Nuclear power plant accident diagnosis method, device, medium and equipment

Abstract

The invention relates to a nuclear power plant accident diagnosis method, a nuclear power plant accident diagnosis device, a medium and equipment. The nuclear power plant accident diagnosis method comprises the following steps: S10, acquiring current working condition parameters and current state signals; s20, judging whether the jump signal is triggered or not according to the current state signal; step S30, if yes, acquiring historical data before jumping; and S40, analyzing the current state and the historical state of the unit in real time according to the current working condition parameters and the historical data before the unit jumps, and obtaining an accident diagnosis result. According to the invention, based on the state change of the unit after the accident, accident diagnosis is carried out by adopting the time sequence characteristics, so that the defect that the accident is diagnosed only by adopting the current state of the unit traditionally is overcome, the misdiagnosis risk is reduced, and large transient accidents immediately triggered by a protection system and the accident diagnosis of which the transient states are relatively mild can be considered. In addition, a secondary diagnosis method is adopted, so that accident types can be given as soon as possible, and specific accidents can be given through subsequent change of unit states.

Description

Technical Field

[0001] This invention relates to the technical field of nuclear power plant accident diagnosis, and more specifically, to a method, apparatus, medium, and equipment for nuclear power plant accident diagnosis. Background Technology

[0002] Nuclear power plants may experience accidents due to equipment failures, pipe ruptures, or other reasons, triggering the reactor shutdown protection system to automatically lower all control rods and stop the reactor's chain reaction. To ensure reactor safety, different system functions are needed to bring the reactor to the appropriate operating state (appropriate temperature, pressure, and boron concentration). Different causes of accidents result in different outcomes, and different accident handling requires different functionalities. Therefore, diagnosing the type and cause of an accident is crucial for selecting the appropriate accident handling strategy.

[0003] Past accident diagnosis primarily relied on the current state of the unit, including the range of current parameters and equipment operating status. For example, primary loop pressure below a certain value, containment pressure above a certain value, and containment radioactivity exceeding a defined level were used to diagnose primary loop breach accidents. However, the unit's state changes constantly after an accident. Initiating events, reactor trips, and activation of dedicated safety facilities cause even more drastic changes. Diagnosis based solely on a single point in time may lead to incorrect accident diagnosis and consequently, incorrect accident response strategies. Furthermore, for accidents with relatively minor deterioration in unit condition, some thresholds may not be breached for a considerable period after the accident, and some states may not appear until much later, causing delays in accident diagnosis and response.

[0004] To address this issue, some accident handling methods abandon diagnosing the initial cause of the accident and determine the handling strategy based on the current state of the unit. For example, cooling and pressurizing when the primary circuit saturation margin is low, and depressurizing when the primary circuit saturation margin is high. Simultaneously, to adapt to changes in the unit's state after an accident, the unit's state is monitored cyclically, and the handling strategy is continuously adjusted according to the unit's state. Because this method does not diagnose the initial cause of the accident, changes in the unit's state may lead to repeated switching between various strategies, reducing accident handling efficiency and potentially increasing the number of transient events. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method, apparatus, medium and equipment for diagnosing nuclear power plant accidents, in view of the problems existing in the prior art.

[0006] The technical solution adopted by this invention to solve its technical problem is: to construct a method for diagnosing nuclear power plant accidents, comprising the following steps: Step S10: Obtain the current operating parameters and current status signals of the unit; Step S20: Determine whether the current status signal is triggered by a heap skipping signal; Step S30: If yes, obtain historical data of the unit before the reactor skipping; Step S40: Analyze the current and historical status of the unit in real time based on the current operating parameters and the historical data before the unit trips, and obtain the accident diagnosis results.

[0007] In the nuclear power plant accident diagnosis method of the present invention, step S40, which involves real-time analysis of the current and historical states of the unit based on the current operating parameters and the historical data before the unit trips, to obtain the accident diagnosis result, includes: Based on the current operating parameters, the historical data before the unit tripped, and the current status signal, the accident diagnosis logic judgment conditions are obtained through analysis and calculation. The current and historical states of the unit are analyzed based on the accident diagnosis logic judgment conditions to obtain the accident diagnosis results.

[0008] In the nuclear power plant accident diagnosis method described in this invention, the accident diagnosis logic judgment conditions include: the first reactor trip signal, the trend or maximum value of important parameters before reactor trip, the current protection signal trigger signal, the trend and historical maximum value of important parameters in the sliding window, and the set status. The process of analyzing the current and historical states of the unit based on the accident diagnosis logic judgment conditions to obtain the accident diagnosis results includes: If the accident diagnosis logic judgment conditions satisfy any one or more of the following: the first-out-of-stack signal, the trend or extreme value of the important parameter before the stack jump, the current protection signal trigger signal, the trend of the sliding window parameter, the historical extreme value, and the set state, then the accident diagnosis result is generated based on the logic calculation result.

[0009] In the nuclear power plant accident diagnosis method of the present invention, the step of analyzing and calculating the current operating parameters, the historical data before the unit trip, and the current state signal to obtain the accident diagnosis logic judgment conditions includes: Determine whether the corresponding first-out jump signal has been received; If so, then the accident diagnosis logic judgment condition of the first out-of-stack signal is satisfied.

[0010] In the nuclear power plant accident diagnosis method of the present invention, the step of analyzing and calculating the current operating parameters, the historical data before the unit trip, and the current state signal to obtain the accident diagnosis logic judgment conditions includes: Based on the historical data of the unit before the reactor trip, the parameter trend or the parameter maximum value of a certain period before the reactor trip is calculated to obtain the trend calculation result and the maximum value calculation result before the reactor trip. Determine whether the trend threshold or the extreme value threshold is met based on the trend calculation result before the heap jump and the extreme value calculation result before the heap jump. If the trend threshold or the extreme value threshold is met, then it is determined that the important parameter before the heap jump is satisfied.

