A monitoring system for the biaxial creep process of nuclear fuel cladding tubes

Abstract

The present invention relates to the field of nuclear fuel technology, and specifically to a biaxial creep process monitoring system for nuclear fuel cladding tubes. The system includes a temperature stress data capture module, a regional state determination module, a creep rate adjustment module, a thermal control stress regulation module, and an effect feedback correction module. In the present invention, by collecting temperature stress data of key locations and performing structural conversion, data standardization and usability are improved. Spatiotemporal information is fused to construct a coupled data table, supporting accurate identification of thermal stresses. Temperature stress trends in boundary areas are jointly analyzed to identify abnormal fluctuation sections, improving the accuracy of creep distribution identification. Continuous response increments and mutation points are analyzed to form a refined feature point set, enhancing the ability to capture strain mutations, extracting key interface adjustment values, analyzing the response differences before and after adjustment, enabling dynamic monitoring and verification of the control unit, improving the targeting of control, identifying areas that have not reached the target through feedback comparison, and establishing a hysteresis compensation mechanism to enhance control efficiency and closed-loop control capabilities.

Description

Technical Field

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

[0002] The field of nuclear fuel technology encompasses the research and development, application, and management of nuclear fuel, focusing primarily on its behavior and performance in nuclear reactors. The core of this technical area is the various physical, chemical, and mechanical effects on nuclear fuel within a nuclear reactor, including its effects on environmental factors such as temperature, pressure, and radiation. Nuclear fuel cladding, the protective outer shell of the nuclear fuel in a nuclear reactor, is responsible for isolating the fuel from the coolant and ensuring the safe operation of the reactor. With the development of nuclear energy technology, the materials, design, and monitoring techniques of nuclear fuel cladding have gradually gained attention, especially the impact of creep on cladding safety, which is currently a key focus of nuclear fuel technology research.

[0003] Among them, the nuclear fuel cladding tube biaxial creep process monitoring system refers to a system that monitors the performance of nuclear fuel cladding tubes during the biaxial creep process. It mainly solves the real-time monitoring and data analysis problems of nuclear fuel cladding tubes under biaxial creep state. By setting corresponding sensors and data acquisition systems, the deformation of the cladding tubes under biaxial load 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 tubes in the nuclear reactor, an efficient monitoring method is provided to help judge its safety and service life.

[0004] Existing technologies for monitoring the biaxial creep process of nuclear fuel cladding tubes rely on single-level stress and strain recording methods and lack a systematic framework for structured processing of sensor data and multi-parameter coupled analysis, resulting in relatively one-sided monitoring results. The extraction of temperature and stress responses fails to fully consider the joint modeling of spatial and temporal multidimensional factors, causing anomaly identification to be affected by data fluctuations, resulting in a high misjudgment rate and impacting accuracy. In the analysis of creep strain behavior, existing solutions fail to systematically capture continuous data response increments and have limited ability to extract strain mutation characteristics, making the control basis untargeted and resulting in suboptimal intervention effects. At the control execution level, static parameter settings are primarily used, lacking a real-time feedback correction mechanism for regulation effects. This inability to effectively identify and compensate for control deviations makes it difficult to form a closed-loop control system. For example, during operating cycles with frequent temperature fluctuations, existing monitoring fails to promptly identify the linkage of multiple abnormalities, resulting in ineffective intervention in some areas of concentrated load, posing a safety hazard and limiting the accuracy and reliability of performance monitoring and life assessment of nuclear fuel cladding tubes in complex service environments. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, an embodiment of the present invention provides a nuclear fuel cladding tube biaxial creep process monitoring system. The technical solution is as follows:

[0006] In one aspect, a nuclear fuel cladding tube biaxial creep process monitoring system is provided, the system comprising:

[0007] The temperature stress data capture module collects temperature sensor readings and stress sensor readings at key locations of nuclear fuel cladding tubes, extracts the original measurement data of sensor equipment number, location coordinates, and time nodes, performs structural conversion on the data format, and generates a basic data table of local thermal stress.

[0008] The regional state determination module extracts the temperature stress data of the interface between the fuel pellet area and the inner wall of the cladding tube based on the local thermal stress basic data table, jointly determines the temperature rise trend and the stress concentration frequency, filters the abnormal fluctuation data segments, marks the load abnormal response areas, and obtains the local creep abnormality segment distribution map;

[0009] 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 response incremental mutation position, and analyzes the corresponding strain change to obtain a strain mutation response feature point set;

[0010] The thermal control stress regulation module calls the strain mutation response feature point set, extracts the flow and pressure adjustment values ​​of the annular cooling channel interface and the shell injection port, analyzes the response differences before and after adjustment, identifies the control unit with excessive response amplitude, and obtains the creep control intervention node index table.

