Nuclear fuel cladding tube biaxial creep process monitoring system

Abstract

The invention relates to the technical field of nuclear fuel, in particular to a nuclear fuel cladding tube biaxial creep process monitoring system, which comprises a temperature stress data capture module, a regional state judgment module, a creep rate adjustment module, a thermal control stress regulation and control module and an effect feedback correction module. According to the method, temperature stress data of key parts are collected and subjected to structural conversion, data standardization and usability are improved, space-time information is fused to construct a coupling data table, accurate recognition of thermal stress is supported, the temperature stress trend of a boundary area is jointly analyzed, abnormal fluctuation sections are recognized, and the creep distribution recognition accuracy is improved; the method comprises the steps of analyzing continuous response increments and mutation points, forming a fine feature point set, enhancing strain mutation capture capability, extracting a key interface adjustment value, analyzing response differences before and after adjustment, realizing dynamic monitoring and verification of a control unit, improving regulation and control targeting, identifying an unreached target area through feedback comparison, constructing a return difference compensation mechanism, and realizing dynamic monitoring and verification of the control unit. And the regulation efficiency and the closed-loop regulation and control capability are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of nuclear fuel, and particularly to a monitoring system for the biaxial creep process of a nuclear fuel cladding tube. Background Art

[0002] The technical field of nuclear fuel encompasses aspects such as the research, development, application, and management of nuclear fuel, mainly focusing on the behavior and performance of nuclear fuel in nuclear reactors. The core content of this technical field is the various physical, chemical, and mechanical effects on nuclear fuel in nuclear reactors, including the influence of environmental factors such as temperature, pressure, and radiation. As a protective outer shell for nuclear fuel in nuclear reactors, the nuclear fuel cladding tube undertakes the isolation work between nuclear fuel and coolant to ensure the safe operation of the reactor. With the development of nuclear energy technology, the materials, design, and monitoring technology of nuclear fuel cladding tubes have gradually received attention, especially the impact of creep phenomena on the safety of cladding tubes, which is also one of the key points in current nuclear fuel technology research.

[0003] Among them, the monitoring system for the biaxial creep process of a nuclear fuel cladding tube refers to a system for monitoring the performance of a nuclear fuel cladding tube during the biaxial creep process, mainly solving the problems of real-time monitoring and data analysis of the nuclear fuel cladding tube in the biaxial creep state. By setting corresponding sensors and data acquisition systems, the deformation of the cladding tube under biaxial loads is recorded in real time, especially the stress-strain relationship during the creep process, and then its performance changes are monitored. By monitoring the stress state and material aging process of the cladding tube in the nuclear reactor, an efficient monitoring method is provided to help judge its safety and service life.

[0004] In the prior art, the monitoring of the biaxial creep process of nuclear fuel cladding tubes relies on single-level stress-strain recording means, lacking a systematic framework for structured processing of sensing data and multi-parameter coupling analysis, resulting in relatively one-sided monitoring results. In the extraction of temperature and stress responses, the joint modeling of multi-dimensional factors of space and time is not fully considered, making the anomaly recognition affected by data fluctuations, leading to a relatively high false positive rate and affecting the accuracy of judgment. In the analysis of creep strain behavior, the existing solutions fail to achieve systematic capture of continuous data response increments, and have limited ability to extract strain mutation characteristics, making the control basis lack pertinence and resulting in unsatisfactory intervention effects. At the control execution level, static parameter setting is mainly used, lacking a real-time feedback correction mechanism for the adjustment effect, and unable to effectively identify and compensate for control deviations, making it difficult to form a closed-loop control system. For example, in some operating cycles with frequent temperature fluctuations in certain temperature zones, the existing monitoring fails to timely identify multi-point abnormal linkages, resulting in ineffective intervention in some load concentration areas, posing potential safety hazards and restricting the accuracy and reliability of performance monitoring and life assessment of nuclear fuel cladding tubes in complex service environments. Summary of the Invention

[0005] To solve the technical problems existing in the prior art, an embodiment of the present invention provides a monitoring system for the biaxial creep process of nuclear fuel cladding tubes. The technical solution is as follows: On the one hand, a monitoring system for the biaxial creep process of nuclear fuel cladding tubes is provided, and the system includes: The temperature stress data capture module collects the readings of temperature sensors and stress sensors at key parts of the nuclear fuel cladding tube, extracts the original measurement data of the sensor device number, positioning coordinates, and time nodes, performs a structural conversion on the data format, and generates a local thermal stress basic data table; The regional state determination module extracts the temperature stress data in the area where the fuel pellet is close to the intersection of the inner wall of the cladding tube based on the local thermal stress basic data table, jointly judges the temperature rising trend and the stress concentration frequency, filters out the abnormally fluctuating data segments, marks the load abnormal response area, and obtains a local creep abnormal section distribution map; The creep rate adjustment module arranges the temperature and stress data in chronological order according to the local creep abnormal section distribution map, identifies the positions of sudden changes in response increments, and analyzes the corresponding strain changes to obtain a set of strain mutation response characteristic points; The thermal control stress regulation module calls the set of strain mutation response characteristic points, extracts the flow rate and pressure adjustment values at the annular cooling channel interface and the shell injection port, analyzes the response differences before and after adjustment, and identifies the control units with response amplitude exceeding the limit to obtain a creep control intervention node index table.

[0006] As a further solution of the present invention, the local thermal stress basic data table includes a temperature stress field group, a measuring point spatial attribute, and a time tag sequence. The local creep abnormal section distribution map includes a thermal stress abnormal boundary, a stress concentration area, and a response trend characteristic. The set of strain mutation response characteristic points includes a mutation amplitude identifier, a time positioning node, and a response sequence characteristic. The creep control intervention node index table includes an intervention unit number, a control parameter group, and risk marking information.