[0011] In the nuclear power plant accident diagnosis method described in this invention, the pre-trip trend calculation result is obtained through the following calculation method: Obtain the values ​​of the target parameters within a preset time period before heap jumping; The sampling data is determined based on the data sampling interval and the preset time period; The slope of the sampled data was calculated using a linear regression method to obtain the sampling slope. The trend calculation result is determined based on the sampling slope.

[0012] In the nuclear power plant accident diagnosis method described in this invention, the pre-trip maximum / minimum value calculation result is obtained through the following calculation method: Obtain the values ​​of the target parameters within a preset time period; The sampling data is determined based on the data sampling interval and the preset time period; The sampled data is arranged to obtain arranged data, and the maximum and minimum values ​​before heap skipping are determined based on the arranged data.

[0013] In the nuclear power plant accident diagnosis method of the present invention, the sorted data includes: first ascending order data; The results of the extreme value calculation before heap skipping include: the maximum value calculation result; The step of arranging the sampled data to obtain arranged data, and determining the calculation result of the maximum and minimum values ​​before heap skipping based on the arranged data, includes: The sampled data are arranged in descending order to obtain the first ascending data; Calculate the mean of the first a data points in the first ascending data to obtain the first calculated mean; The maximum value is determined based on the first calculated mean.

[0014] In the nuclear power plant accident diagnosis method of the present invention, the sorted data includes: first descending order data; The results of the extreme value calculation before heap skipping include: the minimum value calculation results; The step of arranging the sampled data to obtain arranged data, and determining the calculation result of the maximum and minimum values ​​before heap skipping based on the arranged data, includes: The sampled data are arranged in ascending order to obtain the first descending data; Calculate the mean of the first a data points in the first descending data to obtain the second calculated mean; The minimum value calculation result is determined based on the second calculated mean.

[0015] In the nuclear power plant accident diagnosis method of the present invention, the step of analyzing and calculating the current operating parameters, the historical data before the unit trip, and the current state signal to obtain the accident diagnosis logic judgment conditions includes: Based on the current operating condition parameters, calculate the parameter trend at the current moment or the parameter maximum and minimum values ​​over a previous period to obtain the sliding trend calculation results and historical maximum and minimum value calculation results; Determine whether the trend threshold or the extreme value threshold is met based on the sliding trend calculation result and the historical maximum / minimum value calculation result; If the trend threshold or the extreme value threshold is met, then it is determined that the important parameter sliding window trend and historical extreme value are satisfied.

[0016] In the nuclear power plant accident diagnosis method described in this invention, the slip trend calculation result is obtained through the following calculation method: Get the values ​​of the target parameters within a preset time period before the current time; The sampling data is determined based on the data sampling interval and the preset time period; The slope of the sampled data was calculated using a linear regression method to obtain the sampling slope. The sliding trend calculation result is determined based on the sampling slope.

[0017] In the nuclear power plant accident diagnosis method described in this invention, the historical extreme value calculation result is obtained through the following calculation method: Obtain the values ​​of the target parameters from the current moment to a certain historical moment; The sampling data is determined based on the data sampling interval and the time span from the current moment to the historical moment; The sampled data is arranged to obtain arranged data, and the historical extreme value calculation result is determined based on the arranged data.

[0018] The sorted data includes: second ascending order data; The step of arranging the sampled data to obtain arranged data, and determining the historical extreme value calculation result based on the arranged data, includes: The sampled data are arranged in descending order to obtain the second ascending data; Calculate the mean of the first a data points in the second ascending data to obtain the third calculated mean; The historical extreme value calculation result is determined based on the third calculated mean.

[0019] In the nuclear power plant accident diagnosis method of the present invention, the sorting data includes: second descending order data; The step of arranging the sampled data to obtain arranged data, and determining the historical extreme value calculation result based on the arranged data, includes: The sampled data are arranged in ascending order to obtain the second descending order data; The mean of the first a data points in the second descending data is calculated to obtain the fourth calculated mean. The historical extreme value calculation result is determined based on the fourth calculated mean.

[0020] In the nuclear power plant accident diagnosis method described in this invention, the following steps are included after step S40: Step S50: Determine whether a secondary diagnosis is needed for the accident diagnosis results. If not, end the accident diagnosis. Step S60: If so, continue to analyze the current and historical status of the unit in real time to obtain the cause of the accident.

[0021] The present invention also provides a nuclear power plant accident diagnosis device, comprising: The data signal acquisition unit is used to acquire the current operating parameters and current status signals of the unit; The logic detection unit is used to determine whether the heap skipping signal is triggered based on the current state signal; The historical data acquisition unit is used to acquire historical data of the unit before the reactor skipping process; The accident diagnosis unit is used to analyze the current and historical states of the unit in real time based on the current operating parameters and the historical data before the unit tripped, and to obtain the accident diagnosis results.

[0022] In the nuclear power plant accident diagnosis device of the present invention, the accident diagnosis unit includes: The first logic calculation module is used to analyze and calculate based on the current operating parameters, the historical data of the unit before the trip, and the current status signal to obtain the accident diagnosis logic judgment conditions. The current and historical states of the unit are analyzed based on the accident diagnosis logic judgment conditions to obtain the accident diagnosis results.

[0023] In the nuclear power plant accident diagnosis device of the present invention, the first logic calculation module includes: a first OR gate, a first NOT gate, a second OR gate, a third OR gate, a second NOT gate, a third NOT gate, and a first AND gate; The first input terminal of the first OR gate is connected to the important parameter trend or extreme value before the heap jump, the second input terminal of the first OR gate is connected to the important parameter sliding window trend and historical extreme value, and the output terminal of the first OR gate is connected to the first input terminal of the first AND gate through the first NOT gate. The first input terminal of the second OR gate is connected to the important parameter trend or maximum / minimum value before the stack jump, the second input terminal of the second OR gate is connected to the current protection signal trigger signal, and the output terminal of the second OR gate is connected to the second input terminal of the first AND gate. The first and second input terminals of the third OR gate are connected to the first output jump signal, and the output terminal of the third OR gate is connected to the third input terminal of the first AND gate; the input terminal of the second NOT gate is connected to the setting state, and the output terminal of the second NOT gate is connected to the fourth input terminal of the first AND gate; the input terminal of the third NOT gate is connected to the setting state, and the output terminal of the third NOT gate is connected to the fifth input terminal of the first AND gate; the output terminal of the first AND gate outputs the accident diagnosis result.