[0011] As a further solution of the present invention, the local thermal stress basic data table includes a temperature stress field group, measurement point spatial attributes, and a time label sequence; the local creep anomaly section distribution map includes thermal stress anomaly boundaries, stress concentration locations, and response trend characteristics; the strain mutation response feature point set includes mutation amplitude identifiers, time positioning nodes, and response sequence characteristics; and the creep control intervention node index table includes intervention unit numbers, control parameter groups, and risk marking information.

[0012] As a further solution of the present invention, the temperature stress data capture module includes:

[0013] The sensor reading collection submodule collects temperature sensor readings and stress sensor readings at key locations of the nuclear fuel cladding tubes, groups them according to numbers and coordinates, marks missing data, and filters out invalid data to obtain a synchronous monitoring data matrix.

[0014] 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;

[0015] The creep stress modeling submodule selects the biaxial corresponding point group based on the temperature and stress change curves of the sensing coordinate points in the biaxial directions in the coordinate mapping time series, extracts the change rate of the main stress direction and the peak amplitude of the auxiliary stress direction during the process, and generates a local thermal stress basic data table according to the time series.

[0016] As a further solution of the present invention, the area status determination module includes:

[0017] The temperature stress data extraction submodule extracts the temperature and stress sequences of the nodes at the interface between the fuel pellet area and the inner wall of the cladding tube based on the local thermal stress basic data table, arranges them by node number and time stamp, identifies radial and axial temperature and stress gradients, and generates biaxial temperature stress coupling gradient values;

[0018] The trend frequency determination submodule extracts the frequency of occurrence of joint temperature and stress spikes in the node in the time series based on the biaxial temperature-stress coupling gradient value, identifies the node clusters whose spike frequencies exceed the radial rise threshold and the axial mutation threshold, and obtains the biaxial spike frequency distribution;

[0019] The abnormal response marking submodule calls the dual-axis sudden rise frequency distribution, screens the frequency-intensive sections, calculates the frequency standard deviation, derives the creep rate of the nodes, identifies the continuous increase 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.

[0020] As a further solution of the present invention, the frequency standard deviation adopts the formula:

[0021] ;

[0022] in, represents the frequency standard deviation, represents the frequency of the kth frequency, represents the frequency average of the kth frequency, and m represents the total number of measured frequency points.

[0023] As a further solution of the present invention, the creep rate adjustment module includes:

[0024] The abnormal area sequence sorting submodule identifies the corresponding temperature sequence and stress sequence according to the marked area 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;

[0025] The response increment extraction submodule calls the regional 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 incremental change rate exceeds the response threshold, thereby obtaining the mutation response increment interval;

[0026] The strain mutation identification submodule extracts the strain change rate of the interval node according to the mutation response increment interval, screens 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.

[0027] As a further solution of the present invention, the thermal control stress regulation module includes:

[0028] The flow control parameter extraction submodule calls the concentrated risk point data of the strain mutation response characteristic point, calls the parameters of the annular cooling channel interface and the shell injection port, extracts the flow and pressure adjustment values ​​for each time period, merges the data before and after adjustment, analyzes the response amplitude change, and generates the thermal control response change range;

[0029] The over-limit node identification submodule compares the response amplitude change under the adjustment state with the upper limit threshold according to the thermal control response change interval, filters the control unit numbers that exceed the threshold, and records the nodes, response dimensions and time indexes to obtain the creep control intervention node index table.

[0030] As a further solution of the present invention, the system also includes an effect feedback correction module:

[0031] The effect feedback correction module collects stress and strain data after intervention according to the intervention units listed in the creep control intervention node index table, compares the difference with the difference before intervention, identifies the sub-areas that have not reached the adjustment target, and obtains a dynamic control backlash evaluation list;

[0032] The dynamic control hysteresis evaluation list includes a deviation ratio item, an unadjusted standard area, and a feedback identification label.

[0033] As a further solution of the present invention, the effect feedback correction module includes:

[0034] The creep strain acquisition submodule collects the axial strain rate, radial strain rate and applied load value in the corresponding time periods before and after the intervention according to the creep control intervention node index table, analyzes the biaxial strain change and archives the associated time series data to generate a biaxial strain change data group for the cladding tube;

[0035] The offset section identification submodule calls the biaxial strain change data set of the cladding tube, filters the strain change coordinate points that exceed the threshold range based on the biaxial strain reference threshold set initially loaded, locates the deviation range based on the tube section number, and obtains the biaxial offset section index table;

[0036] The hysteresis list sorting submodule extracts the axial and radial strain changes under the corresponding coordinates according to the dual-axis offset segment index table, identifies the strain hysteresis values ​​and sorts them, and organizes the results into a table according to the segment number to obtain a dynamic control hysteresis evaluation list.