[0007] As a further solution of the present invention, the temperature stress data capture module includes: The sensing reading collection sub-module collects the readings of temperature sensors and stress sensors at key parts of the nuclear fuel cladding tube, groups them according to the number and coordinates, marks the missing data, and filters out the invalid data at the same time to obtain a synchronous monitoring data matrix; The space-time parameter reconstruction sub-module extracts the synchronous sampling sequence in the stable period interval based on the spatial coordinates and time nodes of each sensing point in the synchronous monitoring data matrix, splices the temperature and stress values of the coordinate points in the stable period into a time series, and reconstructs the space-time continuous monitoring frame sequence through coordinate mapping to generate a coordinate mapping time series set; The creep stress modeling sub-module screens the biaxial corresponding point groups according to the temperature and stress change curves of the sensing coordinate points in the biaxial directions in the coordinate mapping time series set, extracts the change rate of the principal stress direction and the peak amplitude of the secondary stress direction in the process, and generates a local thermal stress basic data table according to the time series.

[0008] As a further solution of the present invention, the regional state determination module includes: The temperature stress data extraction sub-module extracts the temperature and stress sequences of the nodes in the junction area between the fuel pellet adjacent area and the inner wall of the cladding tube based on the local thermal stress basic data table, arranges them jointly according to the node number and time stamp, identifies the radial and axial temperature gradients and stress gradients, and generates the biaxial temperature stress coupling gradient value; The trend frequency determination sub-module extracts the occurrence frequency of the joint sudden increase of temperature and stress of the nodes in the time series according to the biaxial temperature stress coupling gradient value, identifies the node clusters with the sudden increase frequency exceeding the radial increase threshold and the axial mutation threshold, and obtains the biaxial sudden increase frequency distribution quantity; The abnormal response annotation sub-module calls the biaxial sudden increase frequency distribution quantity, screens the frequency dense sections, calculates the frequency standard deviation, deduces the creep rate of the nodes, identifies the continuous rising interval of the creep rate, and maps the interval to the axial section of the cladding tube according to the spatial structure to obtain the local creep abnormal section distribution map.

[0009] As a further solution of the present invention, the frequency standard deviation adopts the formula: ; Wherein, represents the frequency standard deviation, represents the frequency of the kth frequency, represents the average value of the frequencies of the kth frequency, and m represents the total number of measurement frequency points.

[0010] As a further solution of the present invention, the creep rate adjustment module includes: The abnormal area sequence sorting sub-module identifies the corresponding temperature sequence and stress sequence according to the marked area in the local creep abnormal section distribution map, sorts the node sampling records according to the time stamp, and obtains the area joint time series data; The response increment extraction sub-module calls the area joint time series data, extracts the temperature difference and stress difference between adjacent sampling points, calculates the temperature stress increment between each pair of time points, and identifies the interval range where the increment change rate exceeds the response threshold to obtain the mutation response increment interval; The strain mutation identification sub-module extracts the strain change rate of the nodes in the interval according to the mutation response increment interval, screens the points where the continuous strain change rate suddenly increases, and records the interval position and strain ratio in time sequence to obtain the strain mutation response characteristic point set.

[0011] As a further aspect of the present invention, the thermal control stress regulation module includes: The flow control parameter extraction sub-module calls the risk point data in the strain mutation response feature point set, calls the ring-shaped cooling channel interface and the shell injection port parameters, extracts the flow rate and pressure adjustment values for each time period, merges the data before and after adjustment, analyzes the change in the response amplitude, and generates a thermal control response change interval; The over-limit node identification sub-module compares the change in the response amplitude in the adjusted state with the upper threshold according to the thermal control response change interval, screens the control unit numbers exceeding the threshold, and records the node, response dimension, and time index to obtain a creep control intervention node index table.

[0012] As a further aspect of the present invention, the average change amount of the adjustment value adopts the formula: ; Wherein, represents the average change amount of the adjustment value, represents the instantaneous pressure at the inflow port in the i-th sampling point, represents the effective cross-sectional area of the ring-shaped cooling channel in the i-th sampling point, represents the equivalent resistance of the fluid path in the i-th sampling point, represents the pressure difference before and after adjustment in the i-th sampling point, represents the flow rate adjustment value of the (i - 1)-th sampling point, represents the coefficient of thermal expansion of the fluid in the cooling channel in the i-th sampling point, represents the time interval between the i-th sampling point and the (i - 1)-th sampling point, represents the average value of the flow rate adjustment values of the sampling points within the current time period, represents the total number of sampling points within the current time period.

[0013] As a further aspect of the present invention, the system further includes an effect feedback correction module: The effect feedback correction module collects the stress and strain data after intervention according to the intervention units listed in the creep control intervention node index table, compares the difference with that before intervention, and identifies the sub-regions that do not reach the adjustment target to obtain a dynamic regulation dead zone evaluation list; The dynamic regulation dead zone evaluation list includes a deviation ratio item, an unadjusted and up-to-standard area, and a feedback identification label.

[0014] As a further aspect of the present invention, the effect feedback correction module includes: The creep strain acquisition sub-module collects the axial strain rate, radial strain rate and applied load value at the corresponding time periods before and after intervention according to the creep control intervention node index table, analyzes the biaxial strain change amount and archives and correlates the time series data to generate a biaxial strain change data group of the cladding tube; The offset section identification sub-module calls the biaxial strain change data group of the cladding tube, filters the strain change coordinate points beyond the threshold range according to the biaxial strain reference threshold set initially during loading, locates the deviation range in combination with the pipe section number, and obtains a biaxial offset section index table; The deadband list sorting sub-module extracts the axial and radial strain change amounts at the corresponding coordinates according to the biaxial offset section index table, identifies the deadband degree value of the strain and sorts and classifies it, and organizes the results into a table according to the section number to obtain a dynamic regulation deadband evaluation list.

