An online diagnosis method for third-generation passive pressurized water reactor nuclear power plants
By preprocessing the operating signals of third-generation passive pressurized water reactor nuclear power plants and using fuzzy expert knowledge base diagnosis, accident types can be quickly and accurately identified, solving the problem of nuclear power plant accident diagnosis and ensuring correct decision-making under severe accident conditions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA NUCLEAR POWER OPERATION TECH CORP
- Filing Date
- 2023-06-06
- Publication Date
- 2026-07-14
AI Technical Summary
In the event of an accident at a third-generation passive pressurized water reactor nuclear power plant, the incompleteness and decreased accuracy of plant condition monitoring information increase the difficulty of making correct decisions and may lead to the escalation of the accident.
This paper provides an online diagnostic method that preprocesses nuclear power plant operating signals, identifies state intervals, accident symptoms, and abnormal system states, and constructs a diagnostic tree using a fuzzy expert knowledge base to quickly and accurately identify accident types.
Within 300 seconds, it can diagnose the state range, accident signs, abnormal system states, and accident types of nuclear power plants with an accuracy rate of over 95%, achieving rapid and accurate accident diagnosis.
Smart Images
Figure CN116994786B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of nuclear power simulation technology, and in particular to an online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants. Background Technology
[0002] Third-generation passive pressurized water reactor nuclear power plants have complex structures and involve numerous pieces of equipment. To ensure timely and comprehensive monitoring of their status, each piece of equipment is equipped with sensors for real-time monitoring. Therefore, when anomalies occur in the operation of a nuclear power plant, especially when it develops into a severe accident, plant operators and emergency response technicians need to locate abnormal information from massive amounts of monitoring data and alarm signals to make correct decisions. Furthermore, severe accidents are often accompanied by power loss, widespread instrument damage, and widespread instrument failure. At this time, the plant's status monitoring information is incomplete and inaccurate, further complicating decision-making. If improper operation is performed due to human error or other risks, the accident could escalate rapidly. Therefore, personnel in this situation experience immense work and psychological pressure. In the event of a nuclear power plant accident, it is necessary to diagnose the root cause of the accident and the current operating status based on limited and reliable operational data, providing strong technical support for emergency response. Summary of the Invention
[0003] The purpose of this invention is to provide an online accident diagnosis method for third-generation advanced passive pressurized water reactor nuclear power plants. This method can quickly, accurately, and comprehensively diagnose accidents in third-generation advanced passive pressurized water reactor nuclear power plants based on a small number of operating signals.
[0004] To achieve the above objectives, the present invention provides the following technical solution:
[0005] A method for online accident diagnosis in a third-generation passive pressurized water reactor nuclear power plant includes the following steps:
[0006] S101. Preprocess the read operating signals of the third-generation passive pressurized water reactor nuclear power plant to obtain standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0007] S102. Identify the state range of a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0008] S103. Identify accident signs in third-generation passive pressurized water reactor nuclear power plants based on standardized operating signals of third-generation passive pressurized water reactor nuclear power plants.
[0009] S104. Identify abnormal states of the third-generation passive pressurized water reactor nuclear power plant system based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0010] S105. Identify the accident types of third-generation passive pressurized water reactor nuclear power plants based on accident symptoms and abnormal system states.
[0011] Furthermore, in S101, the read operating signals of the third-generation passive pressurized water reactor nuclear power plant are preprocessed, including checking the validity of the read operating signals and identifying and processing abnormal signals in the read operating signals; checking the validity of the read operating signals includes checking whether the signals are within the design range and checking the consistency of multiple signal channels; identifying and processing abnormal signals in the read operating signals includes identifying default values, abnormal values and multiple signals in the read operating signals, removing default values and abnormal values in the operating signals, and merging multiple signals in the read operating signals.
[0012] Further, S102 includes the following steps:
[0013] S1021. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, judge each issue related to the state interval of the third-generation passive pressurized water reactor nuclear power plant, and obtain the judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant.
[0014] S1022. The judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant are correlated with the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant to obtain the state interval of the third-generation passive pressurized water reactor nuclear power plant.
[0015] The judgment result for each question related to the state interval of the third-generation passive pressurized water reactor nuclear power plant is either yes or no. If the judgment result is yes, the column containing that question in the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is set to 1; if the judgment result is no, the column containing that question in the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is set to 0. The state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is the state interval of the third-generation passive pressurized water reactor nuclear power plant corresponding to the judgment results of all questions related to the state interval of the third-generation passive pressurized water reactor nuclear power plant.
[0016] Further, S103 includes the following steps: identifying accident signs of a third-generation passive pressurized water reactor nuclear power plant by comparing the change in the value of the operating signal of the third-generation passive pressurized water reactor nuclear power plant at the current time with that at the previous time, or by whether the value of the operating signal of the third-generation passive pressurized water reactor nuclear power plant at the current time exceeds a set threshold range.
[0017] Furthermore, the accident warning signs of a third-generation passive pressurized water reactor nuclear power plant include low main system pressure, main system pressure drop, pressure vessel not malfunctioning, high containment pressure, rising containment pressure, rising sump water level, high evaporator radiation dose, high evaporator water level, rising evaporator water level, operators observing SGTR occurring, suspected main system breach with coolant leakage (not containment), loss of AC power, low pressurizer water level, main system temperature drop, high main system pressure, high containment pressure, high containment temperature, reactor shutdown, and decreased reactor power.