[0037] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0038] By collecting and structurally transforming raw temperature and stress data from sensors at key locations, the data structure is standardized, ensuring high consistency and accuracy in subsequent processing. This improves the availability and traceability of the raw measurement data. The spatial location of temperature and stress data is combined with time series to form a data table with spatiotemporal coupling characteristics, providing a basis for accurately identifying the thermal stress state of the material. Trends in temperature and stress data near the fuel pellets and the inner wall interface of nuclear fuel cladding tubes are jointly determined. By identifying multiple abnormal fluctuations, abnormal response segments are effectively analyzed, improving the resolution and accuracy of local creep distribution identification. By identifying response increments and mutation points in time-continuous data, the ability to capture sudden strain changes during creep is enhanced, and a more refined feature point set is constructed, providing a precise reference for the formulation of subsequent control measures. Adjustment values ​​for key interfaces are extracted, and differential analysis of responses before and after adjustment is performed. Dynamic response monitoring of the control unit and verification of the control amplitude are achieved, enhancing the targeting and effectiveness of control measures. Based on the feedback comparison of intervention data, the areas where the control has not reached the target are identified, real-time calibration and compensation identification of the hysteresis area are achieved, a dynamic closed-loop control mechanism is established, and the control efficiency and reliability of the entire monitoring system are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 Schematic diagram of a biaxial creep process monitoring system for a nuclear fuel cladding tube provided by an embodiment of the present invention;

[0041] Figure 2 Schematic diagram of the system framework of the present invention;

[0042] Figure 3 This is a flow chart of the temperature stress data capture module in the present invention;

[0043] Figure 4 This is a flow chart of the regional status determination module in the present invention;

[0044] Figure 5 This is a flow chart of the creep rate adjustment module in the present invention;

[0045] Figure 6 This is a flow chart of the thermal control stress regulation module in the present invention;

[0046] Figure 7 This is a flow chart of the effect feedback correction module in the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0048] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0049] In the embodiments of the present invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same. The terms "of," "corresponding," and "corresponding" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same.

[0050] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0051] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0052] The embodiment of the present invention provides a nuclear fuel cladding tube biaxial creep process monitoring system, such as Figure 1-2 The schematic diagram of the biaxial creep process monitoring system for nuclear fuel cladding tubes shown in FIG. 1 includes:

[0053] The temperature stress data capture module collects temperature sensor readings and stress sensor readings at key locations of nuclear fuel cladding tubes, extracts the original measurement data of sensor equipment number, location coordinates, and time nodes, performs structural conversion on the data format, and generates a basic data table of local thermal stress.

[0054] Based on the local thermal stress basic data table, the regional state judgment module extracts temperature stress data located at the interface between the fuel pellet area and the inner wall of the cladding tube. It jointly determines the regional temperature rise trend and the frequency of stress concentration, filters data segments with abnormal multi-point fluctuations, marks the corresponding areas with abnormal load responses, and obtains a distribution map of local creep anomaly sections.

[0055] The creep rate adjustment module arranges the temperature and stress sequence data in chronological order within the marked areas in the local creep anomaly section distribution map, identifies the response increments between consecutive sampling points on the time axis, analyzes the strain changes corresponding to the incremental mutation positions, and obtains the strain mutation response feature point set;

[0056] The thermal control stress regulation module uses the concentrated risk point data of the strain mutation response characteristic points to extract the flow and pressure adjustment values ​​of the annular cooling channel interface and the shell injection port. It analyzes the response differences before and after adjustment, identifies the control units with excessive response amplitudes, and obtains the creep control intervention node index table.

[0057] The effect feedback correction module collects stress and strain data after intervention according to the intervention units listed in the creep control intervention node index table, compares the data with the difference before intervention, identifies the sub-areas that have not reached the adjustment target, and obtains a dynamic control backlash evaluation list.

[0058] The local thermal stress basic data table includes the temperature stress field group, measuring point spatial attributes, and time label sequence. The local creep anomaly section distribution map includes the thermal stress anomaly boundary, stress concentration location, and response trend characteristics. The strain mutation response feature point set includes the mutation amplitude identifier, time positioning node, and response sequence characteristics. The creep control intervention node index table includes the intervention unit number, control parameter group, and risk marking information. The dynamic control hysteresis evaluation list includes the deviation ratio item, the unadjusted standard area, and the feedback identification label.