[0024] The nuclear power plant accident diagnosis device described in this invention also includes: The second logic calculation module has a first input terminal connected to the output terminal of the first logic calculation module, a second input terminal connected to the current protection signal trigger signal, a third input terminal connected to the secondary diagnosis trigger signal associated with the accident diagnosis result, and an output terminal outputting the accident cause of the accident diagnosis result.

[0025] The present invention also provides a storage medium storing a computer program adapted for loading by a processor to perform the steps of the nuclear power plant accident diagnosis method as described above.

[0026] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps of the nuclear power plant accident diagnosis method as described above by calling the computer program stored in the memory.

[0027] The nuclear power plant accident diagnosis method, apparatus, medium, and equipment of the present invention have the following beneficial effects: The method includes the following steps: Step S10: Acquire the current operating parameters and current status signal of the unit; Step S20: Determine whether a reactor trip signal has been triggered based on the current status signal; Step S30: If so, acquire historical data of the unit before the reactor trip; Step S40: Analyze the current and historical states of the unit in real time based on the current operating parameters and the historical data of the unit before the reactor trip to obtain the accident diagnosis result. The present invention, based on the changes in the unit's state after an accident, uses time-series characteristics for accident diagnosis, overcoming the shortcomings of traditional methods that only use the current state of the unit for accident diagnosis, reducing the risk of misdiagnosis, and can address both large transient accidents that immediately trigger the protection system and those with relatively mild transients. Furthermore, the present invention employs a secondary diagnosis method, which can provide the accident category early and also provide the specific accident based on subsequent changes in the unit's state. Attached Figure Description

[0028] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart illustrating an embodiment of the nuclear power plant accident diagnosis method provided by the present invention; Figure 2 This is a flowchart illustrating Embodiment 2 of the nuclear power plant accident diagnosis method provided by the present invention; Figure 3 This is the diagnostic logic diagram for external ruptures in the steam pipeline shell of a steam generator provided by the present invention; Figure 4 This is the logic diagram for diagnosing the upstream rupture of the isolation valve on the main steam pipeline outside the containment provided by the present invention; Figure 5 This is the logic diagram for diagnosing the downstream rupture of the isolation valve on the main steam pipeline outside the containment provided by the present invention; Figure 6 This is a flowchart illustrating the implementation of the nuclear power plant accident diagnosis method provided by the present invention; Figure 7 This is a logic block diagram of the nuclear power plant accident diagnosis device provided by the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] To address the shortcomings of traditional nuclear power plant accident diagnosis methods, this invention provides a more optimized nuclear power plant accident diagnosis method. This method combines the past and current status of the unit with parameter evolution trends to accurately and promptly diagnose accidents, thereby facilitating the selection of more appropriate handling strategies.

[0031] In a preferred embodiment, such as Figure 1 As shown, the nuclear power plant accident diagnosis method includes the following steps: Step S10: Obtain the current operating parameters and current status signals of the unit.

[0032] Specifically, in this embodiment of the invention, the current operating condition parameters of the unit are the monitoring parameters of the unit's current real-time status (i.e., the parameters required for diagnosis acquired in real-time online). The current status refers to the real-time status of the unit, equipment, and / or system. The current operating condition parameters are selected based on the characteristics of typical nuclear power plant accidents, analyzing the unit parameters affected by the accident requiring diagnosis, and then selecting the necessary diagnostic parameters (i.e., the current operating condition parameters). For example, the parameters required for diagnosing a primary coolant loss accident include: containment pressure, containment radioactivity, and pressurizer pressure; the parameters required for diagnosing a secondary containment breach accident include: steam generator pressure, steam generator water level, and containment pressure; the parameters required for diagnosing a steam generator heat transfer tube rupture accident include: steam generator water level, steam generator pressure, and steam generator radioactivity, etc.

[0033] The current status signals mainly monitor whether reactor protection signals are triggered, including but not limited to: reactor trip signal, safety injection signal, emergency feedwater triggering of steam generator, containment isolation, main steam line isolation, main feedwater line isolation, main pump automatic shutdown signal, chemical and liquid system leakage isolation signal, etc.

[0034] Step S20: Determine whether the heap skipping signal is triggered based on the current status signal.

[0035] In this embodiment of the invention, the reactor trip signal is used as the trigger point for accident diagnosis. Specifically, after a reactor trip signal is detected in real time, the accident diagnosis logic judgment begins, i.e., step S30 is executed, and continues until the operator's grace period designed by the nuclear power plant expires (for example, the grace period of a certain nuclear power plant is 30 minutes after the first important information is transmitted to the operator, which can be approximated as 30 minutes after the reactor trip signal is triggered) or the operator's first intervention command has been issued. The termination condition for accident diagnosis in this invention is selected considering that the diagnosis must be completed within the grace period, and that the operator's intervention will change the state and trend of the unit caused by the initiating event.

[0036] Step S30: If yes, obtain the historical data of the unit before the reactor skipping.

[0037] Specifically, in this embodiment of the invention, the historical data before the unit trips is the same type of parameter as the current operating condition parameter, and is the data of the unit under the historical state.

[0038] Step S40: Analyze the current and historical status of the unit in real time based on the current operating parameters and historical data before the unit trips, and obtain the accident diagnosis results.

[0039] Optionally, in step S40, the real-time analysis of the unit's current and historical states based on current operating parameters and historical data before the unit trips to obtain accident diagnosis results includes: analyzing and calculating based on current operating parameters, historical data before the unit trips, and current state signals to obtain accident diagnosis logic judgment conditions; and analyzing the unit's current and historical states based on the accident diagnosis logic judgment conditions to obtain accident diagnosis results. Preferably, the accident diagnosis logic judgment conditions include: the first trip signal, the trend or maximum / minimum value of important parameters before the trip, the current protection signal trigger signal, the trend and historical maximum / minimum value of the important parameter sliding window, and the set state.