[0018] Further, S104 includes the following steps:
[0019] S1041. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, determine the likelihood function variables for each problem related to the identification of abnormal states in the third-generation passive pressurized water reactor nuclear power plant system.
[0020] S1042. Calculate the confidence probability of each question related to the identification of abnormal states in a third-generation passive pressurized water reactor nuclear power plant system based on the likelihood function.
[0021] S1043. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, calculate the confidence probability of each question that is true in relation to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system.
[0022] S1044. Take the arithmetic mean of the confidence probabilities of all questions related to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system to obtain the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system.
[0023] S1045. Determine whether the calculation results of S1043 and S1044 meet the set confidence probability judgment conditions for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system. If the confidence probability judgment conditions for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system are met, then identify the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system.
[0024] The confidence probability judgment condition for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is as follows: the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is greater than 0.5; or the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is greater than 0.5, and the confidence probability of one or more issues related to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system being true is greater than 0.5.
[0025] Furthermore, the abnormal states of the third-generation passive pressurized water reactor nuclear power plant system include charging-drainage anomalies; issues related to identifying charging-drainage anomalies include: whether there is an indication of high-pressure injection flow rate, and whether the high-pressure injection flow rate value is close to the expected value; whether the pressurizer water level is high or rising; whether the secondary side heat sink is ineffective or lost; whether there was no previous obvious breach indication; whether the main system pressure change is consistent with the high-pressure injection flow rate; and whether saturated water is found to be flowing out of the release valve; the confidence probability judgment condition for charging-drainage anomalies is: the confidence probability of charging-drainage anomalies is greater than 0.5, and the confidence probability of the first issue related to charging-drainage anomalies being true is greater than 0.5.
[0026] Further, S105 includes the following steps:
[0027] The fuzzy expert knowledge base constructs a diagnostic tree for each type of accident in a third-generation passive pressurized water reactor nuclear power plant based on the diagnostic conditions for each type of accident.
[0028] Based on the diagnostic tree of each type of accident in the third-generation passive pressurized water reactor nuclear power plant, determine whether each diagnostic condition of each type of accident in the third-generation passive pressurized water reactor nuclear power plant is valid, and calculate the confidence probability of each diagnostic condition of each type of accident in the third-generation passive pressurized water reactor nuclear power plant being valid.
[0029] The confidence probability of each type of accident in a third-generation passive pressurized water reactor nuclear power plant is obtained by taking the arithmetic average of the confidence probabilities of all diagnostic conditions being met for each type of accident.
[0030] If the confidence probability of this type of accident in a third-generation passive pressurized water reactor nuclear power plant is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is determined to have this type of accident.
[0031] The diagnostic criteria for each type of accident in a Generation III passive pressurized water reactor (PWR) nuclear power plant include several accident symptoms and / or abnormal states of the PWR system.
[0032] Furthermore, accidents in third-generation passive pressurized water reactor nuclear power plants include coolant loss accidents, heat transfer tube rupture accidents, plant-wide power outage accidents, main steam pipeline rupture accidents, and unexpected shutdown accidents.
[0033] This invention also provides a third-generation passive pressurized water reactor nuclear power plant accident online diagnostic system, comprising:
[0034] The data processing module 201 is used to preprocess the read operating signals of the third-generation passive pressurized water reactor nuclear power plant to obtain standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0035] The first identification module 202 is used to identify the state range of a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0036] The second identification module 203 is used to identify accident signs in a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0037] The third identification module 204 is used to identify abnormal states of the third-generation passive pressurized water reactor nuclear power plant system based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0038] The fourth identification module 205 is used to identify the accident type of the third-generation passive pressurized water reactor nuclear power plant based on the accident symptoms and abnormal system states of the third-generation passive pressurized water reactor nuclear power plant.
[0039] Data is connected between the data processing module 201, the first identification module 202, the second identification module 203, the third identification module 204, and the fourth identification module 205.
[0040] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the above-described online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants.
[0041] The present invention also provides a computer-readable storage medium storing computer-readable instructions, which, when executed, implement the steps of the above-described online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants.
[0042] Beneficial technical effects of the present invention:
[0043] The present invention relates to an online accident diagnosis method, system, computer equipment, and storage medium for third-generation advanced passive pressurized water reactor nuclear power plants. Based on 120 operational data points from a third-generation advanced passive pressurized water reactor nuclear power plant, the method can complete the diagnosis of the plant's state range, accident symptoms, system anomalies, and accident types within 300 seconds, with an accuracy rate of over 95%. This enables rapid, accurate, and comprehensive accident diagnosis of third-generation advanced passive pressurized water reactor nuclear power plants. Attached Figure Description
[0044] Figure 1 A flowchart of an embodiment of the online accident diagnosis method for the third-generation advanced passive pressurized water reactor nuclear power plant of the present invention;
[0045] Figure 2 This is a schematic diagram of an embodiment of the third-generation advanced passive pressurized water reactor nuclear power plant accident online diagnosis system of the present invention;
[0046] Figure 3 This is a schematic diagram of the structure of an embodiment of the computer device of the present invention. Detailed Implementation
[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the specification, claims, and foregoing drawings are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings are used to distinguish different objects and not to describe a particular order.
[0048] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0049] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments.