[0059] Specifically, if Figure 2 、 3 As shown, the temperature stress data capture module includes:

[0060] The sensor reading collection submodule collects temperature sensor readings and stress sensor readings at key locations of the nuclear fuel cladding tubes, groups them according to numbers and coordinates, marks missing data, and filters out invalid data to obtain a synchronous monitoring data matrix.

[0061] 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.

[0062] 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;

[0063] 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.

[0064] The creep stress modeling submodule collects the temperature and stress change curves of the sensing coordinate points in the two-axis direction according to the coordinate mapping time series, selects the corresponding point group in the two-axis direction, extracts the change rate of the main stress direction and the peak amplitude of the auxiliary stress direction during the process, and generates a local thermal stress basic data table according to the time series;

[0065] The temperature and stress variation curves at sensing coordinate points in the biaxial direction of the coordinate mapping time series are analyzed. Biaxiality refers to the influence of temperature and stress variations in two directions within a two-dimensional coordinate system: the principal stress direction and the secondary stress direction. Based on the variation curves, groups of coordinate points with significant biaxial variation trends are selected. These groups represent stress and temperature variation data at different locations. The rate of change in the principal stress direction and the peak amplitude in the secondary stress direction are then extracted. The rate of change in the principal stress direction can be obtained by calculating the rate of change of temperature and stress over the time series. For example, the rate of change of temperature can be calculated as the ratio of the temperature change (ΔT) to the time change (Δt) between two points. Similarly, the rate of change of stress can be calculated. The peak amplitude in the secondary stress direction is the difference between the maximum and minimum stress values ​​at all time points, reflecting the amplitude of the secondary stress fluctuation. Data processing generates a local thermal stress basic data table. This table records the temperature and stress data of each sensor point over the time series, along with their rate of change and peak amplitude, providing the foundation for subsequent creep analysis and thermal stress assessment.

[0066] Specifically, if Figure 2 、 4 As shown, the regional status determination module includes:

[0067] The temperature stress data extraction submodule extracts the temperature and stress sequences of the nodes at the interface between the fuel pellet area and the inner wall of the cladding tube based on the local thermal stress basic data table. The modules are organized by node number and timestamp, identify radial and axial temperature and stress gradients, and generate biaxial temperature-stress coupling gradient values.

[0068] From the local thermal stress basic data table, temperature and stress series are extracted for nodes at the interface between the fuel pellets and the cladding tube inner wall. Nodes are selected based on spatial location, as the interface between the fuel pellets and the cladding tube inner wall is a region of the system with the most dramatic temperature and stress variations. Temperature and stress data are organized jointly according to node number and timestamp, ensuring accurate ordering of data based on time and location, facilitating subsequent analysis. Temperature and stress data series are obtained at different time points and nodes, and radial and axial temperature and stress gradients are calculated between nodes. Radial temperature and stress gradients refer to the temperature and stress differences between adjacent nodes in the radial direction, while axial gradients refer to the temperature and stress variations along the cladding tube axis. For example, if the temperature of a node is 100°C and the temperature of the radially adjacent node is 98°C, the radial temperature gradient is 2°C. Similar calculations are used to generate biaxial temperature-stress coupled gradient values, which include both radial and axial temperature and stress gradients. These gradients reflect the thermal stress distribution of the system and provide a basis for subsequent analysis.

[0069] The trend frequency determination submodule extracts the frequency of joint temperature and stress spikes in the time series based on the biaxial temperature-stress coupling gradient value, identifies node clusters whose spike frequencies exceed the radial rise threshold and the axial mutation threshold, and obtains the biaxial spike frequency distribution.

[0070] Based on the biaxial temperature-stress coupling gradient, the frequency of joint temperature and stress spikes at each node in the time series is analyzed. A joint spike refers to a significant simultaneous increase in temperature and stress at the same time point. For example, if the temperature at a node is 150°C and the stress is 250 MPa at time t1, and the temperature is 160°C and the stress is 270 MPa at time t2, then a temperature and stress spike can be considered. The frequency of spikes for all nodes in the time series is counted. If the spike frequency for a node exceeds a set threshold, the node is identified as having a spike. The thresholds include a radial spike threshold and an axial spike threshold. The radial spike threshold is set based on experimental data or original records, while the axial spike threshold is set based on the maximum tolerable variation range. For example, assuming the radial spike threshold is 5 and the axial spike threshold is 3, if a node's spike frequency exceeds these two thresholds within a period of time, the node is identified as an over-limit node and added to the node cluster, ultimately generating a biaxial spike frequency distribution.

