Core cooling monitoring system and core cooling monitoring method, medium, product

Abstract

This application discloses a core cooling monitoring system, method, medium, and product, relating to the field of nuclear reactor monitoring technology. The system includes: a parameter monitoring device comprising N redundantly configured monitoring channels, each connected to the reactor pressure vessel; the parameter monitoring device monitors the core temperature of the reactor pressure vessel through the monitoring channels, where N is an even number; a signal conditioning cabinet comprising a first sub-cabinet and a second sub-cabinet, each connected to a monitoring channel; the first and second sub-cabinets are respectively used to cross-calibrate a first temperature monitoring result determined based on a first core temperature group and a second temperature monitoring result determined based on a second core temperature group to determine the target temperature monitoring result of the reactor pressure vessel; the first and second core temperature groups each include core temperatures monitored by M distinct monitoring channels.

Description

Technical Field

[0001] This application belongs to the field of nuclear reactor monitoring technology, and in particular relates to a core cooling monitoring system, core cooling monitoring method, medium and product. Background Technology

[0002] During the operation of a nuclear power plant, core cooling monitoring is a critical aspect of ensuring the safety of the nuclear reactor. It is necessary to accurately monitor parameters such as the core temperature to ensure that the core is in an effective cooling state.

[0003] Currently, for safety reasons, redundancy is typically required for core cooling monitoring. Specifically, the signal conditioning cabinet of the core cooling monitoring system is often divided into two independent redundant columns. Each of these two redundant columns performs calculations independently, for example, calculating temperature monitoring results based on the core temperature at different locations.

[0004] However, under this independent calculation method, the temperature monitoring results of the two independent redundant columns may differ significantly, making it difficult for operators to make judgments and hindering the accurate determination of the core cooling status information. Summary of the Invention

[0005] This application provides a core cooling monitoring system, method, medium, and product that can more accurately determine the core cooling status information.

[0006] A first aspect of this application provides a core cooling monitoring system, comprising: The parameter monitoring equipment includes N redundant monitoring channels, each connected to the reactor pressure vessel. The parameter monitoring equipment monitors the core temperature of the reactor pressure vessel through the monitoring channels, where N is an even number. The signal conditioning cabinet includes a first sub-cabinet and a second sub-cabinet, which are respectively connected to each monitoring channel. The first and second sub-cabinets are used to cross-calibrate the first temperature monitoring result determined based on the first core temperature group and the second temperature monitoring result determined based on the second core temperature group to determine the target temperature monitoring result of the reactor pressure vessel. The first and second core temperature groups each include the core temperature monitored by M different monitoring channels, where M is half of N.

[0007] A second aspect of this application provides a core cooling monitoring method, characterized in that the method is applied to a first sub-cabinet and / or a second sub-cabinet in the core cooling monitoring system provided in any of the above aspects, the method comprising: The first core temperature group and the second core temperature group of the reactor pressure vessel are obtained; the first core temperature group and the second core temperature group include core temperatures monitored by different monitoring channels. The first temperature monitoring result is determined based on the first core temperature group, and the second temperature monitoring result is determined based on the second core temperature group; The first temperature monitoring result and the second temperature monitoring result are cross-calibrated to determine the target temperature monitoring result of the reactor pressure vessel.

[0008] A third aspect of this application provides a core cooling monitoring method, the method comprising: Acquire multiple pressure vessel water level values ​​monitored in the reactor pressure vessel; The second initial monitoring results corresponding to the water level values ​​of multiple pressure vessels are statistically analyzed to obtain the second statistical distribution information. Based on the second statistical distribution information, the target water level monitoring result of the reactor pressure vessel is determined through the first redundant data voting logic.

[0009] A fourth aspect of the embodiments of this application provides a readable storage medium on which a program or instructions are stored, and when the program or instructions are executed by a processor, they implement the core cooling monitoring method provided by any aspect of the embodiments of this application described above.

[0010] A fifth aspect of the embodiments of this application provides a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform the core cooling monitoring method provided in any of the embodiments of this application described above.

[0011] In the core cooling monitoring system provided in this application embodiment, the parameter monitoring equipment has N redundant monitoring channels to monitor the first and second core temperature groups in the reactor pressure vessel, providing comprehensive data for core cooling monitoring. Then, the first and second sub-cabinets of the signal conditioning cabinet are connected to each monitoring channel, enabling comprehensive acquisition of the first and second core temperature groups. A first temperature monitoring result is determined based on the first core temperature group, and a second temperature monitoring result is determined based on the second core temperature group. The first and second temperature monitoring results are then cross-calibrated. Thus, through cross-calibration, the first and second sub-cabinets can compare, analyze, and correct errors or anomalies that may arise from independent calculations, eliminating differences in results caused by independent calculations. This results in a more accurate and reliable target temperature monitoring result, enabling more precise judgment of core cooling status information. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the structure of a core cooling monitoring system provided in one embodiment of this application; Figure 2 This is a schematic flowchart of the core outlet temperature monitoring process in a core cooling monitoring method provided in one embodiment of this application; Figure 3 This is a schematic diagram of the pressure vessel water level monitoring process in a core cooling monitoring method provided in one embodiment of this application. Detailed Implementation

[0014] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0015] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0016] It should be noted that the acquisition, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations.

[0017] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0018] In traditional core cooling monitoring systems, redundant signal conditioning cabinets employ independent computing architectures. Temperature data collected from different monitoring channels are prone to non-negligible deviations during independent calculations. When two independent redundant columns monitor core temperatures at different locations, the lack of cross-column data cross-calibration mechanisms can lead to systematic deviations in the temperature monitoring results output by the two columns. This makes it difficult for operators to effectively determine the specific parameters of the core outlet saturation margin, hindering post-accident handling.

[0019] Faced with the aforementioned problems, this application first recognized the inherent flaws in the independent computing architecture of redundant monitoring channels. When two columns of monitoring data generate results based on temperature groups at different locations, the physical isolation of the data sources prevents the system from identifying the source of deviation. Traditional solutions lack a low-level logical framework for data cross-verification. To address this, this application explored three improvement paths: first, adding an independent verification module, which increases hardware complexity; second, unifying the two data sources, which weakens the advantages of redundancy design; and third, constructing a cross-column data cross-verification mechanism to achieve result fusion while maintaining the redundant architecture. Through comparison, it was found that the cross-column data cross-verification mechanism can both retain redundancy and fault tolerance capabilities and eliminate independent calculation deviations. Ultimately, a dual-rack collaborative processing architecture was deployed in the signal conditioning rack, enabling real-time cross-verification of the two columns of monitoring data during the calculation process, ensuring the uniqueness and reliability of the output results.

[0020] In this regard, such as Figure 1 As shown in the diagram, this application provides a schematic diagram of a core cooling monitoring system, which includes: The parameter monitoring device 200 includes N redundant monitoring channels, each of which is connected to the reactor pressure vessel 100. The parameter monitoring device 200 monitors the core temperature of the reactor pressure vessel 100 through the monitoring channels, where N is an even number. The signal conditioning cabinet 300 includes a first sub-cabinet 310 and a second sub-cabinet 320, which are respectively connected to each monitoring channel. The first sub-cabinet 310 and the second sub-cabinet 320 are used to cross-calibrate the first temperature monitoring result determined based on the first core temperature group and the second temperature monitoring result determined based on the second core temperature group to determine the target temperature monitoring result of the reactor pressure vessel 100. The first core temperature group and the second core temperature group each include the core temperature monitored by M different monitoring channels, where M is half of N.

[0021] In this embodiment, the N monitoring channels can be implemented using physically isolated independent signal transmission paths, for example, configured as four monitoring channels: a first monitoring channel 211, a second monitoring channel 212, a third monitoring channel 221, and a fourth monitoring channel 222. Each monitoring channel is connected to the reactor pressure vessel 100 and is used to collect core temperature data in real time. A thermocouple array can be used for this purpose, thereby ensuring physical redundancy in data acquisition. The core outlet temperature measuring points corresponding to the redundantly configured first monitoring channel 211, second monitoring channel 212, third monitoring channel 221, and fourth monitoring channel 222 are located on a radial plane at the same axial height within the reactor pressure vessel 100, distributed within the four quadrants of the core.

[0022] Among them, the first sub-rack 310 and the second sub-rack 320 refer to control units that are independently deployed and have the same computing logic. Specifically, they can be implemented using a dual-row security-grade rack architecture, which improves the system's fault tolerance by processing data in parallel.

[0023] Mutual verification refers to the logical operation of cross-validating two sets of temperature monitoring results. Specifically, it can be implemented by difference comparison or weighted fusion algorithm, which improves the reliability of monitoring results by eliminating the bias of individual data.

[0024] The first core temperature group and the second core temperature group each include core temperatures monitored by M different monitoring channels, where M is half of N. Specifically, when the N monitoring channels include the first monitoring channel 211, the second monitoring channel 212, the third monitoring channel 221, and the fourth monitoring channel 222, the temperatures monitored by the first monitoring channel 211 and the second monitoring channel 212 constitute the first core temperature group, and the temperatures monitored by the third monitoring channel 221 and the fourth monitoring channel 222 constitute the second core temperature group.

[0025] This application uses a dual-row deployed signal conditioning cabinet 300 to cross-calibrate the temperature data collected by the redundant monitoring channels, cross-validating the two sets of results that were originally calculated independently. This solves the problem of difficulty in judgment caused by the difference between the dual-row results in the traditional redundant architecture, thereby improving the accuracy of core cooling status monitoring.