[0050] See Figure 1 This embodiment provides an online accident diagnosis method for a third-generation passive pressurized water reactor nuclear power plant, including the following steps:
[0051] S101. The read third-generation passive pressurized water reactor nuclear power plant operation signals are preprocessed to obtain the standardized third-generation passive pressurized water reactor nuclear power plant operation signals as shown in Table 1.
[0052] S102. Identify the state range of a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0053] S103. Identify accident signs in third-generation passive pressurized water reactor nuclear power plants based on standardized operating signals of third-generation passive pressurized water reactor nuclear power plants.
[0054] S104. Identify abnormal states of the third-generation passive pressurized water reactor nuclear power plant system based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0055] S105. Identify the accident types of third-generation passive pressurized water reactor nuclear power plants based on accident symptoms and abnormal system states.
[0056] It should be understood that multiple sub-steps or multiple stages in each step are not necessarily completed at the same time, but can be executed at different times. Their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.
[0057] In this embodiment, in S101, the read third-generation passive pressurized water reactor (PWR) nuclear power plant operating signals are preprocessed, including checking the validity of the read third-generation passive PWR nuclear power plant operating signals and identifying and processing abnormal signals in the read third-generation passive PWR nuclear power plant operating signals; checking the validity of the read third-generation passive PWR nuclear power plant operating signals includes checking whether the signals are within the design range and checking the consistency of multiple signal channels; identifying and processing abnormal signals in the read third-generation passive PWR nuclear power plant operating signals includes identifying default values, abnormal values and multiple signals in the read third-generation passive PWR nuclear power plant operating signals, removing default values and abnormal values in the third-generation passive PWR nuclear power plant operating signals, and merging multiple signals in the read third-generation passive PWR nuclear power plant operating signals.
[0058] Table 1 Standardized Operating Signals for Generation III Passive Pressurized Water Reactor Nuclear Power Plants
[0059]
[0060]
[0061]
[0062]
[0063] In this embodiment, S102 includes the following steps:
[0064] S1021. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, judge each issue related to the state interval of the third-generation passive pressurized water reactor nuclear power plant, and obtain the judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant.
[0065] S1022. The judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant are correlated with the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant shown in Table 2 to obtain the state interval of the third-generation passive pressurized water reactor nuclear power plant.
[0066] In this embodiment, as shown in Table 2, the issues related to the state range of a third-generation passive pressurized water reactor nuclear power plant include issues 1, 2, 3, 4, 5, 6, 7, and 8. Specifically, issue 1 is whether the reactor core is exposed; issue 2 is whether the core exposure has exceeded 10 minutes; issue 3 is whether the core outlet temperature exceeds 1300K; issue 4 is whether the containment environment is highly radioactive; issue 5 is whether the containment temperature exceeds 600K; issue 6 is whether the main system pressure is close to the containment pressure; issue 7 is whether the containment pressure exceeds the design baseline and is rising; and issue 8 is… Whether the containment pressure rise exceeds 30 minutes; the judgment result for each question related to the state interval of the third-generation passive pressurized water reactor nuclear power plant is yes or no; if the judgment result is yes, the column containing that question in the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is 1; if the judgment result is no, the column containing that question in the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is 0; the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is the state interval of the third-generation passive pressurized water reactor nuclear power plant corresponding to the judgment results of all questions related to the state interval of the third-generation passive pressurized water reactor nuclear power plant.
[0067] Table 2. State Relationship Matrix of Third-Generation Passive Pressurized Water Reactor Nuclear Power Plants
[0068]
[0069]
[0070] In this embodiment, S103 includes the following steps:
[0071] Accident signs in third-generation passive pressurized water reactor nuclear power plants can be identified by comparing the changes in the operating signals of the third-generation passive pressurized water reactor nuclear power plant at the current moment with those at the previous moment, or by checking whether the current value of the operating signals of the third-generation passive pressurized water reactor nuclear power plant is within a set threshold range.
[0072] In this embodiment, the accident symptoms of a third-generation passive pressurized water reactor nuclear power plant include low main system pressure, main system pressure drop, pressure vessel not malfunctioning, high containment pressure, rising containment pressure, rising sump water level, high evaporator radioactivity dose, high evaporator water level, rising evaporator water level, operators observing SGTR occurring, suspected main system breach with coolant leakage (not containment), loss of AC power, low pressurizer water level, main system temperature drop, high main system pressure, high containment pressure, high containment temperature, reactor shutdown, and decreased reactor power.
[0073] If the current main system pressure is less than 95% of the pressurizer safety valve opening threshold, the main system pressure is identified as low; if the rate of change of the main system pressure from the current moment to the previous moment is less than zero, the main system pressure is identified as decreasing; if the state range of the third-generation passive pressurized water reactor nuclear power plant is before pressure vessel failure, the pressure vessel is identified as not having failed; if the current containment pressure is greater than 175% of atmospheric pressure, the containment pressure is identified as high; if the rate of change of the containment pressure from the current moment to the previous moment is greater than zero, the containment pressure is identified as rising; if the rate of change of the sump water level from the current moment to the previous moment is greater than zero, the sump water level is identified as rising; if the current evaporator radioactivity dose is greater than the average radioactivity dose of other evaporators, the evaporator radioactivity dose is identified as high; if the current evaporator water level is greater than the evaporator high water level setpoint, the evaporator water level is identified as high; if the rate of change of the evaporator water level from the current moment to the previous moment is greater than zero, the evaporator water level is identified as rising; if operators observe SGTR... If a signal has occurred, it is identified that the SGTR has been observed by the operators; if there is a suspected main system breach and coolant loss, but not a containment signal, it is identified that the suspected main system breach and coolant loss are not containment signals; if there is an AC power loss signal, it is identified that AC power has been lost; if the current pressurizer water level is lower than the pressurizer steady-state operating water level, it is identified that the pressurizer water level is low; if the rate of change of the main system temperature from the previous time is greater than the maximum rate allowed by the regulations, it is identified that the main system temperature has decreased; if the current main system pressure is greater than the pressure of the damaged evaporator, it is identified that the main system pressure is high; if the current containment pressure is greater than 175% of atmospheric pressure, it is identified that the containment pressure is high; if the current containment temperature is greater than 120% of the containment steady-state operating temperature, it is identified that the containment temperature is high; if there is a reactor shutdown signal, it is identified that the reactor has shut down; if the rate of change of the reactor power from the previous time is greater than the decay heat theoretical curve, it is identified that the reactor power has decreased.