[0071] The abnormal response annotation submodule calls the dual-axis sudden rise frequency distribution, screens the frequency-intensive sections, calculates the frequency standard deviation, derives the creep rate of the nodes, identifies the continuous creep rate increase interval, and maps the interval to the cladding tube axial section according to the spatial structure to obtain the local creep abnormal section distribution map;

[0072] Call the biaxial sudden rise frequency distribution and filter out the frequency-intensive segments. The frequency-intensive segments mean that within a certain period of time, the sudden rise frequencies of multiple nodes are relatively high, which indicates that abnormal changes have occurred. After filtering out the frequency-intensive segments, deduce the creep rate of the nodes. The creep rate is usually calculated through the relationship between the stress change and time of the node. Assuming that the stress of a node at time t1 is 200MPa and the stress at time t2 is 210MPa, 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 rises, indicating that within the interval, the creep rate of the node continues to increase, indicating that it is about to enter an abnormal state. The continuously rising creep rate interval is mapped to the axial section of the cladding tube according to the spatial structure, so that the creep anomaly at each position can be intuitively displayed;

[0073] Frequency standard deviation, using the formula:

[0074] ;

[0075] in, represents the frequency standard deviation, represents the frequency of the kth frequency, represents the frequency average of the kth frequency, and m represents the total number of measured frequency points;

[0076] Frequency standard deviation refers to the degree of dispersion of the frequency value of each measured frequency point relative to the average value of all frequencies. It is used to measure the magnitude of frequency fluctuation between sampling points. The larger the value, the more obvious the frequency difference in frequency response in different areas. This indicator can be used to identify abnormally dense sections in the frequency distribution, providing basic data support for subsequent creep analysis.

[0077] The screening of frequency-intensive segments depends on the degree of fluctuation of the frequency distribution. This formula is used to calculate the average absolute deviation between the frequency of each frequency point and the average frequency, which is defined as the frequency standard deviation parameter , this parameter is used to identify the frequency section with large deviation from the average value, providing a basis for regional screening before creep rate derivation;

[0078] : The frequency of the kth measurement frequency point, in Hz. This value is recorded by placing a micro-accelerometer array on the surface of the cladding tube material to record the high-frequency dynamic response. A high-speed sampling system is used to acquire vibration data at a frequency of 20 kHz. The data is converted to the frequency domain through fast Fourier transform (FFT). The number of frequency peaks that appear in the analysis window is taken as the number of times.

[0079] : The average value of all frequencies, obtained by measuring all The sum of the values ​​is divided by the number of frequency points m, and the unit is Hz, ensuring that consistent;

[0080] 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).

[0081] 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 the sensor sampling and frequency domain analysis. The data source is 5-minute period sampling, and the main peak is retained after removing the noise background.

[0082] Set frequency sample: , , , , , , , , , , , ;

[0083] Calculate the average frequency:

[0084] ;

[0085] Compute the sum of absolute deviations: ;

[0086] Calculate the frequency standard deviation:

[0087] 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.

[0088] Specifically, if Figure 2 、 5 As shown, the creep rate adjustment module includes:

[0089] 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;

[0090] 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.

[0091] The response increment extraction submodule calls the regional 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 incremental change rate exceeds the response threshold, thereby obtaining the mutation response increment interval;

[0092] Regional joint time series data is used to extract the temperature and stress differences between each adjacent sampling point. The differences represent the magnitude of the temperature and stress changes between the two time points. For example, assuming a node has a temperature of 150°C and a stress of 200 MPa at time t1, and a temperature of 155°C and a stress of 205 MPa at time t2, the temperature difference is 5°C and the stress difference is 5 MPa. The temperature and stress increments between each pair of adjacent time points are calculated. This increment can be expressed as the combined change in temperature and stress differences, which can be obtained through a simple difference calculation. This allows the identification of intervals where the rate of change of the increment exceeds a response threshold. The response threshold is set based on design requirements or the original data to filter out intervals with large temperature and stress increment changes. For example, if the response threshold is 0.1°C / MPa / s, the rate of change of the temperature and stress increments within each time period is calculated to identify intervals where the rate of change exceeds this threshold. For example, if the incremental change rate of temperature and stress is 0.2°C / Mpa / s within a certain time period, which exceeds the set threshold, the interval will be marked as a sudden change response incremental interval and become the key section for subsequent analysis.