[0026] The working process and principle of this application are as follows: The core cooling monitoring system includes a parameter monitoring device 200 and a signal conditioning cabinet 300. The parameter monitoring device 200 has redundant first monitoring channels 211, second monitoring channels 212, third monitoring channels 221, and fourth monitoring channels 222, which are respectively connected to the reactor pressure vessel 100. The temperatures monitored by the first monitoring channels 211 and second monitoring channels 212 constitute the first core temperature group, and the temperatures monitored by the third monitoring channels 221 and fourth monitoring channels 222 constitute the second core temperature group. The signal conditioning cabinet 300 includes a first sub-cabinet 310 and a second sub-cabinet 320, both of which are connected to the four monitoring channels. The two sub-cabinets independently calculate the temperature monitoring results based on the two sets of core temperatures, perform cross-calibration, and finally determine the target temperature monitoring result of the reactor pressure vessel 100.

[0027] By redundantly configuring monitoring channels and sub-cabinets, the system achieves high reliability. Two sub-cabinets process two sets of temperature data separately and cross-calibrate them, eliminating errors that might arise from a single data source and improving the accuracy of monitoring results. The data cross-validation mechanism between the sub-cabinets enables the system to identify and handle potential data deviations, thereby outputting more reliable target temperature monitoring results.

[0028] As an example, the core cooling monitoring system includes a parameter monitoring device 200 and a signal conditioning cabinet 300. The parameter monitoring device 200 is equipped with a first monitoring channel 211, a second monitoring channel 212, a third monitoring channel 221, and a fourth monitoring channel 222, which are respectively connected to the reactor pressure vessel 100. The temperatures monitored by the first monitoring channel 211 and the second monitoring channel 212 constitute the first core temperature group, and the temperatures monitored by the third monitoring channel 221 and the fourth monitoring channel 222 constitute the second core temperature group.

[0029] The signal conditioning cabinet 300 includes a first sub-cabinet 310 and a second sub-cabinet 320. Both sub-cabinets are connected to the first monitoring channel group 210 and the second monitoring channel group 220, and can simultaneously receive two sets of core temperature data. The first sub-cabinet 310 calculates a first temperature monitoring result based on the first core temperature group, and simultaneously calculates a second temperature monitoring result based on the second core temperature group. The second sub-cabinet 320 performs the same calculation process.

[0030] The two sub-racks perform cross-calibration on their respective calculated first and second temperature monitoring results. The cross-calibration process may include comparing the differences between the two results, assessing their respective reliability, and determining the final target temperature monitoring result based on a pre-defined cross-calibration algorithm. For example, if the two results are similar, the average can be taken; if there are significant differences, the more reliable result is selected based on its respective reliability index.

[0031] Ultimately, the two sub-cabinets output a unified target temperature monitoring result, reflecting the actual temperature state of the reactor pressure vessel 100. This result can be transmitted to the display control console 400 for monitoring and decision support of the core cooling status. Specifically, the first sub-cabinet 310 is connected to the first display 410 to output the target temperature monitoring result calculated by the first sub-cabinet 310 for display; the second sub-cabinet 320 is connected to the second display 420 to output the target temperature monitoring result calculated by the second sub-cabinet 320 for display.

[0032] In this embodiment, the parameter monitoring device 200 has N redundant monitoring channels, which monitor the first and second core temperature groups in the reactor pressure vessel, providing comprehensive data for core cooling monitoring. Then, the first sub-cabinet 310 and the second sub-cabinet 320 of the signal conditioning cabinet 300 are connected to each monitoring channel, enabling comprehensive acquisition of the first and second core temperature groups. Based on the first core temperature group, a first temperature monitoring result is determined, and based on the second core temperature group, a second temperature monitoring result is determined. The first and second temperature monitoring results are then cross-calibrated. Thus, through cross-calibration, the first sub-cabinet 310 and the second sub-cabinet 320 can compare, analyze, and correct errors or anomalies that may arise from independent calculations, eliminating differences caused by independent calculations and synthesizing a more accurate and reliable target temperature monitoring result, thereby enabling more precise judgment of core cooling status information.

[0033] In some of the solutions described above in this application, the neutron measurement component and the temperature measurement component are integrated onto the same cable, thus forming an integrated neutron and temperature measurement component. However, since the redundant neutron measurement component needs to be divided into four groups for neutron measurement signal acquisition, if the number of monitoring channels for monitoring the core temperature signal is not four, a cable mixing problem will occur.

[0034] In this regard, such as Figure 1 As shown, this application further proposes four sets of neutron measurement signals in response to redundancy settings, with N monitoring channels constituting four monitoring channels; Four monitoring channels are constructed to form a first monitoring channel group 210 and a second monitoring channel group 220. Each of the first monitoring channel group 210 and the second monitoring channel group 220 includes two different monitoring channels. The first monitoring channel group 210 corresponds to the first core temperature group, and the second monitoring channel group 220 corresponds to the second core temperature group.

[0035] In this embodiment, in practical applications, monitoring channel configuration refers to the system dynamically adjusting the number of monitoring channels according to the redundancy level of neutron measurement signals specified in the nuclear reactor safety standards. A four-channel configuration can be used to match the redundancy requirements of four sets of neutron measurement signals. Monitoring channel grouping refers to dividing all monitoring channels into two logical groups, which can be implemented through physical isolation or logical partitioning. Its purpose is to provide independent data processing units for the mutual calibration mechanism. Specifically, channel mutual exclusion configuration means that the monitoring channels within each monitoring channel group do not overlap. This can be implemented through channel number allocation or physical connection isolation, aiming to ensure the independence of data from each group and avoid single-point failures affecting multiple groups. In practical applications, the channel group-temperature group correspondence refers to establishing a mapping between the monitoring channel group and a specific core temperature data set. This can be achieved through signal routing configuration or data processing logic. Its purpose is to enable the sub-cabinets of the signal conditioning cabinet 300 to generate temperature monitoring results based on data from specific channel groups, providing a basis for mutual calibration.

[0036] Specifically, the scheme in this application constructs two monitoring channel groups, each containing two distinct channels, by precisely setting the number of monitoring channels to four and matching them with four sets of neutron measurement signals. Each monitoring channel group establishes a mapping relationship with its corresponding core temperature group, enabling the first sub-cabinet 310 and the second sub-cabinet 320 of the signal conditioning cabinet 300 to generate temperature monitoring results based on independent dual-channel data. During the cross-calibration process, since each group contains two channels, even if one channel fails, the data from the other channel can still be used as a reference, thereby achieving fault identification and data verification at the group level. This ensures that the cross-calibration mechanism can compare results based on reliable data, ultimately providing more accurate core temperature monitoring results.

[0037] As an example, in response to four sets of redundant neutron measurement signals, the first monitoring channel group 210 includes a first monitoring channel 211 and a second monitoring channel 212, and the second monitoring channel group 220 includes a third monitoring channel 221 and a fourth monitoring channel 222. The first core temperature monitored by the first monitoring channel 211 and the second core temperature monitored by the second monitoring channel 212 constitute the first core temperature group. The third core temperature monitored by the third monitoring channel 221 and the fourth core temperature monitored by the fourth monitoring channel 222 constitute the second core temperature group.

[0038] Specifically, four integrated neutron temperature measurement units are installed at different positions at the same radial height on the reactor pressure vessel 100. The first monitoring channel 211 and the second monitoring channel 212 each contain one integrated neutron temperature measurement unit, and the third monitoring channel 221 and the fourth monitoring channel 222 each contain one integrated neutron temperature measurement unit. For example, if the first monitoring channel measures a first core temperature of 350 degrees Celsius and the second monitoring channel measures a second core temperature of 355 degrees Celsius, these two temperature values ​​constitute the first core temperature group. Similarly, the temperature values ​​measured by the third and fourth monitoring channels constitute the second core temperature group.

[0039] In this embodiment, the four redundant sets of neutron measurement signals corresponding to the monitoring channel are divided into four independent physical channels. With spatial separation and connection to the reactor pressure vessel 100, the cable mixing problem that may occur when integrating the neutron measurement component and the temperature measurement component can be solved, so as to achieve more comprehensive and accurate monitoring of the core temperature, while ensuring the redundancy and reliability of the measurement system.

[0040] In some of the schemes described above in this application, although redundant monitoring channels can improve the reliability of temperature monitoring, in actual operation, if N monitoring channels share the same power supply, a failure of the power supply will cause all N monitoring channels to fail simultaneously, making it impossible to achieve true redundancy protection, and thus affecting the continuity and accuracy of core cooling monitoring.

[0041] In response, this application further proposes that N monitoring channels be connected to different power supplies respectively.

[0042] In this embodiment, connecting to different power supplies means that each monitoring channel is independently connected to a different power supply unit. This can be achieved by using multiple independent DC power modules or drawing power from different electrical buses. The purpose is to avoid the risk of systemic failure caused by a single power supply failure and to ensure that other monitoring channels can still maintain normal operation when a single power supply is abnormal, thereby providing a stable data foundation for the mutual calibration mechanism.

[0043] Specifically, the solution in this application configures physically isolated power supply paths for each monitoring channel. When a power supply fails, only the monitoring function of the corresponding channel is interrupted, while the other channels can still continuously transmit core temperature data to the signal conditioning cabinet 300. The signal conditioning cabinet 300 continues to perform cross-calibration calculations based on the core temperature data obtained from the effective channels, maintaining the output capability of the target temperature monitoring results, thereby ensuring that the reliability of the core cooling status judgment is not disturbed in the event of abnormal power supply.