[0040] Specifically, based on the accident diagnosis logic judgment conditions, the current and historical states of the unit are analyzed to obtain the accident diagnosis results. These results include: if any one or more of the following conditions are met: first-time trip signal, trend or extreme value of important parameters before tripping, current protection signal trigger signal, trend and historical extreme value of important parameters within the sliding window, and set state, then the accident diagnosis result is generated based on the logical calculation results. In other words, if any one or more of the following five categories of conditions are met, the corresponding accident can be diagnosed (at least the accident category can be determined): first-time trip signal, trend or extreme value of important parameters before tripping, current protection signal trigger signal, trend and historical extreme value of important parameters within the sliding window, and set state (including any one or more of equipment state, system state, and unit state).

[0041] In this embodiment of the invention, the accident diagnosis logic judgment conditions are obtained by analyzing and calculating the current operating parameters, historical data before the unit trip, and current status signals. These conditions include: determining whether a corresponding first-out trip signal has been received; if so, the accident diagnosis logic judgment conditions for the first-out trip signal are met. Specifically, there are many signals for reactor tripping, such as low primary loop pressure tripping, high steam pressure drop tripping, and high neutron energy change rate tripping within the reactor power range. Tripping itself usually causes unit transients and can also lead to other tripping signals. For example, a low primary loop pressure tripping signal causes the control rods to fall directly to the reactor bottom, resulting in a rapid decrease in reactor power and a high neutron change rate, which in turn generates a high neutron energy change rate tripping signal within the power range. Since the nuclear power plant protection system provides a first-out tripping signal display, this invention can utilize this display to determine the current first-out tripping signal and thus determine whether it meets the accident diagnosis logic judgment conditions for the first-out tripping signal. Based on the first-out tripping signal, the parameters and direction of change that initially caused the tripping can be determined. When a reactor trip signal is triggered, the nuclear power plant's protection system automatically records the first signal that caused the trip (i.e., the first trip signal). For example, low temperature or low pressure in the primary loop of the nuclear power plant can trigger a trip. During a trip, the protection system records whether the signal that triggered the trip was low temperature or low pressure. (The unit's state changes after a trip, so while the operator may be observing, the primary loop temperature and pressure may already be below the trip threshold, but the specific signal causing the trip can be traced back to the protection system.) Figure 3 As shown, the first-out reactor trip signal condition is met when either the SG pressure is low (RT) or the SG pressure drop is high (RT). Here, SG represents the steam generator, and RT represents the reactor trip.

[0042] In this embodiment of the invention, the analysis and calculation based on current operating parameters, historical data before unit tripping, and current status signals yields the following accident diagnosis logic judgment conditions: 1) Calculating the parameter trend or parameter extrema over a period before tripping based on historical data before tripping, obtaining the trend calculation result and the extrema calculation result; 2) Determining whether the trend threshold or extrema threshold is met based on the trend calculation result and the extrema calculation result; 3) If the trend threshold or extrema threshold is met, then the condition for the important parameter trend or extrema before tripping is satisfied. That is, for the important parameter trend or extrema before tripping, the main consideration is the parameter trend or parameter extrema within a period before tripping. This is for accidents with relatively minor severity and relatively mild changes in unit status. For example, a breach in the secondary containment loop of a nuclear power plant will release mass energy into the containment, causing an increase in containment pressure. However, for smaller breaches, the containment pressure may not rise to the protection system's activation threshold. Moreover, as the temperature and pressure in the primary loop decrease after reactor shutdown, the containment pressure will decrease after reaching its peak. Simply using a single containment pressure threshold cannot diagnose a breach accident within the containment loop. Therefore, the trend or extreme value of the containment pressure increase before reactor tripping can be used to determine whether a containment pressure increase has occurred.

[0043] The trend of important parameters before heap jumping is calculated using the following method: The values ​​of the target parameters within a preset time period before heap jumping are obtained; the sampled data is determined based on the data sampling interval and the preset time period; the slope of the sampled data is calculated using a linear regression method to obtain the sampling slope; and the trend calculation result is determined based on the sampling slope. Specifically, the calculation method for the trend of important parameters before heap jumping is as follows: The values ​​of the target parameters within n seconds before heap jumping are traced back, with a data sampling interval of m seconds, resulting in n / m values. The slope of these n / m values ​​is calculated using a linear regression method. If the slope is greater than 0 (or greater than a positive number close to 0), the trend calculation result of the target parameter is considered to be increasing; otherwise, the trend calculation result of the target parameter is considered to be not increasing. The same applies to the algorithm for determining a decrease.

[0044] The calculation results of the critical parameter's maximum and minimum values ​​before heap jump are obtained through the following methods: acquiring the target parameter values ​​within a preset time period; determining the sampled data based on the data sampling interval and the preset time period; arranging the sampled data to obtain the arranged data, and determining the maximum and minimum values ​​before heap jump based on the arranged data. The arrangement of the sampled data can be either ascending or descending order. Specifically, the arranged data includes: first ascending data; the maximum and minimum values ​​before heap jump calculation results include: arranging the sampled data from largest to smallest to obtain first ascending data; calculating the mean of the first *a* data points in the first ascending data to obtain a first calculated mean; and determining the maximum value calculation result based on the first calculated mean. Alternatively, the data arrangement includes: first descending order data; the result of calculating the maximum and minimum values ​​before heap jumps includes: the result of calculating the minimum value; arranging the sampled data to obtain the arranged data, and determining the result of calculating the maximum and minimum values ​​before heap jumps based on the arranged data includes: arranging the sampled data in ascending order to obtain first descending order data; calculating the mean of the first a data in the first descending order data to obtain a second calculated mean; and determining the result of calculating the minimum value based on the second calculated mean.