[0074] In this embodiment, S104 includes the following steps:
[0075] S1041. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, determine the likelihood function variables for each problem related to the identification of abnormal states in the third-generation passive pressurized water reactor nuclear power plant system.
[0076] S1042. Calculate the confidence probability of each question related to the identification of abnormal states in a third-generation passive pressurized water reactor nuclear power plant system based on the likelihood function.
[0077] S1043. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, calculate the confidence probability of each question that is true in relation to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system.
[0078] S1044. Take the arithmetic mean of the confidence probabilities of all questions related to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system to obtain the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system.
[0079] S1045. Determine whether the calculation results of S1043 and S1044 meet the set confidence probability judgment conditions for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system. If the confidence probability judgment conditions for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system are met, then identify the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system.
[0080] The confidence probability judgment condition for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is as follows: the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is greater than 0.5; or the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is greater than 0.5, and the confidence probability of one or more issues related to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system being true is greater than 0.5.
[0081] In this embodiment, the abnormal states of the third-generation passive pressurized water reactor nuclear power plant system include charging and draining anomalies; issues related to identifying charging and draining anomalies include: whether there is an indication of high-pressure injection flow rate, and whether the high-pressure injection flow rate value is close to the expected value; whether the pressurizer water level is high or rising; whether the secondary heat sink is invalid or lost; whether there was no obvious breach indication before; whether the main system pressure change is consistent with the high-pressure injection flow rate; and whether saturated water is found to be flowing out of the release valve.
[0082] Based on standardized operating signals from third-generation passive pressurized water reactor nuclear power plants, likelihood function variables for each problem related to the identification of charging and leaking anomalies are determined. For example, the likelihood function variable for the first problem related to charging and leaking anomaly identification is x1 = 5(2 * (current high-pressure injection flow rate / expected high-pressure injection flow rate) - 1); the likelihood function variable for the second problem related to charging and leaking anomaly identification is x2 = 5(2 * (current pressurizer water level / expected pressurizer water level) - 1); the likelihood function variable for the third problem related to charging and leaking anomaly identification is x3 = 5(2 * (current secondary heat sink value / expected secondary heat sink value) - 1); the likelihood function variable for the fourth problem related to charging and leaking anomaly identification is x4 = 5(2 * (current breach value / expected breach value) - 1); and the likelihood function variable for the fifth problem related to charging and leaking anomaly identification is x5 = 5(2 * (current main system pressure value / expected main system pressure) - 1).
[0083] The confidence probability of each question related to the identification of abnormalities in the supply and demand process is calculated using the likelihood function. The confidence probability of the first question related to the identification of abnormalities in the supply and demand process is f(x1) = 1 / (1+e -x1 The confidence probability of the second question related to the abnormal identification of upper and lower leakage is f(x2) = 1 / (1+e -x2 The confidence probability of the third question related to the abnormal identification of upper and lower leakage is f(x3) = 1 / (1+e -x3 The confidence probability of the fourth question related to the abnormal identification of upper and lower leakage is f(x4) = 1 / (1+e -x4 The confidence probability of the fifth question related to the abnormal identification of upper and lower leakage is f(x5) = 1 / (1+e -x5 The likelihood function is: f(x) = 1 / (1+e^(-x)). -x x is the likelihood function variable, and f(x) is the confidence probability.
[0084] The arithmetic mean of the confidence probabilities of all questions related to the identification of abnormal charging and discharging is taken to obtain the confidence probability of abnormal charging and discharging = (f(x1)+f(x2)+f(x3)+f(x4)+f(x5)) / 5;
[0085] If the calculated confidence probability of the abnormal charging and discharging meets the set confidence probability judgment condition for the abnormal charging and discharging, then the abnormal charging and discharging is identified.
[0086] The confidence probability judgment condition for abnormal charging and leaking is: the confidence probability of abnormal charging and leaking is greater than 0.5, and the confidence probability of the first question related to the identification of abnormal charging and leaking is greater than 0.5.
[0087] In this embodiment, step S105 includes the following steps:
[0088] The fuzzy expert knowledge base constructs a diagnostic tree for each type of accident in a third-generation passive pressurized water reactor nuclear power plant based on the diagnostic conditions for each type of accident.
[0089] Based on the diagnostic tree of each type of accident in the third-generation passive pressurized water reactor nuclear power plant, determine whether each diagnostic condition of each type of accident in the third-generation passive pressurized water reactor nuclear power plant is valid, and calculate the confidence probability of each diagnostic condition of each type of accident in the third-generation passive pressurized water reactor nuclear power plant being valid.