[0044] As a preferred embodiment, the solution of this application is implemented as follows: each monitoring channel can be connected to an independent power supply unit. These power supply units adopt a redundant configuration and electrical isolation design to ensure that when one power supply unit fails, the power supply path of other channels is not affected, and the temperature monitoring data can still be transmitted normally to the signal conditioning cabinet 300.

[0045] Through the above scheme, this application effectively avoids the damage to the redundant monitoring architecture caused by single-point power supply failure, strengthens the fault tolerance capability of the system under abnormal power supply conditions, and ensures the reliability of continuous and effective monitoring of the core cooling status.

[0046] In some of the schemes described above in this application, the core cooling monitoring system improves the reliability of temperature monitoring through redundant monitoring channels and a dual-cabinet cross-calibration mechanism. However, since the severe accident instrumentation and control system is connected to the signal conditioning cabinet 300, there is a risk that a failure of the signal conditioning cabinet 300 could lead to the failure of the severe accident instrumentation and control system.

[0047] In this regard, such as Figure 1 As shown, this application further proposes that the system also includes: The severe accident instrumentation and control system 500 is connected to any monitoring channel and is used to determine the core accident status of the reactor pressure vessel based on the core temperature obtained from the monitoring channel.

[0048] In this embodiment, the severe accident instrumentation and control system 500 directly acquires the raw measurement signals from thermocouples and resistance temperature detectors connected to the monitoring channel. These signals are used to determine the core accident status of the reactor pressure vessel based on the core temperature obtained from the monitoring channel. An isolation distribution device is set up for the raw measurement signal acquisition and distribution between the severe accident instrumentation and control system 500 and the signal conditioning cabinet 300. This ensures that a failure of the signal conditioning cabinet 300 does not affect the availability of the signals acquired by the severe accident instrumentation and control system 500, thereby improving the independence and availability of the severe accident instrumentation and control system 500.

[0049] The critical accident control system 500 is directly connected to at least one monitoring channel via a physical interface to directly acquire raw measurement signals, avoiding signal interruption or failure caused by a malfunction of the signal conditioning cabinet 300. The signal processing unit of the critical accident control system 500 can have a built-in accident detection algorithm, such as triggering an accident warning when the temperature rise rate exceeds a preset threshold for three consecutive sampling cycles. Furthermore, for safety reasons, the critical accident control system 500 can also be redundantly configured. For example, the first critical accident control system 500 can be connected to the first monitoring channel 211, and the second critical accident control system 500 can be connected to the second monitoring channel 212. As an example, the core cooling monitoring system also includes a severe accident instrumentation and control system 500. The severe accident instrumentation and control system 500 is directly connected to the first monitoring channel 211, rather than indirectly through the signal conditioning cabinet 300, thereby ensuring signal independence and reliability. The severe accident instrumentation and control system 500 is connected to the first monitoring channel 211. The severe accident instrumentation and control system 500 is used to determine the core accident status of the reactor pressure vessel based on the core temperature monitored by the first monitoring channel 211.

[0050] Specifically, the severe accident instrumentation and control system 500 can employ a dedicated data processing unit connected to the first monitoring channel 211 via a data bus. The data processing unit receives core temperature data from the first monitoring channel 211 and performs real-time analysis and processing. Through direct connection and a built-in accident determination algorithm, the severe accident instrumentation and control system 500 can continuously receive raw temperature data and determine the core accident status in real time, without relying on the processing results of the signal conditioning cabinet 300. Therefore, the severe accident instrumentation and control system 500 can promptly detect core temperature anomalies, providing operators with accurate information on the core accident status and facilitating the implementation of appropriate emergency measures.

[0051] This embodiment allows the severe accident instrumentation and control system 500 to connect directly to the monitoring channel, rather than to the signal conditioning cabinet 300. It also incorporates an accident determination algorithm to continuously receive raw temperature data and determine the core accident status. This avoids the risk of the severe accident instrumentation and control system 500 failing due to a failure of the signal conditioning cabinet 300, and enables timely accident warnings. This effectively improves the independence, reliability, and timeliness of the severe accident instrumentation and control system 500 in determining the core accident status.

[0052] In some of the schemes described above in this application, the signal conditioning cabinet 300 is divided into a first sub-cabinet 310 and a second sub-cabinet 320, which respectively perform the mutual calibration function of temperature monitoring results. However, if the sub-cabinets do not adopt a safety-grade design and lack computer technology support, they may not be able to reliably perform the mutual calibration operation in safety-critical scenarios in nuclear power plants, resulting in significant differences in temperature monitoring results, increasing the difficulty of operator judgment, and affecting the accurate assessment of the core cooling status.

[0053] In this regard, this application further proposes that both the first sub-cabinet 310 and the second sub-cabinet 320 adopt a security-grade signal conditioning cabinet based on computer technology.

[0054] In this embodiment, the design of the safety-grade signal conditioning cabinet based on computer technology meets the nuclear safety grade (1E) electrical equipment standard and has high reliability.

[0055] Specifically, the solution in this application uses the first sub-cabinet 310 and the second sub-cabinet 320 to perform mutual calibration logic operations based on computer technology, receive and process core temperature data from different monitoring channels in real time, calculate the availability index and uncertainty parameter of the temperature monitoring results, and compare and determine the difference according to preset rules. At the same time, the safety-level design ensures that the mutual calibration function can maintain stable operation and avoid data distortion due to equipment malfunction, thereby effectively eliminating the significant differences between the two redundant monitoring results in the independent calculation mode.

[0056] This embodiment improves the reliability and safety of the reactor core cooling monitoring system. The use of a computer-based safety-grade signal conditioning cabinet effectively protects internal equipment from external environmental factors, ensuring the system continues to operate normally under extreme conditions. This design enhances the system's anti-interference capability and environmental adaptability, thereby improving the accuracy and continuity of reactor core cooling monitoring. Therefore, this solution can maintain stable monitoring performance in various complex environments, providing a more reliable guarantee for the safe operation of nuclear power plants.

[0057] Based on the core cooling monitoring system provided in this application, a specific embodiment of the core cooling monitoring method is also provided.

[0058] like Figure 2 As shown, a schematic flowchart of a core cooling monitoring method is provided. This core cooling monitoring method is applied to the first sub-cabinet and / or the second sub-cabinet in the aforementioned core cooling monitoring system, including the following steps S210 to S230: S210, acquire the first core temperature group and the second core temperature group of the reactor pressure vessel; the first core temperature group and the second core temperature group include core temperatures monitored by different monitoring channels. S220, determine the first temperature monitoring result based on the first core temperature group, and determine the second temperature monitoring result based on the second core temperature group; S230, cross-calibrate the first temperature monitoring result with the second temperature monitoring result to determine the target temperature monitoring result of the reactor pressure vessel.

[0059] In this embodiment, the core cooling monitoring system refers to a system used to monitor the cooling status of the nuclear reactor core. Specifically, it can be implemented using a dual-row redundant architecture that includes a first sub-cabinet and a second sub-cabinet. The two rows of cabinets independently collect data and perform calculations, thereby improving system reliability.

[0060] The first core temperature group and the second core temperature group each include core temperatures monitored by M different monitoring channels, where M is half of N. Specifically, when the N monitoring channels include the first monitoring channel, the second monitoring channel, the third monitoring channel, and the fourth monitoring channel, the temperatures monitored by the first monitoring channel and the second monitoring channel constitute the first core temperature group, and the temperatures monitored by the third monitoring channel and the fourth monitoring channel constitute the second core temperature group.

[0061] Temperature monitoring results refer to the core cooling status assessment values ​​calculated based on temperature data. Specifically, they can be achieved through methods such as statistical averaging, extreme value screening, or weighted calculation, and provide basic data for mutual calibration through quantitative analysis.

[0062] Cross-verification refers to the process of cross-validating two independent monitoring results. This can be achieved through methods such as difference comparison, uncertainty analysis, or logical voting. By eliminating anomalies or biases in individual data, the accuracy and reliability of the final monitoring results are ensured.

[0063] This application solves the problem of judgment difficulties caused by the difference in dual-row monitoring results in the prior art by independently acquiring different temperature data under a dual-row redundant architecture and introducing a mutual calibration mechanism. While retaining the safety advantages of the redundant design, it improves the consistency of monitoring results and the reliability of decision-making.

[0064] The working process and principle of this application are as follows: First, the first core temperature group and the second core temperature group of the reactor pressure vessel are obtained.

[0065] Next, the first temperature monitoring result is determined based on the first core temperature group, and the second temperature monitoring result is determined based on the second core temperature group. This step involves processing and analyzing the temperature data to obtain the respective temperature monitoring results.

[0066] Finally, the first temperature monitoring result and the second temperature monitoring result are cross-calibrated to determine the target temperature monitoring result for the reactor pressure vessel. The cross-calibration process compares the differences between the two monitoring results and, through a preset algorithm or rule, comprehensively considers the reliability and accuracy of the two results to ultimately obtain a more reliable target temperature monitoring result.

[0067] This method improves the accuracy and reliability of temperature monitoring by acquiring and cross-calibrating multiple temperature data. The cross-calibration mechanism can effectively eliminate errors or biases that may exist in single monitoring, providing more comprehensive and accurate results for temperature monitoring of reactor pressure vessels.

[0068] As an example, data acquisition begins: the first sub-cabinet acquires multiple thermocouple temperature readings to form the first core temperature group. Simultaneously, the second sub-cabinet acquires multiple thermocouple temperature readings to form the second core temperature group.