[0015] The beneficial effects brought by the technical solution provided by the embodiment of the present invention at least include: By collecting the original temperature and stress data of the sensors at the key parts and performing structural conversion, the standardization of the data structure is realized, so that the subsequent processing has high consistency and accuracy, improves the usability and traceability of the original measurement data, combines the spatial positioning and time series of the temperature and stress data to form a data table with spatio-temporal coupling characteristics, provides a basis for accurately identifying the thermal stress state of the material, jointly determines the trend of the temperature stress data in the area near the fuel pellet and the inner wall junction area of the nuclear fuel cladding tube, effectively analyzes the abnormal response section by identifying multi-point abnormal fluctuations, and improves the resolution and accuracy of the local creep distribution identification. By identifying the response increment of the time-continuous data and extracting the mutation points, the response capture ability of the strain mutation behavior during the creep process is strengthened, a more refined feature point set is constructed, which provides an accurate reference for the formulation of subsequent regulation measures, extracts the key interface adjustment values, and analyzes the differences in the responses before and after the adjustment to realize the dynamic response monitoring of the control unit and the verification of the regulation amplitude, enhancing the targeting and effectiveness of the regulation measures. Based on the feedback comparison of the intervention data, the areas where the regulation fails to reach the target are marked, the real-time calibration and compensation identification of the deadband area are realized, a dynamic closed-loop regulation mechanism is constructed, and the regulation efficiency and regulation reliability of the entire monitoring system are improved. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1It is a schematic diagram of a monitoring system for the biaxial creep process of a nuclear fuel cladding tube provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the system framework of the present invention; Figure 3 It is a flowchart of the temperature stress data capture module in the present invention; Figure 4 It is a flowchart of the area state determination module in the present invention; Figure 5 It is a flowchart of the creep rate adjustment module in the present invention; Figure 6 It is a flowchart of the thermal control stress regulation module in the present invention; Figure 7 It is a flowchart of the effect feedback correction module in the present invention. Specific embodiments

[0018] Next, in conjunction with the accompanying drawings, the technical solutions in the present invention will be described.

[0019] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0020] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0021] In the embodiments of the present invention, sometimes subscripts such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0022] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail in conjunction with the accompanying drawings and specific embodiments.

[0023] The embodiments of the present invention provide a monitoring system for the biaxial creep process of a nuclear fuel cladding tube, such as Figure 1-2 shown in the schematic diagram of the monitoring system for the biaxial creep process of the nuclear fuel cladding tube. The system includes: The temperature stress data capture module collects the readings of temperature sensors and stress sensors at key parts of the nuclear fuel cladding tube, extracts the original measurement data of the sensing device numbers, positioning coordinates, and time nodes, performs a structural conversion on the data format, and generates a local thermal stress basic data table; Based on the local thermal stress basic data table, the regional state determination module extracts the temperature stress data located at the junction area between the fuel pellet close zone and the inner wall of the cladding tube, jointly judges the regional temperature rise trend and the stress concentration frequency, filters out the data segments with abnormal fluctuations at multiple points, marks the abnormal load responses in the corresponding areas, and obtains a local creep abnormal section distribution map; According to the marked areas in the local creep abnormal section distribution map, the creep rate adjustment module arranges the temperature and stress sequence data in chronological order within the same area, identifies the response increments between consecutive sampling points on the time axis, analyzes the strain changes corresponding to the positions of the increment mutations, and obtains a set of strain mutation response characteristic points; The thermal control stress regulation module calls the data of the risk points in the set of strain mutation response characteristic points, extracts the flow rate and pressure adjustment values of the annular cooling channel interface and the housing injection port, analyzes the response differences before and after the adjustment, identifies the control units with response amplitudes exceeding the limit, and obtains a creep control intervention node index table; According to the intervention units listed in the creep control intervention node index table, the effect feedback correction module collects the stress and strain data after the intervention, compares the differences with those before the intervention, and identifies the sub-regions that do not reach the adjustment target, obtaining a dynamic regulation back difference evaluation list.

[0024] The local thermal stress basic data table includes a temperature stress field group, the spatial attributes of the measurement points, and a time tag sequence. The local creep abnormal section distribution map includes thermal stress abnormal boundaries, stress concentration areas, and response trend characteristics. The set of strain mutation response characteristic points includes mutation amplitude identifications, time positioning nodes, and response sequence characteristics. The creep control intervention node index table includes intervention unit numbers, control parameter groups, and risk marking information. The dynamic regulation back difference evaluation list includes deviation ratio items, unadjusted and up-to-standard areas, and feedback identification labels.

[0025] Specifically, as Figure 2 、 3 shown, the temperature stress data capture module includes: The sensing reading collection sub-module collects the readings of temperature sensors and stress sensors at key parts of the nuclear fuel cladding tube, groups them according to the numbers and coordinates, marks the missing data, and filters out the invalid data at the same time to obtain a synchronous monitoring data matrix; Temperature and stress sensor readings are collected from key locations on the nuclear fuel cladding tubes. These sensors are installed at various locations to monitor real-time status and provide essential data for subsequent analysis. After data collection, they are grouped according to sensor number and spatial coordinates. This allows for orderly storage of each sensor's data based on its installation location and number, ensuring that data can be located and processed according to spatial location and number. Missing data is also marked. Missing data is caused by sensor failure or external factors. This marking process helps avoid inaccuracies caused by missing data in subsequent analysis. Invalid data, such as anomalous readings or irrelevant values, is filtered out. This data does not contribute to the results, resulting in a cleaner and more accurate dataset. For example, if a data point on temperature sensor 1 reads -999, indicating a sensor failure, it is marked as missing data and excluded from subsequent analysis. The result is a synchronized monitoring data matrix containing valid data from each sensor at different points in time and space, providing a foundation for further spatiotemporal analysis.