[0093] The strain mutation identification submodule extracts the strain change rate of the interval node according to the mutation response increment interval, selects the points with sudden increase in continuous strain change rate, records the interval position and strain ratio in chronological order, and obtains the strain mutation response feature point set;

[0094] Based on the incremental interval of the sudden response, the strain change rate of the nodes in that interval is extracted. The strain change rate is calculated by calculating the ratio of the strain change to the time change 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%, with a time difference of 2 seconds, the strain change rate is (0.015% - 0.01%) / (2 seconds) = 0.0025% / second. The strain change rate is analyzed to identify points with continuous sudden increases in the strain change rate. Sudden increases in the strain change rate indicate abnormal changes or critical states, so special attention is paid to these sudden increase points. These selected sudden increase points are recorded in chronological order, and the strain ratio (i.e., the ratio of the strain change to the time change) of each point is recorded. This recording generates a set of characteristic points for the sudden strain response. This set contains all nodes with significant increases in strain change rate within the incremental interval of the sudden response, along with their related information. This set of points provides important information for subsequent strain analysis and fault prediction.

[0095] Specifically, if Figure 2 、 6 As shown, the thermal control stress regulation module includes:

[0096] The flow control parameter extraction submodule uses the concentrated risk point data of the strain mutation response feature points, calls the parameters of the annular cooling channel interface and the shell injection port, calculates the average change in the adjustment value, merges the data before and after adjustment, analyzes the change in response amplitude, and generates the thermal control response change range;

[0097] Data is extracted from the characteristic points of strain mutation response. This data represents the system strain change 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, real-time change data of temperature, pressure and flow are further obtained. In order to further adjust the temperature and pressure in the system, extracting the flow and pressure adjustment values ​​in each time period is a key operation. This can clearly understand the working status of the 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 under different states, it helps to determine the performance under different adjustment states and finally generate the thermal control response change range. This range can be used as reference data for subsequent optimization and fault warning. For example, assuming that in a certain time period, the flow adjustment value is 2L / min and the pressure is 1.5MPa, in the next time period, the flow changes to 2.5L / min and the pressure is 1.6MPa. After merging and comparison, the response change amplitude of the time period can be obtained. This range can accurately reflect the degree of fluctuation of the temperature control system.

[0098] The average change in the regulation value represents the absolute deviation of each regulation value from the overall average level after multiple regulation sampling of the fluid flow rate within a selected time period. It is used to measure the intensity of the fluctuation of the flow regulation response within that period. By quantifying the instantaneous inflow pressure, the effective cross-sectional area of ​​the cooling channel, the equivalent resistance, the pressure change, the regulated flow value at the previous sampling, the fluid thermal expansion coefficient, and the sampling time interval for each sampling, and combining the data at each point to calculate the average of the regulation value sequence, and comparing it with the original average regulation value, the final result is the change trend of the regulation response behavior in that time period compared to the long-term baseline state. This value reflects the instantaneous response capability of the flow control, as well as its stability and regulation intensity within the operating cycle.

[0099] The over-limit node identification submodule compares the response amplitude change in the adjustment state with the upper threshold according to the thermal control response change interval, selects the control unit number that exceeds the threshold, and records the node, response dimension and time index to obtain the creep control intervention node index table;

[0100] Comparative analysis is performed through the thermal control response variation interval to identify the over-limit response nodes in the system. The thermal control response variation interval defines the temperature control response range of the system under different states. The maximum value within this range is the upper threshold. By comparing the response amplitude change under the current adjustment state with the set upper threshold, it can be determined whether certain control units have exceeded the predetermined tolerance. In specific operations, the response amplitude change is first monitored, and the real-time fluctuation of the response value is recorded. Then, it is compared one by one with the set upper threshold. If the response amplitude of a unit is greater than the threshold, the unit is filtered out and its number is recorded. For example, if the response amplitude of a control unit is 10 and the set upper threshold is 8, then the unit will be marked as an over-threshold unit, and the node number, response dimension and corresponding time index of the unit will be noted in the record. The over-limit nodes are filtered out and the creep control intervention node index table is obtained. This table will be used for subsequent regulation and intervention to ensure long-term stable operation.