[0069] Next, the temperature monitoring results are calculated: the first sub-cabinet processes the data for the first core temperature group, such as removing outliers, calculating the average value, or selecting the highest value, to obtain the first temperature monitoring result. The second sub-cabinet processes the data for the second core temperature group in the same way to obtain the second temperature monitoring result.

[0070] Finally, a cross-calibration process is performed: first, the differences between the two temperature monitoring results are compared; then, the reliability of each temperature monitoring result is evaluated, considering factors such as the thermocouple's operating status and data consistency; next, the information from the two temperature monitoring results is integrated according to a preset cross-calibration algorithm; finally, based on the cross-calibration results, the final target temperature monitoring result is determined. This could be a weighted average of the two temperature monitoring results, the selection of the more reliable temperature monitoring result, or other comprehensive considerations.

[0071] This embodiment effectively improves the accuracy and reliability of core temperature monitoring. By acquiring multiple temperature data points and cross-calibrating them, errors that might arise from single monitoring are reduced. The cross-calibration mechanism can identify and eliminate potential systematic biases, providing more comprehensive and accurate temperature monitoring results. This method is particularly suitable for reactor transient conditions, providing operators with more reliable information on core cooling status. Furthermore, the comprehensive analysis of multiple data points enhances the redundancy and robustness of the temperature monitoring system, improving its resistance to single-point failures. Ultimately, this improved temperature monitoring method provides a more robust technical guarantee for the safe operation of the reactor, contributing to improved overall safety of nuclear power plants.

[0072] In some of the schemes described above in this application, the redundant temperature monitoring channel groups generate temperature monitoring results based on different core temperatures. However, when calculating the core outlet saturation margin, if only a single temperature value is used or the influence of pressure parameters is not considered, the margin assessment may be inaccurate and may not effectively reflect the true state of core cooling.

[0073] In this regard, this application further proposes that the first temperature monitoring result is the core outlet saturation margin; S220 includes: Obtain the maximum core outlet temperature in the first core temperature group and the target primary loop absolute pressure of the reactor pressure vessel. Determine the core saturation temperature based on the target primary loop absolute pressure; The difference between the core saturation temperature and the maximum core exit temperature is defined as the core exit saturation margin.

[0074] In this embodiment, the maximum core outlet temperature is obtained by filtering the measurements of multiple thermocouples in the first core temperature group. The target primary loop absolute pressure can be calculated using the real-time data collected by pressure sensors. The core saturation temperature is calculated using a primary loop absolute pressure-core saturation temperature correspondence table or a physical model. The difference calculation directly reflects the deviation between the maximum core outlet temperature and the core saturation temperature under the current pressure, thereby quantifying the cooling margin.

[0075] Specifically, when obtaining the maximum core outlet temperature, the system automatically identifies the measured values ​​of all thermocouples in the first core temperature group and selects the highest temperature value as the maximum core outlet temperature, ensuring that the margin assessment is based on the most unfavorable operating condition. The target primary loop absolute pressure is the sum of the primary loop relative pressure and the containment absolute pressure; if the containment absolute pressure measurement fails, the default value is used as the containment absolute pressure in the calculation.

[0076] The core saturation temperature can be obtained by looking up a table or by converting it using thermodynamic formulas. For example, it can be calculated using the following formula: TSAT = f(PABS) = 179.895 + 99.86X + 24.38X² + 5.67X³ + 0.935X 4 , where X = log10(PABS), TSAT is the core saturation temperature, and PABS is the primary loop absolute pressure.

[0077] During the difference calculation, the core outlet saturation margin equals the core saturation temperature minus the maximum core outlet temperature. A positive result indicates that the core outlet temperature has not reached saturation and the cooling capacity is sufficient; a negative result triggers an alarm signal. By combining pressure parameters with the maximum temperature value, this method avoids the limitations of single temperature monitoring, improves the accuracy of margin assessment, and provides a reliable basis for operators to judge the core cooling status.

[0078] As an example, firstly, the maximum core outlet temperature in the first core temperature group and the target primary loop absolute pressure in the reactor pressure vessel are obtained. For example, the maximum core outlet temperature is measured to be 320 degrees Celsius by temperature sensors, and the target primary loop absolute pressure is measured to be 15.5 MPa by pressure sensors.

[0079] Secondly, the core saturation temperature is determined based on the target primary circuit absolute pressure. Specifically, this can be done by consulting a table showing the correspondence between primary circuit absolute pressure and core saturation temperature, or by using the formula for calculating this correspondence. In this example, the core saturation temperature corresponding to 15.5 MPa is 345 degrees Celsius.

[0080] Finally, the difference between the core saturation temperature and the maximum core exit temperature is determined as the core exit saturation margin. In this example, the core exit saturation margin is 345 degrees - 320 degrees = 25 degrees.

[0081] This embodiment enables accurate calculation of the core outlet saturation margin, providing a reliable basis for assessing the core cooling status. This allows operators to promptly determine whether the core is in a safe cooling state, effectively preventing core overheating accidents. Furthermore, by comparing the core saturation temperature with the actual measured maximum core outlet temperature, the safety margin of core cooling can be intuitively reflected, facilitating quick and correct decision-making by operators.

[0082] In some of the solutions described above in this application, when performing cross-calibration based on temperature monitoring results from different monitoring channel groups, if only the numerical differences between the two groups of temperature monitoring results are simply compared without considering the availability and uncertainty of the temperature monitoring results, the cross-calibration process may fail to accurately assess the reliability of the temperature monitoring results, thereby affecting the accuracy of the target temperature monitoring results.

[0083] In this regard, this application further proposes S230, which includes: Obtain the first availability and first uncertainty of the first temperature monitoring result, and obtain the second availability and second uncertainty of the second temperature monitoring result; Based on the first availability and the first uncertainty, and the second availability and the second uncertainty, the first temperature monitoring results and the second temperature monitoring results are cross-calibrated to determine the target temperature monitoring results of the reactor pressure vessel.

[0084] In this embodiment, the first availability is determined by counting the number of invalid thermocouples in the first monitoring channel group. An invalid thermocouple is defined as a thermocouple whose temperature measurement value differs from the average temperature of the first core temperature group by more than a preset threshold. The determination of the first uncertainty requires considering the target primary loop absolute pressure. A target curve covering the maximum core outlet temperature is selected from predefined first and second uncertainty curves, and the corresponding uncertainty value is extracted. During the cross-calibration process, when both sets of temperature monitoring results are available, the ratio of the absolute value of the difference in monitoring results to the cumulative uncertainty value is calculated, and the final target temperature monitoring result is selected based on the comparison results.

[0085] Specifically, the number of invalid thermocouples reflects the overall health status of the monitoring channel group. For example, when the number of invalid thermocouples exceeds a preset proportion, the corresponding temperature monitoring result is deemed unusable. The uncertainty curve is selected based on the range of the maximum core outlet temperature. For example, if the maximum core outlet temperature is greater than a preset switching value, the curve with a wider range from the first and second uncertainty curves is selected as the target uncertainty curve; if the maximum core outlet temperature is not greater than the preset switching value, the curve with a narrower range from the first and second uncertainty curves is selected as the target uncertainty curve. During the cross-calibration process, if the absolute value of the difference between the monitoring results is less than the cumulative uncertainty value, it indicates that the two sets of temperature monitoring results are consistent within the allowable error range, and their average value can be taken as the target temperature monitoring result; if the absolute value of the difference exceeds the cumulative uncertainty value, an alarm is triggered, and the conservative result is used as the target temperature monitoring result, that is, the minimum value between the first and second temperature monitoring results is selected as the target temperature monitoring result. By introducing a quantitative assessment of availability and uncertainty, the cross-calibration process can dynamically adjust the weight of the monitoring results, improving the robustness of the target temperature monitoring results.

[0086] As an example, in the temperature monitoring process of the reactor pressure vessel, the cross-calibration process between the first and second temperature monitoring results is specifically executed. First, the first availability is determined by counting the number of invalid thermocouples whose deviation from the average temperature of the first core temperature group exceeds a preset threshold. When the number of invalid thermocouples exceeds a preset proportion, the first availability is marked as unavailable. The calculation of the first uncertainty is further based on the target uncertainty curve corresponding to the maximum core outlet temperature. The target uncertainty curve is selected from the pre-stored first and second uncertainty curves, based on whether the maximum core outlet temperature exceeds a preset switching value. When both the first and second availability are available, the comparison between the absolute value of the difference in monitoring results and the accumulated uncertainty value is triggered. If the absolute value of the difference in monitoring results is less than the accumulated uncertainty value, the target temperature monitoring result is the average of the first and second temperature monitoring results; if the absolute value of the difference in monitoring results is not less than the accumulated uncertainty value, the target temperature monitoring result is marked as abnormal and an alarm signal is triggered.

[0087] This embodiment effectively solves the problem of difficulty in judgment caused by differences in temperature monitoring results between redundant monitoring channels. By introducing availability determination and uncertainty quantification evaluation mechanism, dynamic verification of the credibility of monitoring results is realized, thereby ensuring the reliability of target temperature monitoring results, providing operators with clear basis for judging the core cooling status, and avoiding the risk of misjudgment caused by data conflicts in redundant systems.

[0088] In some of the solutions described above in this application, when obtaining the availability and uncertainty of temperature monitoring results, if only a single-range uncertainty curve is used for pressure parameter matching, the dynamic changes in the absolute pressure of the first loop under different operating conditions of the reactor pressure vessel may lead to deviations in uncertainty assessment, thereby affecting the accuracy of cross-calibration of temperature monitoring results.