[0026] The spatiotemporal parameter reconstruction submodule extracts the synchronous sampling sequence of the stable period interval based on the spatial coordinates and time nodes of each sensing point in the synchronous monitoring data matrix, splices the temperature and stress values of the coordinate point within the stable period into time series, reconstructs the spatiotemporal continuous monitoring frame sequence through coordinate mapping, and generates a coordinate mapping time series set; The spatial coordinates and time nodes of each sensor point are extracted from the synchronous monitoring data matrix. The spatial coordinates of the data represent the location of each sensor, while the time nodes correspond to the time of each sensor reading. This extracts a synchronous sampling sequence within the stable period interval. Sensor readings within this period are relatively stable and can more accurately reflect normal operating conditions. A stable period refers to a period in which the system temperature and stress values fluctuate minimally, reaching a stable state. After extracting the synchronous sampling sequence, the temperature and stress values of each sensor within the stable period are spliced into a time series. This means that the values of each sensor at multiple time nodes are connected to form a continuous time series data. By performing coordinate mapping on the data, data from different coordinate points can be combined to form a spatiotemporally continuous monitoring frame sequence. This sequence can effectively display temperature and stress changes over different time and space. For example, assuming that the temperature value of a sensor is [100°C, 102°C, 101°C, 100.5°C] and the stress value is [200 MPa, 198 MPa, 199 MPa, 201 MPa] during a stable period, the data will be spliced into a time series according to the time nodes, and a spatiotemporal monitoring sequence will be formed through coordinate mapping to generate a coordinate mapping time series set, which will contain the complete spatiotemporal trajectory of the data and provide detailed information for subsequent stress analysis and thermal control.

[0027] The creep stress modeling sub-module screens the biaxial corresponding point groups according to the temperature and stress change curves of the sensing coordinate points in the biaxial directions in the coordinate mapping time series set, extracts the change rate of the principal stress direction and the peak amplitude of the secondary stress direction in the process, and generates a local thermal stress basic data table according to the time series; Based on the analysis of the temperature and stress change curves of the sensing coordinate points in the biaxial directions in the coordinate mapping time series set, the biaxial directions refer to the influence of the temperature and stress changes in two directions under a two-dimensional coordinate system, which are the principal stress direction and the secondary stress direction. According to the change curves, the coordinate point groups with obvious change trends in the biaxial directions are screened out. The point groups represent the stress and temperature change data at different positions. The change rate of the principal stress direction and the peak amplitude of the secondary stress direction in the process are extracted. The change rate of the principal stress direction can be obtained by calculating the change rate of the temperature and stress in the time series. For example, the change rate of the temperature can be calculated by the ratio of the temperature change (ΔT) between two points to the time change (Δt). Similarly, the change rate of the stress can also be calculated. The peak amplitude of the secondary stress direction is the difference between the maximum stress value and the minimum stress value extracted from all time nodes, which is used to reflect the fluctuation amplitude of the secondary stress. Through data processing, a local thermal stress basic data table can be generated. The table will record the temperature and stress data of each sensor point in the time series, as well as their change rates and peak amplitudes, which become the basic data for subsequent creep analysis and thermal stress evaluation.

[0028] Specifically, as Figure 2 、 4 shown, the regional state determination module includes: The temperature stress data extraction sub-module extracts the temperature and stress sequences of the nodes at the junction of the fuel pellet adjacent area and the inner wall of the cladding tube based on the local thermal stress basic data table, arranges them jointly according to the node number and time stamp, identifies the radial and axial temperature gradients and stress gradients, and generates the biaxial temperature stress coupling gradient value; Extract the temperature and stress sequences of the nodes at the junction between the fuel pellet adjacent area and the inner wall of the cladding tube from the basic data table of local thermal stress. The selection of nodes is based on spatial location. The junction between the fuel pellet adjacent area and the inner wall of the cladding tube is the area where the temperature and stress change relatively violently in the system. Arrange the temperature and stress data jointly according to the node number and time stamp, so as to ensure that the data is accurately sorted according to time and position, which is convenient for subsequent analysis, and the temperature and stress data sequences at different time points and different nodes can be obtained, and calculate the radial and axial temperature gradients and stress gradients between nodes. The radial temperature gradient and stress gradient refer to the temperature and stress differences between adjacent nodes in the radial direction, and the axial gradient refers to the temperature and stress changes along the axis of the cladding tube. For example, assume that the temperature of a certain node is 100 °C and the temperature of the adjacent node in the radial direction is 98 °C, then the radial temperature gradient is 2 °C. Through similar calculations, generate the biaxial temperature-stress coupling gradient value, which includes the temperature and stress gradients in the radial and axial directions. The gradient value can reflect the thermal stress distribution state of the system and provide a basis for subsequent analysis.

[0029] The trend frequency determination sub-module extracts the occurrence frequency of the joint sudden increase of temperature and stress of the nodes in the time series according to the biaxial temperature-stress coupling gradient value, identifies the node clusters whose sudden increase frequencies exceed the radial increase threshold and the axial mutation threshold, and obtains the biaxial sudden increase frequency distribution quantity; According to the biaxial temperature-stress coupling gradient value, analyze the occurrence frequency of the joint sudden increase of temperature and stress of each node in the time series. The joint sudden increase refers to the situation where the temperature and stress increase significantly at the same time node. For example, assume that the temperature of a certain node at time t1 is 150 °C and the stress is 250 MPa, and the temperature at time t2 is 160 °C and the stress is 270 MPa, then it can be considered that the temperature and stress have a sudden increase. Count the occurrence frequency of the sudden increase of all nodes in the time series. If the sudden increase frequency of a certain node exceeds the set threshold, then this node will be identified as having a sudden increase phenomenon. The set threshold includes the radial increase threshold and the axial mutation threshold. The radial increase threshold is set according to experimental data or original records, and the axial mutation threshold is set based on the maximum tolerable change range. For example, assume that the radial sudden increase threshold is 5 times and the axial mutation threshold is 3 times. If the sudden increase frequency of a certain node exceeds these two thresholds within a period of time, then this node will be identified as an over-limit node and added to the node cluster, and finally the biaxial sudden increase frequency distribution quantity is generated.