[0090] The confidence probability of each type of accident in a third-generation passive pressurized water reactor nuclear power plant is obtained by taking the arithmetic average of the confidence probabilities of all diagnostic conditions being met for each type of accident.
[0091] If the confidence probability of this type of accident in a third-generation passive pressurized water reactor nuclear power plant is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is determined to have this type of accident.
[0092] In this embodiment, accidents in third-generation passive pressurized water reactor nuclear power plants include coolant loss accidents, heat transfer tube rupture accidents, plant-wide power outage accidents, main steam pipeline rupture accidents, and unexpected shutdown accidents.
[0093] In this embodiment, the diagnostic conditions for coolant loss accidents are as follows: First diagnostic condition: low main system pressure; Second diagnostic condition: main system pressure drop; Third diagnostic condition: pressure vessel not failed; Fourth diagnostic condition: high containment pressure; Fifth diagnostic condition: containment pressure rise; Sixth diagnostic condition: sump water level rise; Seventh diagnostic condition: abnormal charging and discharging; The fuzzy expert knowledge base constructs a diagnostic tree for coolant loss accidents based on the diagnostic conditions for coolant loss accidents.
[0094] Determining whether a third-generation passive pressurized water reactor nuclear power plant has experienced a coolant loss accident includes the following steps:
[0095] Determine whether each diagnostic condition for a coolant loss accident is met based on the diagnostic tree for coolant loss accidents;
[0096] Calculate the confidence probability of each diagnostic condition for a coolant loss accident based on the diagnostic tree for coolant loss accidents;
[0097] The confidence probabilities of the first, second, fourth, fifth, and sixth diagnostic conditions being true are all calculated using the likelihood function, while the confidence probabilities of the third, seventh, and eighth diagnostic conditions being true are all 100%.
[0098] The confidence probability of a coolant loss accident = (confidence probability of the first diagnostic condition being met + confidence probability of the second diagnostic condition being met + confidence probability of the third diagnostic condition being met + confidence probability of the fourth diagnostic condition being met + confidence probability of the fifth diagnostic condition being met + confidence probability of the sixth diagnostic condition being met + confidence probability of the seventh diagnostic condition being met + confidence probability of the eighth diagnostic condition being met) / 8;
[0099] If the confidence probability of a coolant loss accident is greater than 0.5, then a third-generation passive pressurized water reactor nuclear power plant is considered to have a coolant loss accident.
[0100] In this embodiment, the diagnostic conditions for heat transfer tube rupture accidents are as follows: First diagnostic condition: high radiation dose to the evaporator; Second diagnostic condition: high water level in the evaporator; Third diagnostic condition: rising water level in the evaporator; Fourth diagnostic condition: operators observe that SGTR has occurred; Fifth diagnostic condition: suspected rupture in the main system and coolant leakage, not a containment structure; The fuzzy expert knowledge base constructs a diagnostic tree for heat transfer tube rupture accidents based on the diagnostic conditions.
[0101] Determining whether a heat transfer tube rupture accident exists in a third-generation passive pressurized water reactor nuclear power plant includes the following steps:
[0102] Determine whether each diagnostic condition for a coolant loss accident is met based on the diagnostic tree for coolant loss accidents;
[0103] Calculate the confidence probability of each diagnostic condition for heat transfer tube rupture accidents based on the diagnostic tree for such accidents.
[0104] The confidence probabilities of the first, second, third, and fifth diagnostic conditions being met are all calculated using the likelihood function, and the confidence probability of the fourth diagnostic condition being met is 100%.
[0105] The confidence probability of a heat transfer tube rupture accident = (confidence probability of the first diagnostic condition being met + confidence probability of the second diagnostic condition being met + confidence probability of the third diagnostic condition being met + confidence probability of the fourth diagnostic condition being met + confidence probability of the fifth diagnostic condition being met) / 5;
[0106] If the confidence probability of a heat transfer tube rupture accident is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is considered to have a heat transfer tube rupture accident.
[0107] In this embodiment, the diagnostic conditions for a plant-wide power outage are: First diagnostic condition: loss of AC power signal; the fuzzy expert knowledge base constructs a diagnostic tree for plant-wide power outages based on the diagnostic conditions.
[0108] Determining whether a third-generation passive pressurized water reactor nuclear power plant is at risk of a plant-wide power outage includes the following steps:
[0109] Determine whether each diagnostic condition for a power outage accident in the entire plant is met based on the diagnostic tree of power outage accidents in the entire plant.
[0110] Calculate the confidence probability of each diagnostic condition for a power outage accident in the entire plant based on the diagnostic tree of power outage accidents in the entire plant;
[0111] The confidence probability of the first diagnostic criterion being met is 100%.
[0112] The confidence probability of a plant-wide power outage accident equals the confidence probability of the first diagnostic condition being met.
[0113] If the confidence probability of a plant-wide power outage is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is considered to have a plant-wide power outage.
[0114] In this embodiment, the diagnostic conditions for main steam pipeline rupture accidents are as follows: First diagnostic condition: low pressurizer water level; Second diagnostic condition: main system temperature drop; Third diagnostic condition: high main system pressure; Fourth diagnostic condition: high containment pressure; Fifth diagnostic condition: high containment temperature; The fuzzy expert knowledge base constructs a diagnostic tree for main steam pipeline rupture accidents based on the diagnostic conditions.