[0089] In this regard, this application further proposes a first availability and a first uncertainty for obtaining the first temperature monitoring result, including: Obtain the number of invalid thermocouples in the first monitoring channel group; invalid thermocouples are thermocouples whose temperature measurement value is greater than the average temperature value in the first core temperature group than a preset threshold. Based on the number of thermocouples, determine the first availability of the first temperature monitoring result; Obtain the first uncertainty curve and the second uncertainty curve. Both the first uncertainty curve and the second uncertainty curve are used to characterize the relationship between the uncertainty of the temperature monitoring result and the change of the primary loop absolute pressure of the reactor pressure vessel. The first uncertainty curve and the second uncertainty curve have different ranges. Based on the maximum core outlet temperature in the first core temperature group, the target uncertainty curve is determined from the first uncertainty curve and the second uncertainty curve; The first uncertainty is determined from the target uncertainty curve based on the target primary loop absolute pressure of the reactor pressure vessel.

[0090] In this embodiment, invalid thermocouples are identified by the difference between the measured temperature value and the average temperature value of the thermocouple; the number of thermocouples is negatively correlated with their availability. The first and second uncertainty curves cover different pressure ranges, for example, the first curve covers a range of 0 to 15 MPa, and the second curve covers a range of 10 to 25 MPa. The maximum core outlet temperature is used to determine the pressure fluctuation range under the current operating conditions, thereby selecting an uncertainty curve with a matching range. The target primary loop absolute pressure can be calculated from the real-time data collected by pressure sensors and mapped to the corresponding uncertainty value on the selected curve.

[0091] Specifically, when invalid thermocouples exist in the first monitoring channel group, an increase in the number of thermocouples will lead to a decrease in availability. For example, if the proportion of invalid thermocouples exceeds 0.4%, availability is determined to be unusable. When determining uncertainty, if the maximum core outlet temperature is in the high-temperature range, a second uncertainty curve covering the high-pressure range is selected; if it is in the low-temperature range, a first uncertainty curve covering the low-pressure range is selected. By dynamically matching an uncertainty curve with a more closely aligned range, uncertainty calculation errors caused by pressure parameters exceeding the range of a single curve are avoided, thereby improving the reliability of cross-calibration of temperature monitoring results.

[0092] This embodiment enables the selection of a suitable uncertainty curve based on the maximum core outlet temperature and the accurate determination of the uncertainty of temperature monitoring results based on the primary loop absolute pressure. This method considers the measurement error characteristics under different temperature and pressure conditions, improving the reliability and accuracy of temperature monitoring results and providing a more reliable data foundation for subsequent cross-calibration processes.

[0093] In some of the solutions described above in this application, when both temperature monitoring results are available, there are challenges in effectively handling the differences between them and ensuring the reliability of the final monitoring results, which may make it difficult for operators to accurately determine the core cooling status.

[0094] In response, this application further proposes a method to cross-calibrate the first temperature monitoring results and the second temperature monitoring results based on a first availability and a first uncertainty, and a second availability and a second uncertainty, to determine the target temperature monitoring results for the reactor pressure vessel, including: In response to both the first availability and the second availability indicating that the monitoring results are available, the absolute value of the difference between the first temperature monitoring results and the second temperature monitoring results is obtained, as well as the cumulative value of the uncertainty between the first uncertainty and the second uncertainty; Based on the comparison between the absolute value of the difference in monitoring results and the cumulative value of uncertainty, the target temperature monitoring result of the reactor pressure vessel is determined.

[0095] In this embodiment, the absolute value of the difference between the monitoring results is obtained by calculating the absolute difference between the first temperature monitoring result and the second temperature monitoring result, and the cumulative uncertainty value is obtained by adding the first uncertainty and the second uncertainty. The comparison process includes two processing logics: when the absolute value of the difference between the monitoring results is less than the cumulative uncertainty value, the average value is used as the target temperature monitoring result; when the absolute value of the difference between the monitoring results is not less than the cumulative uncertainty value, the minimum value of the two monitoring results is used as the target temperature monitoring result.

[0096] Specifically, after obtaining two temperature monitoring results and their corresponding uncertainties, the absolute difference between the two is first calculated and compared with the cumulative uncertainty. If the absolute difference is within the allowable uncertainty range, it indicates that the two results are consistent, and averaging them can improve the accuracy of the monitoring results. If the absolute difference exceeds the allowable uncertainty range, it indicates that at least one monitoring result is abnormal. In this case, the minimum value is selected as the final result, following the conservative safety principle to ensure the reliability of the core cooling status assessment. This process, by quantifying the difference and comparing the error range, solves the decision-making problem when results conflict in redundant monitoring systems, avoids the subjectivity of human judgment, and improves the automation processing capability of the monitoring system.

[0097] As an example, when both the first availability and the second availability indicate that the monitoring results are available, the absolute value of the difference between the first and second temperature monitoring results, and the cumulative uncertainty between the first and second uncertainties, are obtained. Specifically, the absolute value of the difference between the monitoring results can be obtained by calculating the absolute value of the difference between the first and second temperature monitoring results. For example, if the first temperature monitoring result is 320 degrees and the second temperature monitoring result is 318 degrees, then the absolute value of the difference is 2 degrees. The cumulative uncertainty can be obtained by adding the first uncertainty and the second uncertainty. For example, if the first uncertainty is 1.5 and the second uncertainty is 1.8, then the cumulative uncertainty is 3.3.

[0098] Furthermore, based on the comparison between the absolute value of the difference in monitoring results and the cumulative uncertainty, the target temperature monitoring result for the reactor pressure vessel is determined. Specifically, if the absolute value of the difference in monitoring results is less than the cumulative uncertainty, the average value of the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result for the reactor pressure vessel. For example, if the absolute value of the difference in monitoring results is 2 and the cumulative uncertainty is 3.3, since 2 is less than 3.3, (320 + 318) / 2 = 319 is determined as the target temperature monitoring result.

[0099] If the absolute value of the difference between the monitoring results is not less than the cumulative uncertainty value, then the minimum value between the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result for the reactor pressure vessel. For example, if the absolute value of the difference between the monitoring results is 4 and the cumulative uncertainty value is 3.3, since 4 is not less than 3.3, 318 (the minimum value between the first temperature monitoring result and the second temperature monitoring result) is determined as the target temperature monitoring result.

[0100] This embodiment enables the determination of a target temperature monitoring result by comparing the absolute value of the difference between the monitoring results and the accumulated uncertainty, when both the first and second temperature monitoring results are available. When the difference is within the uncertainty range, the average value is used as the target result, improving monitoring accuracy. When the difference exceeds the uncertainty range, the minimum value is selected as the target result, ensuring the conservatism and safety of the monitoring results. This method effectively addresses the potential significant differences between two redundant temperature monitoring results under independent calculation methods, providing operators with more accurate and reliable core temperature monitoring data. This facilitates accurate judgment of the core cooling status, thereby improving the operational safety of the nuclear reactor.

[0101] In some of the solutions described above in this application, the problem of how to scientifically determine the final monitoring result to avoid difficulties in operator judgment when both temperature monitoring results are available remains unresolved. In existing methods, if the two monitoring results differ significantly, the lack of objective standards to guide decision-making may lead to misjudgment or delays.

[0102] In this regard, this application further proposes to determine the target temperature monitoring results of the reactor pressure vessel based on the comparison results of the absolute value of the difference between monitoring results and the cumulative value of uncertainty, including: In response to the absolute value of the difference between the monitoring results being less than the cumulative value of the uncertainty, the average value of the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel. In response to the condition that the absolute value of the difference between the monitoring results is not less than the cumulative value of the uncertainty, the minimum value between the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel.

[0103] In this embodiment, the absolute value of the difference between the monitoring results is obtained by calculating the mathematical difference between the two temperature monitoring results, and the cumulative uncertainty value is obtained by adding the uncertainty values ​​of the two monitoring channels. The comparison process adopts the absolute value comparison method. When the monitoring difference is within the allowable uncertainty range, the mean value processing can improve the accuracy of the results; when it exceeds the error tolerance range, the smaller value is selected as the basis for conservative decision-making.

[0104] Specifically, under nuclear reactor operation conditions, when both redundant monitoring channels are functioning normally, the absolute value of the temperature difference between the two monitoring data sets is calculated in real time. Simultaneously, based on the current operating conditions of the pressure vessel, the uncertainty values ​​of the two data sets are retrieved from a pre-calibrated uncertainty curve. If the absolute value of the temperature difference is less than the sum of the uncertainties of the two sets, the arithmetic mean of the two data sets is automatically output as the final monitoring value; if the temperature difference exceeds the allowable error range, the smaller temperature value between the two sets is automatically selected as the output. For example, when the temperature monitoring result of the first set is 305 and the second set is 310, with uncertainties of 3 and 4 respectively, the system determines that the difference of 5 is less than the cumulative value of 7, and ultimately outputs 307.5. This processing mechanism, through quantitative judgment criteria, achieves objective fusion of temperature monitoring results, effectively solving the decision-making problem when there are differences between the two sets of data.

[0105] As an example, when determining the target temperature monitoring result for the reactor pressure vessel, the absolute value of the difference between the first and second temperature monitoring results is first obtained. For instance, assuming the first temperature monitoring result is 320°C and the second temperature monitoring result is 325°C, the absolute value of the difference is 5.

[0106] Next, obtain the sum of the uncertainties between the first and second uncertainties. For example, assuming the first uncertainty is 3 and the second uncertainty is 4, the sum of the uncertainties is 7.