[0045] The following explanation uses ascending order as an example. Specifically, it involves: arranging the sampled data from largest to smallest to obtain the sorted data; calculating the mean of the first *a* data points in the sorted data to obtain the mean of the maximum values ​​(i.e., the first calculated mean); determining the maximum value calculation result based on the mean of the maximum values; the algorithm for calculating the minimum value is similar. Specifically, it involves tracing the values ​​of the target parameter within *n* seconds before the stack jump, with a data sampling interval of *m* seconds, obtaining *n / m* values. The mean of the first *a* maximum values ​​of these *n / m* values ​​is taken. If this mean is *p%* higher than the historical mean of the target parameter during normal unit operation, then the calculated result of the maximum value of the important parameter before the stack jump is considered to have increased or had previously increased. The algorithm for determining whether it has decreased or had previously decreased is similar.

[0046] In this embodiment of the invention, the current status signal refers to an automatic signal designed by the reactor protection system to mitigate accidents. These typically include safety injection signals, emergency feedwater triggering of the steam generator, containment isolation, main steam line isolation, main feedwater line isolation, and automatic shutdown signals of the main pumps. Different accident conditions may trigger different protection signals; therefore, the triggering status of protection signals (i.e., the current protection signal triggering signal) can be used to diagnose the accident category. For example, a secondary side rupture in the steam generator will cause a decrease in steam generator pressure. If the pressure reaches a low threshold, a main steam isolation signal will be triggered. Therefore, if the main steam isolation signal is triggered, it indicates a possible secondary side rupture accident in the steam generator. This condition can be combined with other conditions to confirm a secondary side rupture accident in the steam generator.

[0047] In this embodiment of the invention, the accident diagnosis logic judgment conditions are obtained by analyzing and calculating the current operating parameters, historical data before the unit trip, and current status signals. These conditions include: calculating the parameter trend at the current moment or the parameter maximum / minimum value over a previous period based on the current operating parameters, obtaining the sliding trend calculation result and the historical maximum / minimum value calculation result; determining whether the trend threshold or maximum / minimum value threshold is met based on the sliding trend calculation result and the historical maximum / minimum value calculation result; and determining whether the important parameter sliding window trend and historical maximum / minimum value conditions are met if the trend threshold or maximum / minimum value threshold is met. That is, for the important parameter sliding window trend and historical maximum / minimum value, the current parameter trend or the parameter maximum / minimum value over a previous period is mainly considered. This accident diagnosis logic judgment condition is generally used for accidents of relatively minor severity and relatively mild changes in unit status, where some protection signal thresholds have not been triggered. In such cases, parameter trends can be used to diagnose the accident. For example, a secondary side rupture in the steam generator will cause a decrease in steam generator pressure. If the pressure has not reached the low threshold and the main steam isolation signal has not been triggered, the steam generator pressure decrease trend can be used to diagnose the accident as early as possible.

[0048] The sliding trend result of the sliding window parameter trend is obtained by the following calculation method: obtain the value of the target parameter within the preset time period before the current time; determine the sampled data according to the data sampling interval and the preset time period; use the linear regression method to calculate the slope of the sampled data to obtain the sampling slope; and determine the sliding trend calculation result according to the sampling slope.

[0049] The specific calculation method is as follows: trace the value of the target parameter in the n seconds before the current time. The data sampling interval is m seconds, and n / m values ​​are obtained. Use the linear regression method to find the slope of these n / m values. If the slope is greater than 0 (or greater than a positive number close to 0), the target parameter is considered to have increased; otherwise, it is considered not to have increased. The same applies to the algorithm for judging the decrease.

[0050] The historical extreme values ​​of the sliding window parameters are calculated using the following method: Obtain the target parameter values ​​from the current time to a specific historical time; determine the sampled data based on the data sampling interval and the time span from the current time to the historical time; arrange the sampled data to obtain the arranged data, and determine the historical extreme value calculation result based on the arranged data. The sampled data can be arranged in ascending or descending order. Specifically, the arranged data includes: second ascending data; the process of arranging the sampled data to obtain the arranged data and determining the historical extreme value calculation result based on the arranged data includes: arranging the sampled data from largest to smallest to obtain second ascending data; calculating the mean of the first 'a' data points in the second ascending data to obtain a third calculated mean; and determining the historical extreme value calculation result based on the third calculated mean. Alternatively, the arrangement of data includes: second descending order data; arranging the sampled data to obtain the arrangement data, and determining the historical extreme value calculation result based on the arrangement data includes: arranging the sampled data in ascending order to obtain second descending order data; calculating the mean of the first a data in the second descending order data to obtain the fourth calculated mean; and determining the historical extreme value calculation result based on the fourth calculated mean.

[0051] The following explanation uses ascending order as an example. Specifically, it includes: arranging the sampled data from largest to smallest to obtain the sorted data; calculating the mean of the first *a* data points in the sorted data to obtain the mean of the maximum values; and determining the historical maximum value based on the mean of the maximum values ​​(i.e., the third calculated mean). The method for calculating the historical minimum value is similar. Specifically, it involves tracing back from the current time *t* to a certain historical time *t*. n The values ​​of specific parameters are obtained, with a data sampling interval of m seconds, and (tt) n For each of the m values, the average of the first a maximum values ​​is calculated. If this average is p% higher than the historical average of the target parameter during normal unit operation, it is considered to have increased or previously increased. The same algorithm is used to determine whether it has decreased or previously decreased. This invention, through the calculation of the judgment conditions of this accident diagnosis logic, can avoid the immediate period after a reactor trip. This is because many parameters change rapidly in the short period after a reactor trip, such as a sharp drop in primary loop temperature and pressure, and a rise in evaporator pressure. These rapid changes can mask the trend of parameter changes caused by the initial event.

[0052] This invention considers the changes in the unit's state after an accident and uses time-series characteristics for accident diagnosis, which makes up for the shortcomings of traditional methods that only use the current state of the unit to diagnose accidents and reduces the risk of misdiagnosis.

[0053] refer to Figure 2 The nuclear power plant accident diagnosis method provided by the present invention further includes the following steps after step S40: Step S50: Determine whether a secondary diagnosis of the accident diagnosis results is required. If not, end the accident diagnosis. Step S60: If so, continue to analyze the current and historical status of the unit in real time to obtain the cause of the accident.