[0030] The abnormal response annotation sub-module calls the biaxial sudden increase frequency distribution quantity, screens the frequency dense sections, calculates the frequency standard deviation, deduces the creep rate of the nodes, identifies the continuously increasing interval of the creep rate, and maps the interval to the axial section of the cladding tube according to the spatial structure to obtain the local creep abnormal section distribution map; Call the double-axon ascending frequency distribution quantity, and screen the sections with dense frequencies. The section with dense frequencies refers to the situation where the ascending frequencies of multiple nodes are relatively high within a certain period of time, indicating abnormal changes. After screening out the sections with dense frequencies, deduce the creep rate of the nodes. The creep rate is usually calculated based on the relationship between the stress change of the node and time. Suppose the stress of a certain node is 200 MPa at time t1 and 210 MPa at time t2, then the creep rate can be expressed as: (stress difference) / (time difference)=(210 - 200) / (t2 - t1). After calculating the creep rate, identify the interval where the creep rate continuously increases, indicating that within the interval, the creep rate of the node continues to increase, suggesting that it is about to enter an abnormal state. Map the interval with continuously increasing creep rate to the axial section of the cladding tube according to the spatial structure, so as to visually display the creep anomalies at each position; Frequency standard deviation, using the formula: ; Among them, represents the frequency standard deviation, represents the frequency of the kth frequency, represents the average value of the frequencies of the kth frequency, and m represents the total number of measured frequency points; The frequency standard deviation refers to the degree of dispersion of the frequency values of each measured frequency point relative to the average value of all frequencies, which is used to measure the magnitude of the fluctuation of the frequency among each sampling point. The larger the value, the more obvious the difference in the frequencies appearing in different regions of the frequency response. Through this index, the abnormally dense sections in the frequency distribution can be identified, providing basic data support for subsequent creep analysis; The screening of the sections with dense frequencies depends on the degree of fluctuation of the frequency distribution. This formula is used to calculate the average value of the absolute deviations between the frequencies of each frequency point and the average frequency, which is defined as the frequency standard deviation parameter , and this parameter is used to identify the frequency sections with large deviations from the average value, providing a basis for regional screening before deducing the creep rate; : The frequency of the kth measured frequency point, with the unit of Hz. This value is obtained by recording the high-frequency dynamic response through an array of micro acceleration sensors arranged on the surface of the cladding tube material, using a high-speed sampling system to acquire vibration data at a frequency of 20 kHz, converting it to the frequency domain representation through the fast Fourier transform (FFT), and taking the number of frequency peaks appearing in the analysis window, with the dimension of times; : The average value of all frequencies, obtained by summing all the values and then dividing by the number of frequency points m, with the unit of Hz, ensuring consistency with ; m: The total number of frequency sampling points. In this example, 12 frequency points are collected in the data window collected by the sensor array (i.e., m=12). Multi-point parallel sampling equipment is used to record the response of different cross-sections of the cladding tube. The frequency of each frequency point is the number of main frequency occurrences within the set interval after sensor sampling and frequency domain analysis. The data source is 5-minute periodic sampling, and the main peak after removing the noise background is retained for statistics. Set frequency sample: ; Calculate the average frequency: ; Compute the sum of absolute deviations: ; Calculate the frequency standard deviation: The frequency standard deviation is 3.77 Hz, which represents the average fluctuation amplitude of each frequency in this data sample. Screening out the frequency segment higher than the average value plus the fluctuation amplitude helps to locate the abnormal creep active area for structural mapping and subsequent derivation.

[0031] Specifically, if Figure 2 、 5 As shown, the creep rate adjustment module includes: The abnormal area sequence arrangement submodule identifies the corresponding temperature series and stress series according to the marked areas in the local creep abnormal area distribution map by area number, sorts the node sampling records according to the timestamp, and obtains the regional joint time series data; Analysis is performed based on the marked regions in the local creep anomaly segment distribution map. These marked regions are identified as anomaly segments through preliminary temperature and stress data analysis and frequency-intensive screening, representing high-risk areas for creep. Temperature and stress series corresponding to these regions are extracted sequentially. Data for each region includes the temperature and stress variations at each node within the region. The sampling records for each node are sorted by timestamp to ensure that the temperature and stress data for each node are arranged in chronological order for time series analysis. This sorting ensures that the temperature and stress data for each node reflect their temporal trends. This process ultimately yields regional joint time series data, which demonstrates the temporal variations of temperature and stress for all nodes within each marked region, providing a foundation for subsequent incremental analysis and identification of sudden changes. For example, suppose the node temperatures within a marked region are 150°C at time t1 and 155°C at time t2, and the stresses are 200 MPa and 205 MPa, respectively. After sorting, the data are organized into chronological time series data for further analysis.

[0032] The response increment extraction sub-module calls the regional combined time series data, extracts the temperature difference and stress difference between adjacent sampling points, calculates the temperature-stress increment between each pair of time points, and identifies the range of intervals where the increment change rate exceeds the response threshold, obtaining the mutation response increment interval. Call the regional combined time series data, extract the temperature and stress differences of each adjacent sampling point. The difference represents the change amplitude of temperature and stress between two time points. For example, assume the temperature of a certain node at time t1 is 150°C and the stress is 200 MPa, and at time t2 the temperature is 155°C and the stress is 205 MPa. Then the temperature difference is 5°C and the stress difference is 5 MPa. Calculate the temperature-stress increment between each pair of adjacent time points. The temperature-stress increment can be expressed as the combined change amount of temperature difference and stress difference, and can be obtained through simple difference calculation. Identify the range of intervals where the increment change rate exceeds the response threshold. The response threshold is set according to design requirements or original data, and is used to screen out those intervals with large changes in temperature-stress increment. For example, if the response threshold is 0.1°C / Mpa / s, by calculating the temperature-stress increment change rate in each time period, identify the intervals where the change rate exceeds this threshold. For example, if in a certain time period, the increment change rate of temperature and stress is 0.2°C / Mpa / s, exceeding the set threshold, then this interval will be marked as the mutation response increment interval and become the key section for subsequent analysis.