[0115] Determining whether a third-generation passive pressurized water reactor nuclear power plant has a main steam pipe rupture accident includes the following steps:
[0116] Determine whether each diagnostic condition for a main steam pipeline rupture accident is met based on the diagnostic tree for such accidents.
[0117] Calculate the confidence probability of each diagnostic condition for a main steam pipeline rupture accident based on the diagnostic tree for such accidents.
[0118] The confidence probabilities of the first, second, third, fourth, and fifth diagnostic conditions being met are all calculated using the likelihood function.
[0119] The confidence probability of a main steam pipeline rupture accident = (confidence probability of the first diagnostic condition being met + confidence probability of the second diagnostic condition being met + confidence probability of the third diagnostic condition being met + confidence probability of the fourth diagnostic condition being met + confidence probability of the fifth diagnostic condition being met) / 5;
[0120] If the confidence probability of a main steam pipe rupture accident is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is determined to have a main steam pipe rupture accident.
[0121] In this embodiment, the diagnostic conditions for unexpected reactor shutdown accidents are: first diagnostic condition: reactor shutdown; second diagnostic condition: reactor power reduction; the fuzzy expert knowledge base constructs a diagnostic tree for unexpected reactor shutdown accidents based on the diagnostic conditions for unexpected reactor shutdown accidents.
[0122] Determining whether a third-generation passive pressurized water reactor nuclear power plant has an unexpected shutdown accident includes the following steps:
[0123] Determine whether each diagnostic condition for an unexpected reactor outage is met based on the diagnostic tree for unexpected outages.
[0124] Calculate the confidence probability of each diagnostic condition for an unexpected outage based on the diagnostic tree of unexpected outage accidents;
[0125] The confidence probability of the first diagnostic condition being true is 100%; the confidence probability of the second diagnostic condition being true is calculated using the likelihood function.
[0126] The confidence probability of an unexpected reactor shutdown accident = (confidence probability of the first diagnostic condition being met + confidence probability of the second diagnostic condition being met) / 2;
[0127] If the confidence probability of an unexpected shutdown accident is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is considered to have an unexpected shutdown accident.
[0128] The online accident diagnosis method for third-generation advanced passive pressurized water reactor nuclear power plants in this embodiment can complete the diagnosis of the state range, accident symptoms, system abnormal state and accident type of the third-generation advanced passive pressurized water reactor nuclear power plant within 300 seconds based on 120 operating data of the third-generation advanced passive pressurized water reactor nuclear power plant, with an accuracy rate of over 95%, realizing rapid, accurate and comprehensive accident diagnosis of third-generation advanced passive pressurized water reactor nuclear power plants.
[0129] refer to Figure 2 As an implementation of the above method, the present invention provides an embodiment of an online accident diagnosis system for a third-generation advanced passive pressurized water reactor nuclear power plant. This system embodiment corresponds to the embodiment of the above method, and the system embodiment can be applied to various electronic devices.
[0130] The third-generation passive pressurized water reactor nuclear power plant accident online diagnosis system described in this embodiment includes:
[0131] The data processing module 201 is used to preprocess the read operating signals of the third-generation passive pressurized water reactor nuclear power plant to obtain standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0132] The first identification module 202 is used to identify the state range of a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0133] The second identification module 203 is used to identify accident signs in a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0134] The third identification module 204 is used to identify abnormal states of the third-generation passive pressurized water reactor nuclear power plant system based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant.
[0135] The fourth identification module 205 is used to identify the accident type of the third-generation passive pressurized water reactor nuclear power plant based on the accident symptoms and abnormal system states of the third-generation passive pressurized water reactor nuclear power plant.
[0136] Data is connected between the data processing module 201, the first identification module 202, the second identification module 203, the third identification module 204, and the fourth identification module 205.
[0137] The third-generation advanced passive pressurized water reactor nuclear power plant accident online diagnostic system in this embodiment can complete the diagnosis of the state range, accident symptoms, system abnormal state and accident type of the third-generation advanced passive pressurized water reactor nuclear power plant within 300 seconds based on 120 operating data of the third-generation advanced passive pressurized water reactor nuclear power plant, with an accuracy rate of over 95%, realizing rapid, accurate and comprehensive accident diagnosis of the third-generation advanced passive pressurized water reactor nuclear power plant.
[0138] See Figure 3 This embodiment also provides a computer device, including a memory and a processor. The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, it implements the steps of the above-described online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants.
[0139] The computer device described in this embodiment includes a memory 301, a processor 302, and a network interface 303 that are interconnected via a system bus. It should be noted that only a computer device with components 301-303 is shown in the figures; however, it should be understood that it is not required to implement all shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits, programmable gate arrays, digital processors, embedded devices, etc.
[0140] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.
[0141] The memory 301 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory, random access memory, static random access memory, read-only memory, electrically erasable programmable read-only memory, programmable read-only memory, magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 301 may be an internal storage unit of the computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory 301 may also be an external storage device of the computer device, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc., equipped on the computer device. Of course, the memory 301 may include both the internal storage unit and the external storage device of the computer device. In this embodiment, the memory 301 is typically used to store the operating system and various application software installed on the computer device, such as the computer-readable instructions of the above-mentioned third-generation passive pressurized water reactor nuclear power plant accident online diagnosis method. In addition, the memory 301 may also be used to temporarily store various types of data that have been output or will be output.