[0054] Specifically, after the accident diagnosis logic is executed and a diagnosis result is given, monitoring continues until the operator's grace period designed for the nuclear power plant is reached or the operator issues the first intervention command, at which point monitoring stops. Therefore, during continuous monitoring, since some accidents have not yet developed to a certain extent and their initial causes cannot be fully diagnosed, this invention can diagnose the accident category based on the current and historical states. As the accident progresses, a secondary diagnosis is performed to provide the specific cause of the accident under that category. By employing a secondary diagnosis method, the accident category can be given early, and the specific accident can be identified based on subsequent changes in the unit's status. For example, in a containment steam generator steam line rupture accident, if the rupture is small, the main steam isolation (MSLI) signal appears relatively late after the reactor trip. The rupture can be determined based on the current unit status and parameter trends before and after the trip, but the exact location of the rupture cannot be determined. See [link to relevant documentation]. Figure 3 The diagnostic logic uses red to represent pre-heap jump parameter trend conditions and green to represent sliding window trend conditions. Specifically, for example... Figure 3 As shown, low SG pressure RT and high SG pressure drop RT are the first reactor trip signals. Increased containment pressure (red) and at least 1SG pressure drop are the trends or extreme values ​​of important parameters before the reactor trip. MSLI is the current protection system trigger signal. Increased containment pressure (green) is the trend and historical extreme value of the sliding window of important parameters. All main pumps stopped and SG has radioactivity are the set states. MSLI indicates the isolation of the main steam pipeline.

[0055] When the steam generator pressure continues to drop to the MSLI isolation pressure threshold, the MSLI signal isolates the faulty steam generator. If the rupture is upstream of the main steam isolation valve, the pressure of the non-faulty steam generators will rise, leading to an increase in the pressure difference between the faulty and non-faulty steam generators. Conversely, all steam generator pressures will rise. The location of the rupture can be diagnosed based on these two conditions. See below. Figure 4 and Figure 5 The specific implementation process of the nuclear power plant accident diagnosis method of the present invention is as follows: Figure 6 As shown. It should be noted that the secondary diagnosis is based on the result of the primary diagnosis, and the results of both diagnoses will be presented to the user simultaneously. If the accident diagnosis conditions are not met, no result will be given.

[0056] It should be noted that, Figures 3-5 This example illustrates a specific accident involving a rupture in the steam pipeline shell of a steam generator. For other accidents, the operating parameters are selected according to the accident category.

[0057] refer to Figure 7The present invention also provides a nuclear power plant accident diagnosis device.

[0058] like Figure 7 As shown, the nuclear power plant accident diagnosis device includes: The data signal acquisition unit 701 is used to acquire the current operating parameters and current status signals of the unit.

[0059] The logic detection unit 702 is used to determine whether the heap skipping signal is triggered based on the current status signal.

[0060] Historical data acquisition unit 703 is used to acquire historical data of the unit before the reactor skipping.

[0061] The accident diagnosis unit 704 is used to analyze the current and historical status of the unit in real time based on the current operating parameters and historical data before the unit trips, and to obtain the accident diagnosis results.

[0062] Preferably, in this embodiment of the invention, the accident diagnosis unit 704 includes: a first logic calculation module, used to analyze and calculate based on current operating parameters, historical data before unit tripping, and current state signals to obtain accident diagnosis logic judgment conditions; and to analyze the current and historical states of the unit based on the accident diagnosis logic judgment conditions to obtain accident diagnosis results. The first logic calculation module includes: a first OR gate (e.g., ... Figure 3 OR1 in the first NOT gate (e.g.) Figure 3 NOT1 in the second OR gate (such as NOT1 in the second OR gate) Figure 3 OR2 in the middle), third OR gate (such as Figure 3 OR3 in the second NOT gate (e.g.) Figure 3 NOT2 in the middle), third NOT gate (such as Figure 3 NOT3 in the middle) and the first AND gate (such as Figure 3 AND1 in the middle.

[0063] In this configuration, the first input of the first OR gate is connected to the trend or maximum / minimum value of the critical parameter before the recirculation jump; the second input of the first OR gate is connected to the trend and historical maximum / minimum value signals of the critical parameter sliding window; and the output of the first OR gate is connected to the first input of the first AND gate via the first NOT gate. The first input of the second OR gate is connected to the trend or maximum / minimum value of the critical parameter before the recirculation jump; the second input of the second OR gate is connected to the current protection signal trigger signal; and the output of the second OR gate is connected to the second input of the first AND gate. The first and second inputs of the third OR gate are connected to the first-out recirculation jump signal; and the output of the third OR gate is connected to the third input of the first AND gate. The input of the second NOT gate is connected to the setting state; and the output of the second NOT gate is connected to the fourth input of the first AND gate. The input of the third NOT gate is connected to the setting state; and the output of the third NOT gate is connected to the fifth input of the first AND gate. The output of the first AND gate outputs the fault diagnosis result.

[0064] Furthermore, the nuclear power plant accident diagnosis device also includes: a second logic calculation module 705, the first input terminal of which is connected to the output terminal of the first logic calculation module, the second input terminal of which is connected to the current protection signal trigger signal, the third input terminal of which is connected to the secondary diagnosis trigger signal associated with the accident diagnosis result, and the output terminal of the second logic calculation module 705 outputting the accident cause of the accident diagnosis result. The second logic calculation module 705 includes: a second AND gate (such as...). Figure 4 AND2 and third AND gates (such as AND2) and third AND gates (such as AND2) Figure 5 AND3 in the middle.

[0065] It should be noted that the type, level and number of logic gates (such as AND gates, NOT gates, OR gates, etc.) used in the accident diagnosis unit 704 and the second logic calculation module 705 provided by the present invention are only illustrative examples, that is, only one type of accident, and will be different for different accident types.

[0066] Specifically, the specific operational procedures between the various units in the nuclear power plant accident diagnosis device can be found in the aforementioned nuclear power plant accident diagnosis method, and will not be repeated here.