[0107] Then, the absolute value of the difference in monitoring results is compared with the cumulative uncertainty. In this example, the absolute value of the difference in monitoring results (5) is less than the cumulative uncertainty (7).

[0108] Based on the comparison results, the target temperature monitoring result for the reactor pressure vessel is determined. Specifically, since the absolute value of the difference between the monitoring results is less than the cumulative uncertainty, the average value of the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result for the reactor pressure vessel. In this example, the target temperature monitoring result is (320 + 325) / 2 = 322.5.

[0109] Furthermore, if the absolute value of the difference between the monitoring results is not less than the accumulated uncertainty value, then the minimum value between the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel. For example, assuming the first temperature monitoring result is 320°C, the second temperature monitoring result is 330°C, and the absolute value of the difference between the monitoring results is 10, which is greater than the accumulated uncertainty value of 7, then the target temperature monitoring result is taken as 320°C.

[0110] This embodiment enables the selection of a target temperature monitoring result based on the degree of difference and uncertainty range when discrepancies exist between different temperature monitoring results. When the difference is small, using the average value can comprehensively consider the two temperature monitoring results, improving monitoring accuracy. When the difference is large, the minimum value is selected as a conservative estimate to ensure the safe operation of the nuclear reactor. This method improves the accuracy and reliability of core cooling monitoring, helps operators better judge the core cooling status, and thus enhances the overall safety of the nuclear power plant.

[0111] In some of the above-mentioned schemes in this application, when the first temperature monitoring result and the second temperature monitoring result are cross-calibrated, if the availability status of either monitoring result is unavailable, the original cross-calibration logic cannot be effectively executed, resulting in the inability to generate the target temperature monitoring result and affecting the continuous monitoring of the core cooling status.

[0112] In this regard, this application further proposes to cross-calibrate the first temperature monitoring results and the second temperature monitoring results based on the first availability and the first uncertainty, and the second availability and the second uncertainty, to determine the target temperature monitoring results of the reactor pressure vessel, including: In response to either the first availability or the second availability indicating that the monitoring result is unavailable, the third temperature monitoring result, which indicates that the monitoring result is available, is determined as the target temperature monitoring result for the reactor pressure vessel.

[0113] In this embodiment, the availability of temperature monitoring results is indicated by a preset status flag, which is determined by the number of invalid thermocouples detected. When the number of invalid thermocouples in the monitoring channel exceeds a preset proportional threshold, the availability status is switched to unavailable. The selection logic for the third temperature monitoring result is implemented through a hardware voting circuit, which receives two availability status signals in real time and outputs the channel number of the valid monitoring result.

[0114] Specifically, when a large-scale thermocouple failure occurs in the first monitoring channel group, its corresponding first availability status flag is set to unavailable. At this time, the second temperature monitoring result of the second monitoring channel group is directly used as the final output value.

[0115] As an example, we first obtain the first availability and first uncertainty of the first temperature monitoring result, and then obtain the second availability and second uncertainty of the second temperature monitoring result. Here, availability indicates whether the temperature monitoring result is usable, and uncertainty indicates the measurement error range of the temperature monitoring result.

[0116] Furthermore, based on the first availability and first uncertainty, and the second availability and second uncertainty, the first temperature monitoring results and the second temperature monitoring results are cross-calibrated to determine the target temperature monitoring result for the reactor pressure vessel. Specifically, by comparing the availability and uncertainty of the two sets of temperature monitoring results, the more reliable result is selected as the final target temperature monitoring result.

[0117] For example, if either the first availability or the second availability indicates that the monitoring result is unavailable, the first temperature monitoring result and the third temperature monitoring result, which indicates that the monitoring result is available in the second temperature monitoring result, are used as the target temperature monitoring result for the reactor pressure vessel.

[0118] Therefore, by cross-calibrating and filtering the two sets of temperature monitoring results, more accurate and reliable target temperature monitoring results can be obtained, thus improving the accuracy and reliability of core cooling monitoring.

[0119] This embodiment enables cross-calibration and filtering of temperature monitoring results at different locations within the reactor pressure vessel, improving the accuracy and reliability of core cooling monitoring. By comparing the availability and uncertainty of temperature monitoring results from different locations, the more reliable result is selected as the final monitoring result, avoiding the errors that may arise from a single monitoring result. This provides operators with more accurate core temperature information, facilitating the timely detection and handling of core cooling anomalies and improving the operational safety of the nuclear power plant. Furthermore, this approach reduces the difficulty for operators to make judgments due to discrepancies in monitoring results, thereby improving the operational efficiency of the nuclear power plant.

[0120] In some of the embodiments described above in this application, a temperature monitoring result mutual calibration mechanism based on redundant channels is proposed to solve the problem of temperature monitoring discrepancies. However, in this process, the pressure vessel water level monitoring lacks an effective redundant data processing method, which makes the water level monitoring results unreliable due to the failure of a single sensor or noise interference, and may produce erroneous water level information, which is not conducive to the operator accurately judging the core cooling status.

[0121] In this regard, such as Figure 3 As shown, this application further proposes that the method also includes the following steps S310 to S330: S310, acquire multiple pressure vessel water level values ​​monitored in the reactor pressure vessel; S320, statistically analyze the second initial monitoring results corresponding to the water level values ​​of multiple pressure vessels to obtain the second statistical distribution information; S330, based on the second statistical distribution information, determines the target water level monitoring result of the reactor pressure vessel through the first redundant data voting logic.

[0122] Among them, multiple pressure vessel water level values ​​refer to reactor pressure vessel water level measurement data obtained through redundantly deployed sensors. These can be implemented using various types of water level sensing devices such as capacitive water level gauges or ultrasonic water level gauges. The purpose is to avoid monitoring blind spots caused by the failure of a single sensor and to ensure the sufficiency and reliability of the data source. The second initial monitoring result can be understood as the water level monitoring result corresponding to the pressure vessel water level value output by each water level sensor (e.g., water level above the threshold, or water level below the threshold). Its purpose is to provide basic measurement data for subsequent statistical analysis. The second statistical distribution information refers to the data distribution characteristics obtained by statistically analyzing multiple second initial monitoring results. Its purpose is to provide a reliable statistical basis for the voting logic. The first redundant data voting logic refers to the decision rule for determining the target water level monitoring result based on the second statistical distribution information. Its purpose is to output robust water level monitoring results.

[0123] The second statistical distribution information includes the frequency or distribution pattern of each second initial monitoring result. The second redundant data voting logic is a 2-out-of-4 attenuation logic, which can be used to filter the second initial monitoring results during implementation. When applying the 2-out-of-4 attenuation logic, the result that meets the 2-out-of-4 rule is selected from multiple second initial monitoring results as the target water level monitoring result.

[0124] Specifically, multiple pressure vessel water level values ​​are input to the data processing module. First, the corresponding second initial monitoring results are obtained through analysis. Then, these second initial monitoring results are categorized and statistically analyzed to generate a frequency distribution table containing the occurrence counts of each second initial monitoring result. Based on the preset rules of the 2-out-of-4 attenuation logic, target water level monitoring results that meet the criteria are selected.

[0125] This embodiment effectively solves the problem of integrating the results of multi-channel monitoring data. By dynamically adjusting the redundant voting logic, it ensures that reliable parameter monitoring values ​​can still be output during multi-channel monitoring, avoiding misjudgment of the core status by the operator due to excessive data dispersion.

[0126] In some of the solutions described above in this application, when at least one of the indicators of the availability of the second initial monitoring results is unavailable, the original first redundant data voting logic may not be able to effectively handle the change in availability, resulting in a decrease in the reliability of the target parameter monitoring results or the inability to generate them.

[0127] In this regard, this application further proposes that, prior to S330, it also includes: In response to at least one of the third availability indicators of each second initial monitoring result indicating that the monitoring result is unavailable, the number of monitoring results indicating that the monitoring result is unavailable is obtained; Based on the number of monitoring results, the voting logic for the first redundant data is degraded to obtain the voting logic for the second redundant data. The S330 includes: Based on the second statistical distribution information, the target water level monitoring result of the reactor pressure vessel is determined through the second redundant data voting logic.

[0128] In this embodiment, the specific method of degradation processing includes dynamically adjusting the redundancy requirement of the voting logic based on the number of unavailable monitoring results. For example, when the number of second initial monitoring results is four and the first redundant data voting logic uses a two-out-of-four attenuation logic, if one second initial monitoring result is unavailable, the second redundant data voting logic degrades to a two-out-of-three attenuation logic. Furthermore, during the degradation processing, it is necessary to ensure that the number of remaining available monitoring results still meets the minimum redundancy requirement; for example, at least two available second initial monitoring results must be retained before the degraded voting logic can be executed.

[0129] Specifically, when unavailable data exists in the second initial monitoring results, the number of unavailable monitoring results is first counted. For example, if the second initial monitoring results contain data from four independent channels, and the availability indicator of one channel is unavailable, the number of monitoring results is reduced to three. In this case, the original two-out-of-four attenuation logic cannot be directly applied and must be degraded to a two-out-of-three attenuation logic. Furthermore, the degraded second redundant data voting logic will perform a majority vote based on the second statistical distribution information of the remaining three available monitoring results. By dynamically adjusting the redundancy of the voting logic, the continuity and reliability of the monitoring system can be maintained even when some monitoring results are unavailable.