[0033] The strain mutation identification sub-module extracts the strain change rate of the interval nodes according to the mutation response increment interval, screens out the points where the continuous strain change rate suddenly increases, records the interval position and strain ratio in chronological order, and obtains the strain mutation response feature point set. According to the mutation response increment interval, extract the strain change rate of the interval nodes. The strain change rate is obtained by calculating the ratio of the strain change amount to the time change amount between adjacent time nodes. For example, if the strain at time point t1 is 0.01% and the strain at time point t2 is 0.015%, and the time difference is 2 seconds, then the strain change rate is (0.015% - 0.01%) / (2 seconds) = 0.0025% / second. Analyze the strain change rate, screen out the points where the continuous strain change rate suddenly increases. The sudden increase in the strain change rate means an abnormal change or critical state. Therefore, pay special attention to the suddenly increasing points. The screened suddenly increasing points will be recorded in chronological order, and the strain ratio (i.e., the ratio of the strain change amount to the time change amount) of each point will be recorded together. By recording, the strain mutation response feature point set will be obtained. This feature point set contains all the nodes within the mutation response increment interval and with a significant increase in the strain change rate and their related information. The point set will provide an important basis for subsequent strain analysis and fault prediction.

[0034] Specifically, as Figure 2 , 6 shown, the thermal control stress regulation module includes: The flow control parameter extraction sub-module calls the risk point data of the strain mutation response feature point set, calls the annular cooling channel interface and the shell injection port parameters, calculates the average change amount of the adjustment value, merges the data before and after adjustment, analyzes the change of the response amplitude, and generates the thermal control response change interval; Extract data from the strain mutation response feature point set. This data represents the system strain changes under different working conditions and reflects the physical changes of each node. By calling the parameters of the annular cooling channel interface and the shell injection port, the real-time change data of temperature, pressure and flow rate can be further obtained. In order to further adjust the temperature and pressure in the system, it is crucial to extract the flow rate and pressure adjustment values in each time period. This can clearly understand the working state of temperature control in each time period and provide data support for subsequent analysis. By merging the data before and after adjustment and comparing the response amplitude changes of the system in different states, it helps to determine the performance under different adjustment states. Finally, the thermal control response change interval is generated, which can be used as reference data for subsequent optimization and fault warning. For example, assume that in a certain time period, the flow rate adjustment value is 2 L / min and the pressure is 1.5 MPa. In the next time period, the flow rate becomes 2.5 L / min and the pressure is 1.6 MPa. After merging and comparison, the response change amplitude of this time period can be obtained, and this interval can accurately reflect the fluctuation degree of the temperature control system; The average change amount of the adjustment value represents the absolute deviation degree of each adjustment value relative to the overall average level after multiple adjustment samplings of the fluid flow rate within the selected time period, and is used to measure the fluctuation intensity of the flow rate adjustment response during this time period. By quantifying the instantaneous inflow pressure of each sampling, the effective cross-sectional area of the cooling channel, the equivalent resistance, the pressure change amount, the adjustment flow rate value at the previous sampling, the fluid thermal expansion coefficient, and the sampling time interval, and taking the mean of the adjustment value sequence calculated by combining the data of each point and comparing it with the original average adjustment value, the change trend of the adjustment response behavior of this time period compared with the long-term reference state is finally obtained. This value reflects the instantaneous response ability of the flow control and its stability and adjustment intensity during the operation cycle; The average change amount of the adjustment value uses the formula: ; where, represents the average change amount of the adjustment value, represents the instantaneous pressure at the inflow port in the i-th sampling point, represents the effective cross-sectional area of the annular cooling channel in the i-th sampling point, represents the equivalent resistance of the fluid path in the i-th sampling point, represents the pressure difference before and after adjustment at the $i$-th sampling point, represents the flow rate adjustment value at the $(i - 1)$-th sampling point, represents the coefficient of thermal expansion of the fluid in the cooling channel at the $i$-th sampling point, represents the time interval between the $i$-th sampling point and the $(i - 1)$-th sampling point, represents the average value of the flow rate adjustment values of the sampling points within the current time period, represents the total number of sampling points within the current time period; Each parameter in the formula is obtained through data monitoring, collection, or calculation. The following are the specific formula parameters and the calculation derivation process: (unit: Pascal, Pa) represents the instantaneous pressure at the inlet port during the $i$-th sampling. This parameter is obtained through real-time monitoring by a fluid pressure sensor. Assume the pressure during the $i$-th sampling is Pa; (unit: square meter, m²) represents the effective cross-sectional area of the annular cooling channel during the $i$-th sampling. It is obtained by referring to the design specification and is set as m²; (unit: Pascal per cubic meter, Pa / m³) represents the equivalent resistance of the fluid path during the $i$-th sampling. It is calculated according to the fluid dynamics calculation formula and the physical characteristics of the channel. Let be Pa / m³; (unit: Pascal, Pa) represents the pressure difference before and after adjustment during the $i$-th sampling. It is also obtained from the difference between two readings of the pressure sensor. Let be Pa; (unit: cubic meter per second, m³ / s) represents the flow rate adjustment value at the $(i - 1)$-th sampling. It is obtained through real-time monitoring by a flow meter. Let be m³ / s; (unitless) represents the coefficient of thermal expansion of the fluid in the cooling channel during the $i$-th sampling. It is calculated according to the physical property table of the fluid and the ambient temperature. Let be ; (unit: second, s) represents the time interval between the $i$-th sampling and the $(i - 1)$-th sampling. It is obtained by a time recording device. Let be s; (Unit: cubic meters per second, m³ / s) represents the mean value of the flow rate adjustment values at all sampling points during the current time period, obtained through statistical analysis of the original data. Let be m³ / s; represents the total number of sampling points during the current time period. This value is a set or statistical value. Let be ; First, calculate the flow rate adjustment value of a single sample: ; Then, find the average value of all samples and calculate : ; This result indicates that the average flow rate adjustment change value during the current time period is cubic meters per second. The data reflects the immediate response of the flow rate adjustment mechanism and provides basic data for the next step of fluid dynamics analysis.