[0067] Specifically, when no accident occurs, the nuclear power plant accident diagnosis device of this invention collects important parameters required for nuclear power plant diagnosis in real time and stores time-series data for a sufficient duration. Simultaneously, it monitors for reactor trip signals. Once a reactor trip signal is detected, the device initiates accident diagnosis logic calculations and judgments, calculating the required historical trends and extreme values, continuously calculating the required sliding time window trends and extreme values, extracting the first reactor trip signal, monitoring protection system action signals and determining corresponding conditions, and performing logic calculations. Once the corresponding accident diagnosis logic calculation result is true, the diagnosis result is output. When the diagnosis stop condition is met (i.e., triggered by operator manual action or the grace period after a reactor trip), the diagnosis system automatically stops.

[0068] This invention takes into account the changes in the unit's state after an accident and uses time-series characteristics for accident diagnosis, which makes up for the shortcomings of previous methods that only used the current state of the unit to diagnose accidents, reduces the risk of misdiagnosis, and can take into account both large transient accidents that trigger the protection system immediately and those accidents with relatively mild transients. In addition, the use of a secondary diagnosis method can give the accident category as early as possible, and can also give the specific accident based on the subsequent changes in the unit's state.

[0069] Furthermore, an electronic device of the present invention includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program to implement the nuclear power plant accident diagnosis method as described above. Specifically, according to embodiments of the present invention, the processes described above with reference to the flowchart can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, when the computer program is downloaded, installed, and executed by an electronic device, it performs the functions defined above in the methods of the embodiments of the present invention. The electronic device in the present invention can be a terminal such as a laptop, desktop computer, tablet computer, or smartphone, or it can be a server.

[0070] Furthermore, one type of storage medium of the present invention stores a computer program thereon, which, when executed by a processor, implements the nuclear power plant accident diagnosis method described above. Specifically, it should be noted that the storage medium described above in the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein computer-readable program code is carried. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0071] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0072] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0073] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0074] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0075] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They do not limit the scope of protection of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should fall within the scope of the claims of the present invention.

Claims

1. A method for diagnosing nuclear power plant accidents, characterized in that, Includes the following steps: Step S10: Obtain the current operating parameters and current status signals of the unit; Step S20: Determine whether the heap skipping signal is triggered based on the current state signal; Step S30: If yes, obtain historical data of the unit before the reactor skipping; Step S40: Analyze the current and historical status of the unit in real time based on the current operating parameters and the historical data before the unit trips, and obtain the accident diagnosis results.

2. The nuclear power plant accident diagnosis method according to claim 1, characterized in that, In step S40, the current and historical states of the unit are analyzed in real time based on the current operating parameters and the historical data before the unit trips, and the accident diagnosis results are obtained, including: Based on the current operating parameters, the historical data before the unit tripped, and the current status signal, the accident diagnosis logic judgment conditions are obtained through analysis and calculation. The current and historical states of the unit are analyzed based on the accident diagnosis logic judgment conditions to obtain the accident diagnosis results.

3. The nuclear power plant accident diagnosis method according to claim 2, characterized in that, The accident diagnosis logic judgment conditions include: the first trip signal, the trend or extreme value of important parameters before trip, the current protection system trigger signal, the trend and historical extreme value of important parameters in the sliding window, and the set status. The process of analyzing the current and historical states of the unit based on the accident diagnosis logic judgment conditions to obtain the accident diagnosis results includes: If the accident diagnosis logic judgment conditions satisfy any one or more of the following: the first-out-of-stack signal, the trend or extreme value of the important parameter before the stack jump, the current protection signal trigger signal, the trend of the important parameter sliding window, the historical extreme value, and the set state, then the accident diagnosis result is generated based on the logic calculation result.

4. The nuclear power plant accident diagnosis method according to claim 3, characterized in that, The step of analyzing and calculating based on the current operating parameters, historical data before the unit trip, and the current status signal to obtain the accident diagnosis logic judgment conditions includes: Determine whether the corresponding first-out jump signal has been received; If so, then the accident diagnosis logic judgment condition of the first out-of-stack signal is satisfied.

5. The nuclear power plant accident diagnosis method according to claim 3, characterized in that, The step of analyzing and calculating based on the current operating parameters, historical data before the unit trip, and the current status signal to obtain the accident diagnosis logic judgment conditions includes: Based on the historical data of the unit before the reactor trip, the parameter trend or the parameter maximum value of a certain period before the reactor trip is calculated to obtain the trend calculation result and the maximum value calculation result before the reactor trip. Determine whether the trend threshold or the extreme value threshold is met based on the trend calculation result before the heap jump and the extreme value calculation result before the heap jump. If the trend threshold or the extreme value threshold is met, then it is determined that the important parameter before the heap jump is satisfied.

6. The nuclear power plant accident diagnosis method according to claim 5, characterized in that, The pre-jump trend calculation result is obtained through the following calculation method: Obtain the values ​​of the target parameters within a preset time period before heap jumping; The sampling data is determined based on the data sampling interval and the preset time period; The slope of the sampled data was calculated using a linear regression method to obtain the sampling slope. The trend calculation result is determined based on the sampling slope.

7. The nuclear power plant accident diagnosis method according to claim 5, characterized in that, The result of the maximum / minimum value calculation before heap skipping was obtained by the following calculation method: Obtain the values ​​of the target parameters within a preset time period before heap jumping; The sampling data is determined based on the data sampling interval and the preset time period; The sampled data is arranged to obtain arranged data, and the maximum and minimum values ​​before heap skipping are determined based on the arranged data.

8. The nuclear power plant accident diagnosis method according to claim 7, characterized in that, The sorted data includes: first ascending order data; the maximum / minimum value calculation result before heap skipping includes: maximum value calculation result; The step of arranging the sampled data to obtain arranged data, and determining the maximum / minimum value calculation result before heap skipping based on the arranged data, includes: The sampled data are arranged in descending order to obtain the first ascending data; Calculate the mean of the first a data points in the first ascending data to obtain the first calculated mean; The maximum value is determined based on the first calculated mean.