[0142] In some embodiments, the processor 302 may be a central processing unit, a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 302 is typically used to control the overall operation of the computer device. In this embodiment, the processor 302 is used to execute computer-readable instructions stored in the memory 301 or to process data, for example, to execute the computer-readable instructions of the aforementioned third-generation passive pressurized water reactor nuclear power plant accident online diagnostic method.
[0143] The network interface 303 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device and other electronic devices.
[0144] The computer equipment in this embodiment can complete the diagnosis of the state range, accident signs, system abnormal state and accident type of the third-generation advanced passive pressurized water reactor nuclear power plant within 300 seconds based on 120 operating data of the third-generation passive pressurized water reactor nuclear power plant, with an accuracy rate of over 95%, realizing rapid, accurate and comprehensive accident diagnosis of the third-generation advanced passive pressurized water reactor nuclear power plant.
[0145] This embodiment also provides a computer-readable storage medium storing computer-readable instructions, which, when executed, implement the steps of the above-described online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants.
[0146] The computer-readable storage medium of this embodiment can complete the diagnosis of the state range, accident signs, system abnormal state and accident type of the third-generation advanced passive pressurized water reactor nuclear power plant within 300 seconds based on 120 operating data of the third-generation passive pressurized water reactor nuclear power plant, with an accuracy rate of over 95%, realizing rapid, accurate and comprehensive accident diagnosis of the third-generation advanced passive pressurized water reactor nuclear power plant.
[0147] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.
Claims
1. A method for online accident diagnosis in a third-generation passive pressurized water reactor nuclear power plant, characterized in that, Includes the following steps: S101. Preprocess the read operating signals of the third-generation passive pressurized water reactor nuclear power plant to obtain standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant. S102. Based on the standardized operating signals of third-generation passive pressurized water reactor nuclear power plants, identify the state range of third-generation passive pressurized water reactor nuclear power plants, specifically including the following steps: S1021. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, judge each issue related to the state interval of the third-generation passive pressurized water reactor nuclear power plant, and obtain the judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant. S1022. The judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant are correlated with the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant to obtain the state interval of the third-generation passive pressurized water reactor nuclear power plant. The judgment result for each question related to the state interval of a third-generation passive pressurized water reactor nuclear power plant is either yes or no; If the judgment result is yes, then the column containing the problem in the state relationship matrix of the corresponding third-generation passive pressurized water reactor nuclear power plant will have a value of 1; If the judgment result is negative, then the column containing the problem in the state relationship matrix of the corresponding third-generation passive pressurized water reactor nuclear power plant will have a value of 0. The state relation matrix of the third-generation passive pressurized water reactor nuclear power plant is the state interval of the third-generation passive pressurized water reactor nuclear power plant corresponding to the judgment results of all issues related to the state interval of the third-generation passive pressurized water reactor nuclear power plant. S103. Identify accident signs in third-generation passive pressurized water reactor nuclear power plants based on standardized operating signals of third-generation passive pressurized water reactor nuclear power plants. S104. Identify abnormal states of the third-generation passive pressurized water reactor nuclear power plant system based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant. S105. Identify the accident types of third-generation passive pressurized water reactor nuclear power plants based on accident symptoms and abnormal system states.
2. The online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants according to claim 1, characterized in that, In S101, the read operating signals of the third-generation passive pressurized water reactor nuclear power plant are preprocessed, including checking the validity of the read operating signals and identifying and processing abnormal signals in the read operating signals; the validity check of the read operating signals includes checking whether the signals are within the design range and checking the consistency of multiple signal channels; Identify and process abnormal signals in the read operating signals of the third-generation passive pressurized water reactor nuclear power plant, including identifying default values, abnormal values and multiple signals in the read operating signals of the third-generation passive pressurized water reactor nuclear power plant, removing default values and abnormal values in the operating signals of the third-generation passive pressurized water reactor nuclear power plant, and merging multiple signals in the read operating signals of the third-generation passive pressurized water reactor nuclear power plant.
3. The online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants according to claim 1, characterized in that, S103 includes the following steps: identifying accident signs of a third-generation passive pressurized water reactor nuclear power plant by comparing the change in the value of the operating signal of the third-generation passive pressurized water reactor nuclear power plant at the current time with that at the previous time, or by whether the value of the operating signal of the third-generation passive pressurized water reactor nuclear power plant at the current time exceeds a set threshold range.
4. The online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants according to claim 3, characterized in that, Third-generation passive pressurized water reactor nuclear power plant accident warning signs include low main system pressure, main system pressure drop, pressure vessel not malfunctioning, high containment pressure, rising containment pressure, rising sump water level, high evaporator radiation dose, high evaporator water level, rising evaporator water level, operators observing SGTR, suspected main system breach with coolant leakage (not containment), loss of AC power, low pressurizer water level, main system temperature drop, high main system pressure, high containment pressure, high containment temperature, reactor shutdown, and reactor power reduction.
5. The online accident diagnosis method for a third-generation passive pressurized water reactor nuclear power plant according to claim 1, characterized in that, S104 includes the following steps: S1041. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, determine the likelihood function variables for each problem related to the identification of abnormal states in the third-generation passive pressurized water reactor nuclear power plant system. S1042. Calculate the confidence probability of each question related to the identification of abnormal states in a third-generation passive pressurized water reactor nuclear power plant system based on the likelihood function. S1043. Based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, calculate the confidence probability of each question that is true in relation to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system. S1044. Take the arithmetic mean of the confidence probabilities of all questions related to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system to obtain the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system. S1045. Determine whether the calculation results of S1043 and S1044 meet the set confidence probability judgment conditions for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system. If the confidence probability judgment conditions for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system are met, then identify the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system. The confidence probability judgment condition for the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is as follows: the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is greater than 0.5; or the confidence probability of the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system is greater than 0.5, and the confidence probability of one or more issues related to the abnormal state of the third-generation passive pressurized water reactor nuclear power plant system being true is greater than 0.
