in step 2, the logical device is an abstract description of a classification of instantiated devices. For example, a water-conducting bearing is a logical device, and a water-conducting bearing of a unit of a power plant is an instantiated physical device. The sub-steps of step 2 are as follows: In step 2.1, we filter the failure modes based on the logical device and select the failure mode that the current node matches. In step 2.2, the entire failure mode tree is mapped and transformed into the FTA fault tree logic model.

[0008] Preferably, in step 3, the fault library generates a logic rule of the FTA model based on the fault knowledge base model selected in step 2, by mapping the top node to a top event of the FTA fault tree, the middle node to an middle event node of the FTA fault tree, and the end node to a basic event node of the FTA fault tree, where the top node, the middle node and the end node are branch nodes in the FTA fault tree.

[0009] Preferably, when mapping to nodes, the associations of each hierarchical node are synchronously mapped, where each hierarchical node includes a top node, an intermediate node and an end node.

[0010] Preferably, in step 4, the fault diagnosis tool includes measurement points, diagnosis rules, algorithm models and scripts.

[0011] The principle of diagnosing the measurement points is to select the measurement points of the detection devices under the logical devices related to the node, and diagnose the occurrence probability and the fault occurrence status of the node based on the data of the measurement points.

[0012] The diagnostic principle of the diagnostic rule is to call the rule engine based on the business rules related to the logical devices of the node to diagnose the occurrence probability and the fault occurrence status of the node.

[0013] The diagnosis principle of the algorithm model is to call the algorithm engine to diagnose the occurrence probability and fault occurrence status of the node based on the hydroelectric power generation dedicated algorithm associated with the node's logical device.

[0014] The diagnosis principle of the script is as follows: Based on the relevant cases in the fault case library related to the logical device of the node, the case library diagnosis algorithm is invoked to diagnose the occurrence probability and fault occurrence situation of the node.

[0015] Preferably, in step 4, the purpose of setting the fault diagnosis tool of the node of the fault tree is to perform dynamic analysis using the fault tree. The dynamic analysis includes several situations as follows: 1) For the measurement points of the detection device of the logical device, the probability of failure occurrence is predicted by a diagnostic tool at the measurement point. 2) A rule diagnosis engine is called for the business rules of the logical device to predict the probability of failure. 3) If the amount of data at the device's measurement points is greater than a preset threshold, an algorithm engine associated with the logical device is invoked to predict the node's failure probability.

[0016] Preferably, the sub-steps of step 6 are as follows: In step 6.1, we first publish the logic model and activate the newly created FTA fault tree logic model. In step 6.2, the next step is to instantiate, and the plant and instantiation device tree corresponding to the model to be instantiated are selected, and the model instantiation process is entered. In the instantiation process, the logical devices bound to the nodes of the FTA fault tree logical model are converted to physical devices in the instantiation device tree of the plant, and the logical fault diagnosis tools bound to the nodes are converted to instantiation tools.

[0017] Preferably, the sub-steps of step 7 are as follows: In step 7.1, a timing task is created to periodically call the instantiated model for fault diagnosis. Step 7.2 is the diagnosis process, in which if a diagnosis tool is set for an event node, the diagnosis tools set for the nodes are called in sequence to obtain the alarm status and occurrence probability of the node, and the occurrence probability is substituted into the fault tree model. If a diagnosis tool is not set for an intermediate node, the occurrence probability of the node is estimated by the fault diagnosis method until the alarm status and occurrence probability of the top event are finally estimated.

[0018] Preferably, in step 8, a periodic fault diagnosis is performed on the scheduling tasks created in step 7 to generate a complete FTA fault tree, which identifies the fault conditions and occurrence probability of each event node.

[0019] The present invention can achieve the following beneficial effects: In the conventional FTA fault tree diagnosis, the occurrence probability of basic events is derived only by the experience of the fault tree creator, the static occurrence probability of the fault tree basic events is manually set, and then the occurrence probability of the top event is manually derived by performing the fault tree diagnosis. The method of the present invention can obtain the real-time data of the monitoring measurement point of the current device by binding the device and the fault diagnosis tool with the node event of the fault tree, and dynamically calculate and set the probability of the FTA fault tree event node according to the actual situation by adopting different fault diagnosis tools, and realizes that the FTA fault tree diagnosis is performed periodically in real time by the task configuration method, and one FTA fault instance (diagnosis result) is generated each time. [Brief description of the drawings]