9. The nuclear power plant accident diagnosis method according to claim 7, characterized in that, The sorted data includes: first descending order data; The results of the extreme value calculation before heap skipping include: the minimum value calculation results; The step of arranging the sampled data to obtain arranged data, and determining the maximum / minimum value calculation result before heap skipping based on the arranged data, includes: The sampled data are arranged in ascending order to obtain the first descending data; Calculate the mean of the first a data points in the first descending data to obtain the second calculated mean; The minimum value calculation result is determined based on the second calculated mean.

10. The nuclear power plant accident diagnosis method according to claim 3, characterized in that, The step of analyzing and calculating based on the current operating parameters, historical data before the unit trip, and the current status signal to obtain the accident diagnosis logic judgment conditions includes: Based on the current operating condition parameters, calculate the parameter trend at the current moment or the parameter maximum and minimum values ​​over a previous period to obtain the sliding trend calculation results and historical maximum and minimum value calculation results; Determine whether the trend threshold or the extreme value threshold is met based on the sliding trend calculation result and the historical maximum / minimum value calculation result. If the trend threshold or the extreme value threshold is met, then it is determined that the important parameter sliding window trend and historical extreme value are satisfied.

11. The nuclear power plant accident diagnosis method according to claim 10, characterized in that, The sliding trend calculation result is obtained through the following calculation method: Get the values ​​of the target parameters within a preset time period before the current time; The sampling data is determined based on the data sampling interval and the preset time period; The slope of the sampled data was calculated using a linear regression method to obtain the sampling slope. The sliding trend calculation result is determined based on the sampling slope.

12. The nuclear power plant accident diagnosis method according to claim 10, characterized in that, The historical extreme values ​​were calculated using the following method: Obtain the values ​​of the target parameters from the current moment to a certain historical moment; The sampling data is determined based on the data sampling interval and the time span from the current moment to the historical moment; The sampled data is arranged to obtain arranged data, and the historical extreme value calculation result is determined based on the arranged data.

13. The nuclear power plant accident diagnosis method according to claim 12, characterized in that, The sorted data includes: second ascending order data; The step of arranging the sampled data to obtain arranged data, and determining the historical extreme value calculation result based on the arranged data, includes: The sampled data are arranged in descending order to obtain the second ascending data; Calculate the mean of the first a data points in the second ascending data to obtain the third calculated mean; The historical extreme value calculation result is determined based on the third calculated mean.

14. The nuclear power plant accident diagnosis method according to claim 12, characterized in that, The sorted data includes: second descending order data; The step of arranging the sampled data to obtain arranged data, and determining the historical extreme value calculation result based on the arranged data, includes: The sampled data are arranged in ascending order to obtain the second descending order data; The mean of the first a data points in the second descending data is calculated to obtain the fourth calculated mean. The historical extreme value calculation result is determined based on the fourth calculated mean.

15. The nuclear power plant accident diagnosis method according to any one of claims 1-14, characterized in that, The following steps are included after step S40: Step S50: Determine whether a secondary diagnosis is needed for the accident diagnosis results. If not, end the accident diagnosis. Step S60: If so, continue to analyze the current and historical status of the unit in real time to obtain the cause of the accident.

16. A nuclear power plant accident diagnostic device, characterized in that, include: The data signal acquisition unit is used to acquire the current operating parameters and current status signals of the unit; The logic detection unit is used to determine whether the heap skipping signal is triggered based on the current state signal; The historical data acquisition unit is used to acquire historical data of the unit before the reactor skipping process; The accident diagnosis unit is used to analyze the current and historical states of the unit in real time based on the current operating parameters and the historical data before the unit tripped, and to obtain the accident diagnosis results.

17. The nuclear power plant accident diagnostic device according to claim 16, characterized in that, The accident diagnosis unit includes: The first logic calculation module is used to analyze and calculate based on the current operating parameters, the historical data of the unit before the trip, and the current status signal to obtain the accident diagnosis logic judgment conditions. The accident diagnosis and analysis module is used to analyze the current and historical states of the unit based on the accident diagnosis logic judgment conditions to obtain the accident diagnosis results.

18. The nuclear power plant accident diagnostic device according to claim 17, characterized in that, The first logic calculation module includes: a first OR gate, a first NOT gate, a second OR gate, a third OR gate, a second NOT gate, a third NOT gate, and a first AND gate; The first input terminal of the first OR gate is connected to the important parameter trend or extreme value before the heap jump, the second input terminal of the first OR gate is connected to the important parameter sliding window trend and historical extreme value, and the output terminal of the first OR gate is connected to the first input terminal of the first AND gate through the first NOT gate. The first input terminal of the second OR gate is connected to the important parameter trend or maximum / minimum value before the stack jump, the second input terminal of the second OR gate is connected to the current protection signal trigger signal, and the output terminal of the second OR gate is connected to the second input terminal of the first AND gate. The first and second input terminals of the third OR gate are connected to the first output jump signal, and the output terminal of the third OR gate is connected to the third input terminal of the first AND gate; the input terminal of the second NOT gate is connected to the setting state, and the output terminal of the second NOT gate is connected to the fourth input terminal of the first AND gate; the input terminal of the third NOT gate is connected to the setting state, and the output terminal of the third NOT gate is connected to the fifth input terminal of the first AND gate; the output terminal of the first AND gate outputs the accident diagnosis result.

19. The nuclear power plant accident diagnostic device according to claim 17, characterized in that, Also includes: The second logic calculation module has a first input terminal connected to the output terminal of the first logic calculation module, a second input terminal connected to the current protection signal trigger signal, a third input terminal connected to the secondary diagnosis trigger signal associated with the accident diagnosis result, and an output terminal outputting the accident cause of the accident diagnosis result.

20. A storage medium, characterized in that, The storage medium stores a computer program adapted for loading by a processor to perform the steps of the nuclear power plant accident diagnosis method as described in any one of claims 1 to 15.

21. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps of the nuclear power plant accident diagnosis method as described in any one of claims 1 to 15 by calling the computer program stored in the memory.

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