[0035] The over-limit node identification sub-module compares the response amplitude change in the adjustment state with the upper limit threshold according to the thermal control response change interval, screens the control unit numbers that exceed the threshold, and records the node, response dimension, and time index to obtain the creep control intervention node index table; Through the thermal control response change interval for comparative analysis, the over-limit response nodes in the system are identified. The thermal control response change interval defines the temperature control response range of the system in different states. The maximum value within this range is the upper limit threshold. By comparing the response amplitude change in the current adjustment state with the set upper limit threshold, it can be determined whether some control units exceed the predetermined tolerance. Specifically, during operation, first monitor the response amplitude change, record the real-time fluctuations of the response values, and then compare them with the set upper limit threshold one by one. If the response amplitude of a certain unit is greater than the threshold, the unit is screened out and its number is recorded. For example, assume that the response amplitude of a certain control unit is 10, and the set upper limit threshold is 8. Then this unit will be marked as an over-threshold unit, and the node number, response dimension, and corresponding time index of this unit will be noted in the record. Screen the over-limit nodes to obtain the creep control intervention node index table. This table will be used for subsequent regulation and intervention to ensure long-term stable operation.

[0036] Specifically, as shown in Figure 2 , 7 , the effect feedback correction module includes: The creep strain acquisition sub-module collects the axial strain rate, radial strain rate, and applied load values at the corresponding time periods before and after the intervention according to the creep control intervention node index table, analyzes the biaxial strain change amount, and archives and correlates the time series data to generate the biaxial strain change data group of the cladding tube; According to the creep control intervention node index table, find the specified control intervention node, and obtain the axial strain rate, radial strain rate and applied load value of the node during the corresponding time periods before and after the intervention. The axial strain rate refers to the ratio of the strain change of the node in the axial direction to the time change within the specified time period. Similarly, the radial strain rate represents the strain change rate of the node in the radial direction. The applied load value refers to the external load applied to the node during this time period. For example, between time t1 and t2, assuming that the axial strain rate change of a certain node is 0.005% / s, the radial strain rate change is 0.003% / s, and the applied load is 1000 N, calculate the change amount of the biaxial strain according to the parameters, which includes the comprehensive change of temperature and stress. Through this calculation, the overall trend of the strain in the biaxial direction can be analyzed. The calculation results will be archived and associated into time series data for subsequent processing. The data is organized into a biaxial strain change data group of the cladding tube, which includes the strain rate and load data in different directions at different time nodes. The data can provide support for further analysis and prediction.

[0037] The offset section identification sub-module calls the biaxial strain change data group of the cladding tube, filters the strain change coordinate points that exceed the threshold range according to the initially set biaxial strain reference threshold during loading, and locates the deviation range in combination with the pipe section number to obtain the biaxial offset section index table; Call the biaxial strain change data group of the cladding tube, analyze the axial and radial strain changes of each node, and filter the strain change coordinate points that exceed the threshold range according to the initially set biaxial strain reference threshold during loading. The biaxial strain reference threshold is a value set according to engineering experience or specifications, and is used to judge whether abnormal strain changes occur. For example, assuming that the biaxial strain reference threshold is set to an axial strain of 0.01% / s and a radial strain of 0.005% / s, when the axial strain change of a certain node exceeds 0.01% / s and the radial strain change exceeds 0.005% / s, mark this node as abnormal, and locate the strain change coordinate points that exceed the range in combination with the pipe section number. The pipe section number is used to indicate the location where the abnormal strain change occurs for positioning and subsequent processing. Organize all the coordinate points of the abnormal strain changes and their pipe section numbers into a biaxial offset section index table, which provides a marked area for subsequent analysis.

[0038] The deadband list sorting sub-module extracts the axial and radial strain change amounts at the corresponding coordinates according to the biaxial offset section index table, identifies the deadband degree values of the strain and sorts and classifies them, and organizes the results into a table according to the section number to obtain the dynamic regulation deadband evaluation list; Extract the axial and radial strain change amounts of each coordinate point according to the biaxial offset section index table. The strain change amount represents the strain change of each node in different time periods, and calculate the strain hysteresis degree value. The strain hysteresis degree value refers to the difference between the strain change amount of a node and the expected strain change amount within a certain time period. For example, assume that the actual axial strain change amount of a certain node between time periods t1 and t2 is 0.015%, while the expected strain change amount is 0.01%, then the strain hysteresis degree value is 0.015% - 0.01% = 0.005%. Sort the hysteresis degree values and classify them according to the magnitude of the hysteresis degree to help determine which nodes' strain changes deviate from the expected range. Organize the sorted strain hysteresis degree values into a table according to the section numbers to obtain a dynamic regulation hysteresis evaluation list, which can help engineers identify the areas that need dynamic adjustment.

[0039] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A monitoring system for the biaxial creep process of a nuclear fuel cladding tube, characterized in that The system includes: The temperature stress data capture module collects the readings of temperature sensors and stress sensors at key parts of the nuclear fuel cladding tube, extracts the original measurement data of the sensor device numbers, positioning coordinates, and time nodes, performs a structural conversion on the data format, and generates a local thermal stress basic data table; The regional state determination module, based on the local thermal stress basic data table, extracts the temperature stress data in the area where the fuel pellet is close to the inner wall of the cladding tube, jointly judges the temperature rising trend and the stress concentration frequency, filters out the abnormally fluctuating data segments, marks the load abnormal response areas, and obtains a local creep abnormal section distribution map; The creep rate adjustment module arranges the temperature and stress data in chronological order according to the local creep abnormal section distribution map, identifies the positions of sudden changes in response increments, and analyzes the corresponding strain changes to obtain a set of strain mutation response characteristic points; The thermal control stress regulation module calls the set of strain mutation response characteristic points, extracts the flow rate and pressure adjustment values of the annular cooling channel interface and the housing injection port, analyzes the response differences before and after adjustment, and identifies the control units with response amplitude exceeding the limit to obtain a creep control intervention node index table.

2. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 1, characterized in that: The local thermal stress basic data table includes a temperature stress field group, spatial attributes of measurement points, and a time tag sequence. The local creep abnormal section distribution map includes thermal stress abnormal boundaries, stress concentration areas, and response trend characteristics. The set of strain mutation response characteristic points includes mutation amplitude identifiers, time positioning nodes, and response sequence characteristics. The creep control intervention node index table includes intervention unit numbers, control parameter groups, and risk marking information.

3. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 1, wherein: The temperature stress data capture module includes: The sensing reading collection sub-module collects the readings of temperature sensors and stress sensors at key parts of the nuclear fuel cladding tube, groups them according to the numbers and coordinates, marks the missing data, and filters out the invalid data at the same time to obtain a synchronous monitoring data matrix; The space-time parameter reconstruction sub-module extracts the synchronous sampling sequences in the stable period interval based on the spatial coordinates and time nodes of each sensing point in the synchronous monitoring data matrix, splices the temperature and stress values of the coordinate points in the stable period in time series, and reconstructs the space-time continuous monitoring frame sequence through coordinate mapping to generate a coordinate mapping time series set; The creep stress modeling sub-module, according to the temperature and stress change curves of the sensing coordinate points in the biaxial direction in the coordinate mapping time series set, filters out the biaxial corresponding point groups, extracts the change rate of the principal stress direction and the peak amplitude of the secondary stress direction in the process, and generates a local thermal stress basic data table in time series.

4. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 3, characterized in that: The regional state determination module includes: The temperature stress data extraction sub-module, based on the local thermal stress basic data table, extracts the temperature and stress sequences of the nodes in the area where the fuel pellet is close to the inner wall of the cladding tube, jointly arranges them according to the node numbers and time stamps, identifies the radial and axial temperature gradients and stress gradients, and generates a biaxial temperature stress coupling gradient value; The trend frequency determination sub-module extracts the occurrence frequency of the combined sudden rise of temperature and stress at nodes in the time series based on the biaxial temperature-stress coupling gradient value, identifies the node clusters with the sudden rise frequency exceeding the radial rise threshold and the axial mutation threshold, and obtains the biaxial sudden rise frequency distribution quantity; The abnormal response annotation sub-module calls the biaxial sudden rise frequency distribution quantity, screens the frequency-dense sections, calculates the frequency standard deviation, deduces the creep rate of the nodes, identifies the continuously rising interval of the creep rate, and maps the interval to the axial section of the cladding tube according to the spatial structure, obtaining the local creep abnormal section distribution map.

5. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 4, characterized in that: The frequency standard deviation adopts the formula: ； Among them, represents the frequency standard deviation, represents the frequency of the k-th frequency, represents the average value of the frequency of the k-th frequency, and m represents the total number of measured frequency points.

6. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 4, wherein: The creep rate adjustment module includes: The abnormal area sequence sorting sub-module identifies the corresponding temperature sequence and stress sequence according to the marked areas in the local creep abnormal section distribution map, sorts the node sampling records according to the timestamp, and obtains the area combined time series data; The response increment extraction sub-module calls the area combined time series data, extracts the temperature difference and stress difference between adjacent sampling points, calculates the temperature-stress increment between each pair of time points, and identifies the interval range where the increment change rate exceeds the response threshold, obtaining the mutation response increment interval; The strain mutation identification sub-module extracts the strain change rate of the nodes in the interval according to the mutation response increment interval, screens the points with continuous sudden increase in the strain change rate, records the interval positions and strain ratios in chronological order, and obtains the strain mutation response feature point set.

7. The biaxial creep process monitoring system for nuclear fuel cladding tubes according to claim 6, characterized in that: The thermal control stress regulation module includes: The flow control parameter extraction sub-module calls the risk point data in the strain mutation response feature point set, calls the parameters of the annular cooling channel interface and the shell injection port, extracts the flow rate and pressure adjustment values for each time period, merges the data before and after adjustment, analyzes the change in the response amplitude, and generates the thermal control response change interval; The over-limit node identification sub-module compares the change in the response amplitude in the regulated state with the upper limit threshold according to the thermal control response change interval, screens the control unit numbers exceeding the threshold, and records the nodes, response dimensions, and time indices, obtaining the creep control intervention node index table.

8. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 7, wherein: The average change amount of the adjustment value adopts the formula: ； Among them, represents the average change in the adjustment value, represents the instantaneous pressure at the inlet port in the i-th sampling point, represents the effective cross-sectional area of the annular cooling channel in the i-th sampling point, represents the equivalent resistance of the fluid path in the i-th sampling point, represents the pressure difference before and after adjustment in the i-th sampling point, represents the flow adjustment value at the (i - 1)-th sampling point, represents the coefficient of thermal expansion of the fluid in the cooling channel in the i-th sampling point, represents the time interval between the i-th sampling point and the (i - 1)-th sampling point, represents the mean of the flow adjustment values of the sampling points within the current time period, represents the total number of sampling points within the current time period.

9. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 1, characterized in that: The system further includes an effect feedback correction module: The effect feedback correction module collects the stress-strain data after intervention according to the intervention units listed in the creep control intervention node index table, compares the difference with that before intervention, and identifies the sub-regions that do not reach the adjustment target, obtaining the dynamic regulation back-off evaluation list; The dynamic regulation back-off evaluation list includes a deviation ratio item, an unregulated compliance area, and a feedback identification label.

10. The monitoring system for the biaxial creep process of the nuclear fuel cladding tube according to claim 9, characterized in that: The effect feedback correction module includes: The creep strain acquisition sub-module collects the axial strain rate, radial strain rate, and applied load value in the corresponding time periods before and after intervention according to the creep control intervention node index table, analyzes the biaxial strain change amount, and archives and correlates the time series data, generating the biaxial strain change data group of the cladding tube; The offset section identification sub-module calls the biaxial strain change data group of the cladding tube, screens the strain change coordinate points exceeding the threshold range according to the initially set biaxial strain reference threshold during loading, and locates the deviation range in combination with the pipe section number, obtaining the biaxial offset section index table; The dead-band list sorting sub-module extracts the axial and radial strain change amounts at the corresponding coordinates according to the biaxial offset section index table, identifies the dead-band degree value of the strain and sorts and classifies it, and organizes the results into a table according to the section number to obtain the dynamic regulation dead-band evaluation list.

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