[0020] The present invention will now be further described with reference to the accompanying drawings and examples. [Figure 1] 1 is a method flow of the present invention for automatically generating an FTA real-time dynamic tree based on a fault knowledge base and performing fault detection. [Diagram 2] FIG. 2 is a knowledge base model diagram of shaft system operation failure of a hydroelectric generating unit according to the present invention. [Diagram 3] FIG. 2 is a fault tree diagram of a hydroelectric generating unit shaft system operation fault FAT of the present invention. [Figure 4] FIG. 2 is a model diagram of a generator fault knowledge base of the present invention. [Diagram 5] FIG. 2 is a fault tree diagram of a generator fault FAT of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] The conventional fault tree drawing steps will be described using a conventional fault tree drawing tool (FreeFta) currently in common use as an example.

[0022] In step 1, the top event and logic gate are identified based on the results of accident investigation and statistical analysis, referring to the frequency of accident occurrence and the severity of accident losses. Drag the top event from the toolbar to the canvas, set the top event number (note that the top event number is T) and name. This step is performed by the computer.

[0023] In step 2, intermediate process events are created sequentially as intermediate event fault tree nodes according to the analyzed event causes. Click the top event to add intermediate events and logic gates, and set the intermediate event number (the intermediate event number is the first part of M + a number) and name. This step is performed by a computer.

[0024] In step 3, the basic event that causes the intermediate accident is located in the basic event node of the fault tree. Click the intermediate event node to add a basic event, and set the basic event number (basic event number is the first part of X + a number), name, and occurrence probability (occurrence probability is 0 to 1, including 0 and 1). This step is performed by a computer.

[0025] In step 4, the fault tree is checked to see if it complies with the principles of logic analysis, the connections of logic gates are checked, whether the upper-layer events are the necessary results of the lower-layer events, whether the lower-layer events are sufficient cause events of the upper-layer events, and whether all the direct cause events are present. This step is performed by a computer.

[0026] In step 5, the complete static tree is saved after checking for errors, and the fault tree drawing is now complete. This step is performed by the computer.

[0027] According to the above steps, the analyst must be familiar with the system to be analyzed and apply the analysis method accurately and skillfully. For a complex system, the operation procedures are complicated and the amount of calculation is large, which brings great difficulties to a certain extent in qualitative and quantitative analysis. To solve this problem, the present invention generates an FTA fault tree model by directly mapping the fault tree representation of the existing fault case library, thereby reducing the requirements for fault tree creation personnel, reducing the creation work amount, and shortening the time cost. By binding the fault node device and setting the event node fault diagnosis tool, realizing real-time dynamic fault diagnosis analysis. The specific solution is as follows:

[0028] As shown in FIGS. 1 to 5, the method for automatically generating an FTA real-time dynamic tree based on a fault knowledge base proposed in this application includes the following steps. In step 1, a new FTA logical model is created by generating an FTA real-time dynamic tree based on the fault knowledge base. This step is performed by a computer. Specifically, we select a method to create a new FTA logic model and generate an FTA real-time dynamic tree based on the fault knowledge base. This step can eliminate the analysis process of manually checking top events, intermediate events, basic events, and event-related logic gates, and the cumbersome process of using the dragging method on the drawing board to create a fault tree step by step.

[0029] In step 2, a fault knowledge base model is selected based on a logical device, where the logical device is an abstract description of a classification of instantiated devices, such as a hydroelectric generating unit, a rotor, an upper guide shoe, an upper frame, etc. The fault knowledge base model builds a knowledge base of power device failure modes and their effects according to a prescribed field (not limited to) of historical device failures (multiple levels) at different levels such as system, subsystem, device, component, etc. This step is performed by a computer.

[0030] The relationship between the logical device and the fault knowledge base model is as follows: Since the historical faults recorded in the fault knowledge base are all created for model management according to the logical device classification, the mapping and conversion from the cases in the fault knowledge base to the FTA fault tree should also be done according to the logical device classification.

[0031] Specifically, in this step, we first filter the failure modes according to the logical device, and then select the failure mode that the current node applies to. Then, by default, we map and convert the entire tree of failure modes into the FTA fault tree logical model, but we also support pruning and converting part of the branch of the knowledge base model tree (the branch to be pruned must include the root node and the base node).

[0032] Explaining with reference to Fig. 2, if "Hydroelectric power generation unit shaft system operation fault" is selected as the fault knowledge base, the user can select the root node or intermediate node of the model tree, such as "Hydroelectric power generation unit shaft system operation fault", "Rotating unit fault", or "Shaft system instability", to cut it as the top event node of the FTA fault tree. If no selection is made, the whole model tree will be converted by default.