[0101] Specifically, if Figure 2 、 7 As shown, the effect feedback correction module includes:

[0102] The creep strain acquisition submodule collects the axial strain rate, radial strain rate, and applied load values ​​in the corresponding time periods before and after the intervention based on the creep control intervention node index table, analyzes the biaxial strain changes, and archives the associated time series data to generate a biaxial strain change data set for the cladding tube;

[0103] Based on the creep control intervention node index table, the specified control intervention node is found and the axial strain rate, radial strain rate, and applied load values ​​for the node in the corresponding time periods before and after the intervention are obtained. The axial strain rate refers to the ratio of the node's strain change in the axial direction to the time change during the specified time period. Similarly, the radial strain rate represents the rate of change of the node's strain in the radial direction. The applied load value refers to the external load applied to the node during that time period. For example, between time t1 and t2, assuming that the axial strain rate at a certain node changes by 0.005% / s, the radial strain rate changes by 0.003% / s, and the applied load is 1000N, the change in biaxial strain is calculated based on the parameters, which includes the combined changes in temperature and stress. Through this calculation, the overall strain trend in the biaxial directions can be analyzed. The calculation results are archived and associated as time series data for subsequent processing. The data is organized into a biaxial strain change data set for the cladding tube, which includes strain rate and load data in different directions at different time nodes. This data can support further analysis and prediction.

[0104] The offset section identification submodule calls the biaxial strain change data set of the cladding tube, filters the strain change coordinate points that exceed the threshold range based on the biaxial strain reference threshold set by the initial loading, locates the deviation range based on the tube section number, and obtains the biaxial offset section index table;

[0105] The biaxial strain change data set for the cladding tube is called up to analyze the axial and radial strain changes at each node. Based on the biaxial strain threshold initially set during loading, strain change coordinate points that exceed this threshold are screened. The biaxial strain threshold is a value set based on engineering experience or specifications and is used to determine whether abnormal strain changes have occurred. For example, assuming the biaxial strain threshold is set to 0.01% / s for axial strain and 0.005% / s for radial strain, if the axial strain change at a node exceeds 0.01% / s or the radial strain change exceeds 0.005% / s, the node is marked as abnormal. The out-of-range strain change coordinate points are then located using the pipe segment number. The pipe segment number indicates the location of the abnormal strain change for easy location and subsequent processing. All coordinate points with abnormal strain changes and their pipe segment numbers are organized into a biaxial offset segment index table, providing a marked area for subsequent analysis.

[0106] The hysteresis list compilation submodule extracts the axial and radial strain changes under the corresponding coordinates based on the dual-axis offset segment index table, identifies the strain hysteresis values, sorts and classifies them, and organizes the results into a table by segment number to obtain a dynamic control hysteresis evaluation list;

[0107] Based on the dual-axis offset segment index table, the axial and radial strain changes at each coordinate point are extracted. The strain changes represent the strain changes at each node over different time periods, and the strain hysteresis value is calculated. The strain hysteresis value refers to the difference between the strain change at a node and the expected strain change over a specific time period. For example, if the actual axial strain change at a node between time periods t1 and t2 is 0.015%, while the expected strain change is 0.01%, the strain hysteresis value is 0.015% - 0.01% = 0.005%. The hysteresis values ​​are sorted and categorized by hysteresis size to help identify nodes whose strain changes deviate from the expected range. The sorted strain hysteresis values ​​are then organized into a table by segment number to create a dynamic control hysteresis assessment list, which helps engineers identify areas requiring dynamic adjustment.

[0108] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A nuclear fuel cladding tube biaxial creep process monitoring system, characterized in that: The system comprises: The temperature stress data capture module collects temperature sensor readings and stress sensor readings at key locations of nuclear fuel cladding tubes, extracts the original measurement data of sensor equipment number, location coordinates, and time nodes, performs structural conversion on the data format, and generates a basic data table of local thermal stress. The regional state determination module extracts the temperature stress data of the interface between the fuel pellet area and the inner wall of the cladding tube based on the local thermal stress basic data table, jointly determines the temperature rise trend and the stress concentration frequency, filters the abnormal fluctuation data segments, marks the load abnormal response areas, and obtains the local creep abnormality segment distribution map; The area status determination module includes: The temperature stress data extraction submodule extracts the temperature and stress sequences of the nodes at the interface between the fuel pellet area and the inner wall of the cladding tube based on the local thermal stress basic data table, arranges them by node number and time stamp, calculates the radial and axial temperature gradients and stress gradients between the nodes, and generates the biaxial temperature stress coupling gradient value; The trend frequency determination submodule analyzes the frequency of occurrence of joint temperature and stress spikes in the node time series based on the dual-axis temperature-stress coupling gradient value, identifies node clusters whose spike frequencies exceed radial rise thresholds and axial mutation thresholds, and obtains the dual-axis spike frequency distribution; The combined sudden rise refers to the situation where the temperature and stress increase significantly at the same time point; The abnormal response marking submodule calls the dual-axis sudden rise frequency distribution, screens the frequency-intensive sections, calculates the frequency standard deviation, derives the creep rate of the nodes, identifies the continuous creep rate increase interval, and maps the interval to the cladding tube axial section according to the spatial structure to obtain the 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 response incremental mutation position, and analyzes the corresponding strain change to obtain a strain mutation response feature point set; The thermal control stress regulation module calls the strain mutation response feature point set, extracts the flow and pressure adjustment values ​​of the annular cooling channel interface and the shell injection port, analyzes the response differences before and after adjustment, identifies the control unit with excessive response amplitude, and obtains the creep control intervention node index table.