[0130] As an example, four initial parameter monitoring channels are arranged inside the nuclear reactor pressure vessel to measure the pressure vessel water level. When four second initial monitoring results are obtained, the availability status of each channel is first checked. Specifically, if the third availability flag of two monitoring channels is found to be unavailable, the number of unavailable monitoring results is counted as two. At this point, the originally designed two-out-of-four attenuation logic is degraded to a one-out-of-two attenuation logic, and the target water level monitoring result of the reactor pressure vessel is selected using the degraded one-out-of-two attenuation logic.

[0131] Through this embodiment, when some monitoring data is unavailable, the fault-tolerant mechanism of dynamically adjusting the voting logic of redundant data effectively eliminates the impact of unreliable data on the monitoring results, ensuring that reliable core parameter monitoring values ​​can still be output even under partial equipment failure conditions, avoiding the risk of misjudgment due to missing data, and improving the operational reliability of the nuclear reactor safety monitoring system.

[0132] In some of the solutions described above in this application, mechanisms have been considered to improve the reliability of monitoring results for core outlet saturation margin and other key parameters used for post-accident handling. However, for the design input parameters used to calculate core outlet saturation margin, such as analog input signals, including primary loop wide-range and narrow-range pressure signals and containment pressure signals; and digital input signals, including safety injection signals and shutdown signals, existing methods do not provide effective redundant data processing mechanisms. This leads to the failure or ineffectiveness of monitoring results for a single channel, affecting the calculation accuracy of that channel and the overall judgment of the core cooling status.

[0133] In this regard, this application further proposes that the core cooling monitoring method may also include: Acquire multiple core parameter values ​​corresponding to target core parameters obtained from monitoring at different locations within the reactor pressure vessel; the target core parameters are core parameters excluding temperature. Multiple core parameter values ​​are filtered to obtain the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters.

[0134] In this embodiment, parameter value filtering can be implemented in two ways. The first method involves sorting multiple core parameter values ​​in ascending order to form a core parameter value sequence, and then selecting any result in the sequence other than the maximum and minimum values ​​as the target parameter monitoring result. For example, if the three monitored values ​​for neutron fluence are 12.5, 13.0, and 14.2, the sorted sequence is 12.5, 13.0, and 14.2, with the second largest value, 13.0, selected as the target value. The second method involves performing statistical distribution analysis on the initial monitoring results and determining the target value through redundant data voting logic. When some monitoring results are unavailable, the voting logic can dynamically degrade to accommodate the amount of available data. Both filtering methods complement the temperature cross-calibration mechanism, jointly improving the robustness of multi-type parameter monitoring.

[0135] Specifically, after acquiring neutron flux rate monitoring values ​​at different locations, the availability of each monitoring channel is first verified. For the set of monitoring values ​​from available channels, a sequence is generated by sorting the values ​​in ascending order, and the second-to-last value is selected as the final output value. This filtering mechanism effectively avoids distortion of monitoring results caused by a single sensor malfunction by excluding extreme maximum values. Furthermore, when some monitoring channels are unavailable due to faults, the system can switch to statistical distribution analysis mode to determine the target value based on the central tendency of the remaining valid data. For example, if two channels are unavailable out of four coolant flow monitoring values, the remaining two valid values ​​are compared for consistency. If the difference is within a preset tolerance range, the average value is taken; otherwise, an alarm is triggered to prompt manual intervention. This process, through a layered processing strategy, ensures that basic monitoring functions are maintained even when some equipment fails.

[0136] Through the above technical solution, this application can filter and process the design input parameters used for core outlet saturation margin calculation, obtaining more accurate and reliable target parameter monitoring results. This improves the accuracy and reliability of core cooling monitoring, prevents calculation distortion or failure caused by a single fault, and thus better ensures the safe operation of the nuclear reactor.

[0137] In some of the solutions described above in this application, when filtering multiple core parameter values, directly selecting the maximum or minimum value may cause abnormal data interference and affect the reliability of the monitoring results.

[0138] In response, this application further proposes to perform parameter value screening on multiple core parameter values ​​to obtain the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters, including: The core parameter values ​​are sorted in order of magnitude to obtain a core parameter value sequence; The second largest value in the core parameter value sequence is determined as the target parameter monitoring result corresponding to the reactor pressure vessel and the target core parameters.

[0139] In this embodiment, the sorting operation of the core parameter value sequence is achieved by arranging it in ascending or descending order, and the selection logic for the second largest value is based on obtaining the second highest data after excluding the maximum value in the sequence. During the parameter filtering process, the sorting operation and the selection of the second largest value form a continuous data processing link, and the two work together to ensure that abnormally high values ​​are effectively filtered. For example, when the target core parameter is a safety injection signal, if an abnormal safety injection signal is generated in a certain monitoring channel due to a sensor failure, the second largest value selection mechanism can avoid the impact of this abnormal value on the final monitoring result.

[0140] Specifically, after acquiring multiple core parameter values ​​from different locations on the reactor pressure vessel, the parameter values ​​are first sorted in ascending order to generate an ordered sequence. Then, the maximum value in the sequence is skipped, and the second-to-last value is selected as the target parameter monitoring result. This processing method avoids subjective errors introduced by manual judgment through mechanical sorting and fixed-position filtering, while also eliminating the interference of a single abnormally high value on the monitoring results.

[0141] This embodiment effectively solves the technical problem of difficulty in selecting reliable benchmark values ​​when multiple monitoring data points exhibit discrete differences in a redundant monitoring system. By employing mechanical sorting and a second-largest value selection rule, it automatically eliminates potentially abnormally high values ​​while retaining valid monitoring data, ensuring that the output results are both representative and conservatively secure, thus providing stable and reliable data support for accurately determining the core cooling status.

[0142] In some of the above-mentioned schemes in this application, when performing parameter value screening on multiple core parameter values, if the maximum value is directly selected as the target parameter monitoring result, the monitoring result may deviate from the true value due to individual abnormal measurement values, affecting the accuracy of core cooling status judgment.

[0143] In response, this application further proposes to perform parameter value screening on multiple core parameter values ​​to obtain the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters, including: The first initial monitoring results corresponding to multiple core parameter values ​​are statistically analyzed to obtain the first statistical distribution information. Based on the first statistical distribution information, the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters are determined through the first redundant data voting logic.

[0144] In this embodiment, the first statistical distribution information includes the frequency or distribution pattern of each first initial monitoring result. The first redundant data voting logic is a two-out-of-four attenuation logic, which can be used to filter the first initial monitoring results in specific implementations. When applying the two-out-of-four attenuation logic, results that meet the two-out-of-four rule are selected as candidate results from multiple first initial monitoring results. If multiple candidate results that meet the rule exist, a secondary screening can be performed by combining the confidence weight of the measurement channel.

[0145] The specific implementation process of the redundant data voting logic is the same as the pressure vessel water level monitoring process described above, and will not be described in detail here. However, you can refer to the description in the above embodiments.

[0146] This embodiment effectively solves the problem of integrating the results of multi-channel monitoring data. By dynamically adjusting the redundant voting logic, it ensures that reliable parameter monitoring values ​​can still be output during multi-channel monitoring, avoiding misjudgment of the core status by the operator due to excessive data dispersion.

[0147] In some embodiments described above in this application, a mutual calibration mechanism is proposed to determine the target temperature monitoring results of the reactor pressure vessel. However, during its implementation, when the temperature monitoring results are not of the core outlet saturation margin type, the existing mutual calibration logic cannot effectively handle unilateral fault scenarios, resulting in a complex and ambiguous target result generation process, which in turn exacerbates the difficulty for operators in judging the core cooling status.

[0148] In this regard, this application further proposes that the first temperature monitoring result and the second temperature monitoring result are temperature monitoring results other than the core exit saturation margin; S230 includes: In response to a fault indicated by a first temperature monitoring result, the second temperature monitoring result is determined as the target temperature monitoring result for the reactor pressure vessel; or in response to a fault indicated by a second temperature monitoring result, the first temperature monitoring result is determined as the target temperature monitoring result for the reactor pressure vessel. The target temperature monitoring results are output to the display control consoles of the first and second sub-cabinets for display.

[0149] In this embodiment, temperature monitoring results other than the core outlet saturation margin can be achieved using conventional temperature parameters such as core inlet temperature, pressure vessel wall temperature, maximum core outlet temperature signal, and pressure vessel upper head saturation margin signal. The purpose is to clarify the applicable boundaries of the cross-calibration logic and avoid incorrectly applying complex cross-calibration rules applicable to key parameters to other temperature parameters. Responding directly to fault indication and switching monitoring results means that when a fault signal occurs in the monitoring results on either side, the valid side result is immediately adopted. This can be achieved based on signal over-limit judgment or communication interruption detection logic. The purpose is to eliminate redundant calculations and quickly lock the valid monitoring source to prevent result delays. Outputting to the dual-cabinet display control console means synchronizing the target results to physically isolated control terminals. This can be achieved using industrial communication protocols to achieve data synchronization transmission. The purpose is to ensure consistent presentation of monitoring information on different control consoles.

[0150] Specifically, the solution in this application limits the temperature monitoring result type to the accident handling parameters of non-core outlet saturation margin. When the system detects a fault indicated by the first temperature monitoring result or the second temperature monitoring result, it directly adopts the effective side monitoring result as the target temperature monitoring result and synchronously outputs the target result to the display control console of the first sub-cabinet and the second sub-cabinet.

[0151] As a preferred embodiment, the solution of this application is implemented as follows: when monitoring the maximum core outlet temperature of the reactor pressure vessel, if the first temperature monitoring result indicates a fault due to an abnormal thermocouple signal, the system immediately adopts the second temperature monitoring result as the target temperature monitoring result and synchronizes the result to the touch screen display control console of the first and second sub-cabinets for real-time display.