[0033] In step 3, the fault knowledge base model is dynamically decomposed and mapped into the FTA logical fault tree model based on the FTA logical model construction rules. This step is performed by a computer.

[0034] Specifically, based on the fault knowledge base model selected in step 2, a) for example, select the "failure of rotating unit" node as the fault tree top event. Convert the "failure of rotating unit" knowledge base model node into an FTA fault tree top event node, set the logical gate (OR gate) of the node to the logical gate of the fault tree node, set the name to the failure mode of the fault tree node, and set the associated logical device to the associated logical device of the fault tree node. b) Map the intermediate "shaft system instability" node of the fault knowledge base model tree to the intermediate event node of the FTA fault tree model. The node data relationship is the same as that of the top node. c) Map the end nodes of the fault knowledge base model tree, "loose upper frame support bolt", "loose bush support member", "large bush clearance", and "shaft system change", in that order to the basic event node of the FTA fault tree model. The node data relationship is the same as that of the top node. d) Map the fault knowledge base model to the FTA fault tree logical model, and the mapping is completed.

[0035] In step 4, a fault diagnosis tool for the event node is set. This step is performed by a computer.

[0036] Alternatively, if a static analysis needs to be performed using a fault tree, the occurrence probability of the basic events of the fault tree needs to be manually set. To dynamically diagnose the fault tree in real time, the fault diagnosis tools of the fault tree nodes need to be manually set. The current fault diagnosis tool supports four diagnosis tools: measurement points, diagnosis rules, algorithm models, and scripts. The configuration rules are as follows:

[0037] A fault diagnosis tool is selected based on the type of device currently configured in the fault node. If the fault occurrence probability can be directly diagnosed based on the monitoring data value of the device measurement point, or the fault occurrence probability can be diagnosed by a simple condition judgment, the fault diagnosis tool can be directly configured as a measurement point. If a business rule is required to diagnose the fault occurrence probability in this device, the fault diagnosis tool is configured as a diagnosis rule. If the data amount of the device measurement point is larger than a preset threshold, or the calculation method is complicated and requires the calculation of a special hydraulic algorithm to diagnose the fault occurrence probability, the fault diagnosis tool can be configured as an algorithm model. If the fault that occurred in this device can be covered by the fault case library, the fault diagnosis tool can be configured as a script. i. Measurement point: A measurement point of a detection device under a logical device related to the node is selected, and the occurrence probability and occurrence status of a failure of the node are diagnosed based on the data of the measurement point. ii. Diagnosis rule: Based on the business rules related to the logical devices of the node, the rule engine is invoked to diagnose the occurrence probability and the occurrence status of the failure of the node. iii. Algorithm model: Based on the hydro-specific algorithm associated with the node's logical device, the algorithm engine is invoked to diagnose the occurrence probability and fault occurrence status of the node. iv. Script: Based on the relevant cases in the fault case library related to the logical device of the node, the case library diagnosis algorithm is invoked to diagnose the occurrence probability and occurrence status of the fault of the node.

[0038] As shown in Fig. 3, when the related logical device is "rotor", the corresponding fault has a matching case in the fault case library, so a script is applied as a fault diagnosis tool. When setting a fault diagnosis tool for a node, a script-based fault detection tool is set for the node based on the above rules, and a script for "amplitude hardly changes when rotation is constant" is set for the node "rotating unit fault", and a script for "vibrates regardless of excitation or load" is set for the node "shaft system instability".

[0039] Step 5 completes the construction of the FTA logical fault tree. This step is performed by a computer. Specifically, the created FTA fault tree logical model is saved and later used for instantiation of another physical device.

[0040] Step 6 exposes the logic model and instantiates the FTA logic model. This step is performed by a computer. Specifically, we first publish the logical model and enable the newly created FTA fault tree logical model. Only valid models can be instantiated. Then, we perform the instantiation operation, select the plant and instantiation device tree corresponding to the model to be instantiated, and enter the model instantiation process. In the instantiation process, we convert the logical devices bound to the nodes of the FTA fault tree logical model into physical devices in the instantiation device tree of the plant, and convert the logical fault diagnosis tools bound to the nodes into instantiation tools.