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

3. The nuclear fuel cladding tube biaxial creep process monitoring system according to claim 1, characterized in that: The temperature stress data capture module includes: The sensor reading collection submodule collects temperature sensor readings and stress sensor readings at key locations of the nuclear fuel cladding tubes, groups them according to numbers and coordinates, marks missing data, and filters out invalid data to obtain a synchronous monitoring data matrix. 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 sensor point in the synchronous monitoring data matrix, performs time series splicing on the temperature and stress values ​​of each sensor within the stable period, reconstructs the spatiotemporal continuous monitoring frame sequence through coordinate mapping, and generates a coordinate mapping time series set; The creep stress modeling submodule selects the biaxial corresponding point group based on the temperature and stress change curves of the sensing coordinate points in the biaxial directions in the coordinate mapping time series, extracts the change rate of the main stress direction and the peak amplitude of the auxiliary stress direction during the process, and generates a local thermal stress basic data table according to the time series.

4. The nuclear fuel cladding tube biaxial creep process monitoring system according to claim 1, characterized in that: The frequency standard deviation is calculated using the formula: ； in, represents the frequency standard deviation, represents the frequency of the kth frequency, represents the frequency average of the kth frequency, and m represents the total number of measured frequency points.

5. The nuclear fuel cladding tube biaxial creep process monitoring system according to claim 1, characterized in that: The creep rate adjustment module includes: The abnormal area sequence sorting submodule identifies the corresponding temperature sequence and stress sequence according to the marked area 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; The response increment extraction submodule calls the regional 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 incremental change rate exceeds the response threshold, thereby obtaining the mutation response increment interval; The strain mutation identification submodule extracts the strain change rate of the interval node according to the mutation response increment interval, screens 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.

6. The nuclear fuel cladding tube biaxial creep process monitoring system according to claim 5, characterized in that: The thermal control stress regulation module includes: The flow control parameter extraction submodule calls the concentrated risk point data of the strain mutation response characteristic point, calls the parameters of the annular cooling channel interface and the shell injection port, extracts the flow and pressure adjustment values ​​for each time period, merges the data before and after adjustment, analyzes the response amplitude change, and generates the thermal control response change range; The over-limit node identification submodule compares the response amplitude change under the adjustment state with the upper limit threshold according to the thermal control response change interval, filters the control unit numbers that exceed the threshold, and records the node number, response dimension and time index to obtain the creep control intervention node index table.

7. The nuclear fuel cladding tube biaxial creep process monitoring system according to claim 1, characterized in that: The system also includes an effect feedback correction module: The effect feedback correction module collects stress and strain data after intervention according to the intervention units listed in the creep control intervention node index table, compares the difference with the difference before intervention, identifies the sub-areas that have not reached the adjustment target, and obtains a dynamic control backlash evaluation list; The dynamic control hysteresis evaluation list includes a deviation ratio item, an unadjusted standard area, and a feedback identification label.

8. The nuclear fuel cladding tube biaxial creep process monitoring system according to claim 7, characterized in that: The effect feedback correction module includes: The creep strain acquisition submodule collects the axial strain rate, radial strain rate and applied load value in the corresponding time periods before and after the intervention according to the creep control intervention node index table, analyzes the biaxial strain changes and archives and associates them into time series data to generate a biaxial strain change data group for the cladding tube; The offset section identification submodule calls the biaxial strain change data set of the cladding tube, filters the strain change coordinate points that exceed the threshold range based on the biaxial strain reference threshold set initially loaded, locates the deviation range based on the tube section number, and obtains the biaxial offset section index table; The hysteresis list arrangement submodule extracts the axial and radial strain changes under the corresponding coordinates according to the dual-axis offset segment index table, calculates the strain hysteresis values ​​and sorts them, and arranges the results into a table according to the segment number to obtain a dynamic control hysteresis evaluation list; The strain hysteresis value refers to the difference between the strain change of a node and the expected strain change within a certain period of time.

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