[0152] Through the above scheme, in addition to the core outlet saturation margin, this application also considers the generation process of other key parameters for post-accident handling, eliminates the ambiguity of results in the case of single-sided failure, improves the real-time performance and reliability of core cooling monitoring, and enables operators to obtain unambiguous core status information in real time to accurately judge the cooling status.

[0153] In addition, in conjunction with the core cooling monitoring methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the core cooling monitoring methods in the above embodiments.

[0154] In addition, in conjunction with the core cooling monitoring method in the above embodiments, this application embodiment can provide a computer program product for implementation. When the instructions in the computer program product are executed by the processor of an electronic device, the electronic device performs the core cooling monitoring method provided by any aspect of the above embodiments of this application.

[0155] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0156] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0157] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0158] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0159] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A reactor core cooling monitoring system, characterized in that, The system includes: A parameter monitoring device includes N redundant monitoring channels, each of which is connected to a reactor pressure vessel. The parameter monitoring device monitors the core temperature of the reactor pressure vessel through the monitoring channels, where N is an even number. The signal conditioning cabinet includes a first sub-cabinet and a second sub-cabinet, which are respectively connected to each of the monitoring channels. The first sub-cabinet and the second sub-cabinet are respectively used to cross-calibrate the first temperature monitoring result determined based on the first core temperature group and the second temperature monitoring result determined based on the second core temperature group to determine the target temperature monitoring result of the reactor pressure vessel. The first core temperature group and the second core temperature group each include the core temperature monitored by M different monitoring channels, where M is half of N.

2. The system according to claim 1, characterized in that, In response to the four sets of redundant neutron measurement signals, the N monitoring channels are four monitoring channels; The four monitoring channels are used to construct a first monitoring channel group and a second monitoring channel group, and each of the first monitoring channel group and the second monitoring channel group includes two different monitoring channels. The first monitoring channel group corresponds to the first core temperature group, and the second monitoring channel group corresponds to the second core temperature group.

3. The system according to claim 1, characterized in that, The N monitoring channels are each connected to a different power supply.

4. The system according to claim 1, characterized in that, The system also includes: A severe accident instrumentation and control system, which is connected to any one of the monitoring channels, is used to determine the core accident status of the reactor pressure vessel based on the core temperature monitored by the monitoring channel.

5. The system according to claim 1, characterized in that, Both the first sub-cabinet and the second sub-cabinet are security-grade signal conditioning cabinets based on computer technology.

6. A method for monitoring reactor core cooling, characterized in that, The method is applied to the first sub-cabinet and / or the second sub-cabinet of the core cooling monitoring system according to any one of claims 1-5, and the method includes: The first core temperature group and the second core temperature group of the reactor pressure vessel are obtained; the first core temperature group and the second core temperature group include core temperatures monitored by different monitoring channels. The first temperature monitoring result is determined based on the first core temperature group, and the second temperature monitoring result is determined based on the second core temperature group; The first temperature monitoring result and the second temperature monitoring result are cross-calibrated to determine the target temperature monitoring result of the reactor pressure vessel.

7. The method according to claim 6, characterized in that, The first temperature monitoring result is the core outlet saturation margin; The determination of the first temperature monitoring result based on the first core temperature group includes: Obtain the maximum core outlet temperature in the first core temperature group and the target primary loop absolute pressure of the reactor pressure vessel. The core saturation temperature is determined based on the target primary loop absolute pressure. The difference between the core saturation temperature and the maximum core outlet temperature is determined as the core outlet saturation margin.

8. The method according to claim 6, characterized in that, The step of cross-calibrating the first temperature monitoring result with the second temperature monitoring result to determine the target temperature monitoring result of the reactor pressure vessel includes: Obtain the first availability and first uncertainty of the first temperature monitoring result, and obtain the second availability and second uncertainty of the second temperature monitoring result; Based on the first availability, the first uncertainty, the second availability, and the second uncertainty, the first temperature monitoring result and the second temperature monitoring result are cross-calibrated to determine the target temperature monitoring result of the reactor pressure vessel.

9. The method according to claim 8, characterized in that, The first availability and first uncertainty of obtaining the first temperature monitoring result include: Obtain the number of invalid thermocouples in the first monitoring channel group; the invalid thermocouple is the thermocouple whose temperature measurement value is greater than the average temperature value in the first core temperature group and the difference is greater than a preset threshold. Based on the number of thermocouples, determine the first availability of the first temperature monitoring result; Obtain a first uncertainty curve and a second uncertainty curve. Both the first uncertainty curve and the second uncertainty curve are used to characterize the relationship between the uncertainty of the temperature monitoring result and the change in the primary loop absolute pressure of the reactor pressure vessel. The first uncertainty curve and the second uncertainty curve have different ranges. Based on the maximum core outlet temperature in the first core temperature group, the target uncertainty curve is determined from the first uncertainty curve and the second uncertainty curve; The first uncertainty is determined from the target uncertainty curve based on the target primary loop absolute pressure of the reactor pressure vessel.

10. The method according to claim 8, characterized in that, The step of cross-calibrating the first temperature monitoring result and the second temperature monitoring result based on the first availability, the first uncertainty, the second availability, and the second uncertainty to determine the target temperature monitoring result of the reactor pressure vessel includes: In response to both the first availability and the second availability indicating that the monitoring results are available, the absolute value of the difference between the first temperature monitoring results and the second temperature monitoring results is obtained, as well as the cumulative value of the uncertainty between the first uncertainty and the second uncertainty; Based on the comparison between the absolute value of the difference in the monitoring results and the cumulative value of the uncertainty, the target temperature monitoring result of the reactor pressure vessel is determined.

11. The method according to claim 10, characterized in that, The determination of the target temperature monitoring result of the reactor pressure vessel based on the comparison result of the absolute value of the difference between the monitoring results and the accumulated value of the uncertainty includes: In response to the absolute value of the difference between the monitoring results being less than the accumulated uncertainty value, the average value of the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel. In response to the absolute value of the difference between the monitoring results not being less than the accumulated uncertainty value, the minimum value between the first temperature monitoring result and the second temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel.

12. The method according to claim 8, characterized in that, The step of cross-calibrating the first temperature monitoring result and the second temperature monitoring result based on the first availability, the first uncertainty, the second availability, and the second uncertainty to determine the target temperature monitoring result of the reactor pressure vessel includes: In response to either the first availability or the second availability indicating that the monitoring result is unavailable, the third temperature monitoring result, which indicates that the monitoring result is available, is determined as the target temperature monitoring result of the reactor pressure vessel.

13. The method according to claim 6, characterized in that, The method further includes: Acquire multiple pressure vessel water level values ​​monitored in the reactor pressure vessel; The second initial monitoring results corresponding to the water level values ​​of the multiple pressure vessels are statistically analyzed to obtain the second statistical distribution information. Based on the second statistical distribution information, the target water level monitoring result of the reactor pressure vessel is determined through the first redundant data voting logic.

14. The method according to claim 13, characterized in that, Before determining the target water level monitoring result of the reactor pressure vessel based on the second statistical distribution information and through the first redundant data voting logic, the method further includes: In response to at least one of the third availability indicators of each of the second initial monitoring results indicating that the monitoring result is unavailable, the number of monitoring results indicating that the monitoring result is unavailable is obtained; Based on the number of monitoring results, the first redundant data voting logic is degraded to obtain the second redundant data voting logic. The determination of the target water level monitoring result of the reactor pressure vessel based on the second statistical distribution information and through the first redundant data voting logic includes: Based on the second statistical distribution information, the target water level monitoring result of the reactor pressure vessel is determined through the second redundant data voting logic.

15. The method according to claim 6, characterized in that, The method further includes: Acquire multiple core parameter values ​​corresponding to target core parameters, which are monitored in the reactor pressure vessel; the target core parameters are core parameters other than temperature. The multiple core parameter values ​​are filtered to obtain the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters.

16. The method according to claim 15, characterized in that, The step of filtering the multiple core parameter values ​​to obtain the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters includes: The multiple core parameter values ​​are sorted in order of magnitude to obtain a core parameter value sequence; The second largest value in the core parameter value sequence is determined as the target parameter monitoring result corresponding to the target core parameter of the reactor pressure vessel.

17. The method according to claim 15, characterized in that, The step of filtering the multiple core parameter values ​​to obtain the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters includes: The first initial monitoring results corresponding to the multiple core parameter values ​​are statistically analyzed to obtain the first statistical distribution information. Based on the first statistical distribution information, the target parameter monitoring results corresponding to the reactor pressure vessel and the target core parameters are determined by the first redundant data voting logic.

18. The method according to claim 6, characterized in that, The first temperature monitoring result and the second temperature monitoring result are temperature monitoring results excluding the core outlet saturation margin; The step of cross-calibrating the first temperature monitoring result with the second temperature monitoring result to determine the target temperature monitoring result of the reactor pressure vessel includes: In response to a fault indicated by a first temperature monitoring result, a second temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel; or in response to a fault indicated by a second temperature monitoring result, a first temperature monitoring result is determined as the target temperature monitoring result of the reactor pressure vessel. The target temperature monitoring results are output to the display control consoles of the first sub-cabinet and the second sub-cabinet for display.

19. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the core cooling monitoring method according to any one of claims 6 to 18.

20. A computer program product comprising a computer program that is read and executed by a processor of a computer device, causing the computer device to perform the core cooling monitoring method according to any one of claims 6 to 18.

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