[0041] Step 7 is to configure the scheduling task. This step is performed by the computer. Specifically, this step is as follows: a) A timing task is created and the instantiation model is periodically called to perform fault diagnosis. b) If a diagnostic tool is set for an event node, the diagnosis process sequentially calls the diagnostic tool set for the node, obtains the alarm state and occurrence probability of the node, and substitutes the occurrence probability into the fault tree model. If a diagnostic tool is not set for an intermediate node, the occurrence probability of the node is estimated by a fault diagnosis method (Min Cut Set, Min Path Set, etc.) until the alarm state and occurrence probability of the top event are finally estimated.

[0042] Step 8 is to issue a fault alarm. This step is performed by the computer. Periodically perform fault diagnosis according to the scheduling task configured in step 7, and generate an instance diagram of the fault diagnosis result, i.e., one complete FTA fault tree. This tree identifies the fault status and occurrence probability of each event node.

[0043] 11 is a description of related concepts in the present embodiment. Logical Modeling: Use logical models to define static FTA fault trees, completing the static analysis capabilities of traditional fault trees. Reuse logical models to generate instantiation models. Model Instance: Model instances are used to realize dynamic fault tree diagnosis upgrade. Scheduling Configuration: Using the scheduling configuration, the instantiated fault tree model diagnosis can be scheduled and executed periodically or in real-time. Fault Instance: By combining model instances and scheduling configurations, we realize real-time dynamic fault tree diagnosis capability. One fault tree instance is generated for each diagnosis, which shows the real-time fault tree occurrence probability and fault conditions.

[0044] Example 1 Here, the generator fault tree generation process is taken as an example to describe the present invention in detail with reference to the attached drawings 4-5. In step 1, a new FTA logical model is constructed by generating an FTA real-time dynamic tree based on the fault knowledge base. This step is performed by a computer.

[0045] In step 2, the fault knowledge base is filtered in the failure mode list by the logical path "main transformer system" to find the "generator fault" model, and the FTA model is generated. This step is performed by a computer.

[0046] In step 3, the fault knowledge base model is dynamically decomposed and mapped into the FTA logical fault tree model based on the construction rules of the FTA logical model. This step is performed by a computer. Specifically, the fault knowledge base model selected in step 2 will be described with reference to FIG. 4. a) As an example, select the "generator failure" node as the fault tree top event. Convert the "generator failure" knowledge base model node to the FTA fault tree top event node, and set the logic gate (OR gate) of the node to the logic gate of the fault tree node, the name to the failure mode of the fault tree node, and the associated logic device to the associated logic device of the fault tree node. b) Map the intermediate "high temperature overheating (over 700) °C" node of the fault knowledge base model tree to the FTA fault tree model intermediate event node. The node data relationship is the same as the setting of the top node. c) Map the end node "transformer failure" of the fault knowledge base model tree to the basic event node of the FTA fault tree model. The node data relationship is the same as the setting of the top node. d) Map the fault knowledge base model to the FTA fault tree logical model, and the mapping is completed.

[0047] In step 4, a fault diagnosis tool for the event node is set. This step is performed by a computer. Associate the logical device "Main transformer" with the "High temperature overheating (over 700) °C" node, and set the fault diagnosis tool to the diagnosis rule (transformer three-ratio value diagnosis method).

[0048] Step 5 completes the construction of the FTA logical fault tree. This step is performed by a computer. Specifically, the created FTA fault tree logical model can be saved and later used for instantiation of another physical device, as shown in Figure 5.

[0049] Step 6 exposes the logic model and instantiates the FTA logic model. This step is performed by a computer. Specifically, we first publish the logical model and enable the newly created FTA fault tree logical model. Only valid models can be instantiated. Then, we perform the instantiation operation to select the plant and instantiation device tree corresponding to the model to be instantiated, and enter the model instantiation process. In the instantiation process, we convert the logical devices bound to the nodes of the FTA fault tree logical model into physical devices in the instantiation device tree of the plant, and convert the logical fault diagnosis tools bound to the nodes into instantiation tools.

[0050] Step 7 is to configure the scheduling task. This step is performed by the computer. Specifically, the steps include the following: a) Create a timing task and periodically call the instantiation model to perform fault diagnosis; b) If a diagnostic tool is set for an event node, the diagnosis process sequentially calls the diagnostic tool set for the node, obtains the alarm state and occurrence probability of the node, and substitutes the occurrence probability into the fault tree model; if a diagnostic tool is not set for an intermediate node, estimate the occurrence probability of the node by a fault diagnosis method (minimum cut set, minimum path set, etc.) until the alarm state and occurrence probability of the top event are finally estimated.