5.
6. The online accident diagnosis method for a third-generation passive pressurized water reactor nuclear power plant according to claim 5, characterized in that, Abnormal states of third-generation passive pressurized water reactor nuclear power plant systems include charging and discharging anomalies; Issues related to identifying abnormal charging and discharging include: whether there is an indication of high-pressure injection flow rate, and whether the high-pressure injection flow rate value is close to the expected value; whether the pressure regulator water level is high or rising; whether the secondary heat sink is invalid or lost; whether there was no obvious rupture indication before; whether the main system pressure change is consistent with the high-pressure injection flow rate; and whether saturated water is found to be flowing out of the release valve. The confidence probability judgment condition for abnormal charging and discharging is: the confidence probability of abnormal charging and discharging is greater than 0.5, and the confidence probability of the first issue related to abnormal charging and discharging is greater than 0.
5.
7. The online accident diagnosis method for a third-generation passive pressurized water reactor nuclear power plant according to claim 1, characterized in that, S105 includes the following steps: The fuzzy expert knowledge base constructs a diagnostic tree for each type of accident in a third-generation passive pressurized water reactor nuclear power plant based on the diagnostic conditions for each type of accident. Based on the diagnostic tree of each type of accident in the third-generation passive pressurized water reactor nuclear power plant, determine whether each diagnostic condition of each type of accident in the third-generation passive pressurized water reactor nuclear power plant is valid, and calculate the confidence probability of each diagnostic condition of each type of accident in the third-generation passive pressurized water reactor nuclear power plant being valid. The confidence probability of each type of accident in a third-generation passive pressurized water reactor nuclear power plant is obtained by taking the arithmetic average of the confidence probabilities of all diagnostic conditions being met for each type of accident. If the confidence probability of this type of accident in a third-generation passive pressurized water reactor nuclear power plant is greater than 0.5, then the third-generation passive pressurized water reactor nuclear power plant is determined to have this type of accident. The diagnostic criteria for each type of accident in a Generation III passive pressurized water reactor (PWR) nuclear power plant include several accident symptoms and / or abnormal states of the PWR system.
8. The online accident diagnosis method for a third-generation passive pressurized water reactor nuclear power plant according to claim 7, characterized in that, Third-generation passive pressurized water reactor nuclear power plant accidents include coolant loss accidents, heat transfer tube rupture accidents, plant-wide power outage accidents, main steam pipeline rupture accidents, and unexpected shutdown accidents.
9. An online accident diagnosis system for a third-generation passive pressurized water reactor nuclear power plant, characterized in that, include: The data processing module (201) is used to preprocess the read third-generation passive pressurized water reactor nuclear power plant operation signals to obtain standardized third-generation passive pressurized water reactor nuclear power plant operation signals. The first identification module (202) is used to identify the state range of a third-generation passive pressurized water reactor nuclear power plant based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant. Specifically, it includes the following steps: judging each issue related to the state range of the third-generation passive pressurized water reactor nuclear power plant based on the standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant, and obtaining the judgment results of all issues related to the state range of the third-generation passive pressurized water reactor nuclear power plant; associating the judgment results of all issues related to the state range of the third-generation passive pressurized water reactor nuclear power plant with the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant, and obtaining the state range of the third-generation passive pressurized water reactor nuclear power plant. The judgment result for each question related to the state interval of the third-generation passive pressurized water reactor nuclear power plant is either yes or no. If the judgment result is yes, the column containing that question in the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is set to 1; if the judgment result is no, the column containing that question in the state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is set to 0. The state relationship matrix of the third-generation passive pressurized water reactor nuclear power plant is the state interval of the third-generation passive pressurized water reactor nuclear power plant corresponding to the judgment results of all questions related to the state interval of the third-generation passive pressurized water reactor nuclear power plant. The second identification module (203) is used to identify accident signs of a third-generation passive pressurized water reactor nuclear power plant based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant. The third identification module (204) is used to identify abnormal states of the third-generation passive pressurized water reactor nuclear power plant system based on standardized operating signals of the third-generation passive pressurized water reactor nuclear power plant. The fourth identification module (205) is used to identify the accident type of the third-generation passive pressurized water reactor nuclear power plant based on the accident symptoms and abnormal system states of the third-generation passive pressurized water reactor nuclear power plant. Data connection between the data processing module (201), the first identification module (202), the second identification module (203), the third identification module (204) and the fourth identification module (205).
10. A computer device comprising a memory and a processor, wherein the memory stores computer-readable instructions, characterized in that, When the processor executes the computer-readable instructions, it implements the steps of the online accident diagnosis method for a third-generation passive pressurized water reactor nuclear power plant as described in any one of claims 1-8.
11. A computer-readable storage medium storing computer-readable instructions thereon, characterized in that, When the computer-readable instructions are executed, they implement the steps of the online accident diagnosis method for third-generation passive pressurized water reactor nuclear power plants as described in any one of claims 1-8.