[0051] Step 8 is to issue a fault alarm. This step is performed by the computer. Periodically perform fault diagnosis according to the scheduling task configured in step 7, and generate an instance diagram of the fault diagnosis result, i.e., a complete FTA fault tree. This tree identifies the fault conditions and occurrence probability of each event node.

[0052] The above embodiments are only preferred technical solutions of the present invention, and should not be considered as limiting the present invention, and the scope of protection of the present invention should cover the technical solutions described in the claims and equivalent alternatives containing the technical features in the technical solutions described in the claims, that is, equivalent alternative improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A method for automatically generating an FTA real-time dynamic tree based on a fault knowledge base, comprising: Step 1: constructing a new FTA logical model by a method of generating an FTA real-time dynamic tree based on a fault knowledge base; Step 2 of selecting a fault knowledge base model based on a logic device; Step 3: building a fault library based on the FTA logic model to generate logic rules for the FTA model, and decomposing and mapping the fault knowledge base model to the FTA logic fault tree model; Step 4: setting a fault diagnosis tool for the event node; Step 5 of completing the construction of the FTA logical fault tree; Step 6 of publishing the FTA logic model and instantiating the FTA logic model; A step 7 of configuring the scheduling task; Step 8: periodically performing fault diagnosis and issuing a fault alarm by the configured scheduling task; Including, In step 2, the logical device is an abstract description of a classification of instantiated devices, step 2 comprising: Step 2.1: filtering failure modes based on logic devices and selecting a failure mode that the current node matches; Step 2.2, which maps and transforms the entire tree of failure modes into an FTA fault tree logic model; as a sub-step, In step 3, the fault library generates a logic rule of an FTA model according to the fault knowledge base model selected in step 2 by mapping a top node to a top event of an FTA fault tree, a middle node to a middle event node of the FTA fault tree, and an end node to a basic event node of the FTA fault tree, where the top node, the middle node, and the end node are branch nodes in the FTA fault tree; When mapping to nodes, synchronously map the associations of each hierarchical node, each hierarchical node including a top node, an intermediate node, and an end node; In step 4, the fault diagnosis tool includes measurement points, diagnosis rules, algorithm models and scripts; The principle of diagnosing the measurement point is to select the measurement point of the detection device under the logical device related to the node, and diagnose the occurrence probability and the fault occurrence status of the node based on the data of the measurement point; The diagnostic principle of the diagnostic rule is to call the rule engine based on the business rule related to the logical device of the node to diagnose the occurrence probability and the fault occurrence status of the node; The diagnosis principle of the algorithm model is to call the algorithm engine based on the hydroelectric power generation dedicated algorithm associated with the logical device of the node to diagnose the occurrence probability and fault occurrence status of the node; The diagnostic principle of the script is to call a case library diagnostic algorithm based on the relevant cases in the fault case library related to the logical device of the node to diagnose the occurrence probability and fault occurrence situation of the node; In step 4, the purpose of setting the fault diagnosis tools for the nodes of the fault tree is to perform dynamic analysis using the fault tree; Dynamic analysis is 1) A situation in which a probability of failure is predicted by a diagnostic tool at a measurement point of a detection device of a logic device; 2) A situation in which a rule diagnosis engine is called to predict the probability of a failure occurring for the business rules of a logical device; 3) if the amount of data at the measurement points of the device is greater than a predefined threshold, an algorithm engine associated with the logic device is invoked to predict the node failure probability; Some of the situations include: Step 6 is: Step 6.1 of publishing the logic model and validating the newly created FTA fault tree logic model; Next, instantiation is performed by selecting a plant and an instantiation device tree corresponding to the model to be instantiated, and entering the instantiation process of the model. In the instantiation process, the logical devices bound to the nodes of the FTA fault tree logical model are converted into physical devices in the instantiation device tree of the plant, and the logical fault diagnosis tools bound to the nodes are converted into instantiation tools; step 6.

2. as a sub-step, Step 7 is Step 7.1 creating a timing task and periodically invoking the instantiated model for fault diagnosis; Step 7.2 of the diagnosis process, in which if a diagnosis tool is set in the event node, the diagnosis tools set in the node are called in sequence, the alarm status and occurrence probability of the node are obtained, and the occurrence probability is substituted into the fault tree model; if the diagnosis tool is not set in the intermediate node, the occurrence probability of the node is estimated by the fault diagnosis method until the alarm status and occurrence probability of the top event are finally estimated; as a sub-step, In step 8, periodic fault diagnosis is performed on the scheduling task created in step 7 to generate a complete FTA fault tree, and the FTA fault tree identifies the fault conditions and occurrence probability of each event node.

Images