Fuel assembly operation robot positioning method and system based on adaptive contour feature matching

Abstract

The invention belongs to the technical field of nuclear fuel assembly detection, and particularly relates to a fuel assembly operation robot positioning method and system based on adaptive contour feature matching. Comprising the steps that a global surface optimization tool converts acquired contour data into optimized ideal contour surface information, a fitting contour surface evaluation optimization tool feeds back a fitting contour surface overall deviation evaluation result, and a task data integration tool is an algorithm tool for relevant data configuration in the operation execution process of an execution assembly. And the task data integration tool constructs a data warehouse, and obtains trajectory data corresponding to the contour from the contour surface optimization module. The method has the advantages that one-key self-adaptive execution of assembly operation work can be achieved, accurate operation positioning is achieved through high-precision contour modeling, the method adapts to various motion control cards through a configuration type mode, dependence on the operation technology of operators is reduced, and the operation safety of equipment is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of nuclear fuel assembly detection, and particularly relates to a fuel assembly operating robot positioning method and system based on adaptive contour feature matching. BACKGROUND

[0002] The existing fuel assembly operating device has the following problems: 1) limited positioning accuracy, only selecting non-continuous operation points by experience data or fuel assembly features; 2) weak adaptability of motion trajectory, and the contour surface presents local unevenness, too large curvature change and other non-smoothness phenomena, resulting in insufficient automation degree of the whole task flow. SUMMARY

[0003] The purpose of the present application is to provide a fuel assembly operating robot positioning method and system based on adaptive contour feature matching, which aims to solve the problem of generating high-precision three-dimensional contour for large free contour surfaces, and to solve the problem of contour surface presenting local unevenness, too large curvature change and other non-smoothness phenomena. The global overall smoothing processing of the fitted contour surface is realized by encapsulating the smoothing optimization algorithm, which meets the high-precision positioning requirements of the motion control of the operating robot. In addition, by encapsulating the special data assembly algorithm tool and the supporting information warehouse, the whole fuel assembly operating robot device has the task configuration and full-automatic task implementation capability.

[0004] The technical scheme of the present application is as follows: a fuel assembly operating robot positioning system based on adaptive contour feature matching, comprising a global surface optimization tool, a fitted contour surface evaluation optimization tool, a task data integration tool and a task data configuration library;

[0005] The global surface optimization tool realizes the conversion of the collected contour data into the ideal optimized contour surface information by constraining the contour surface smoothness and the curvature change;

[0006] The fitted contour surface evaluation optimization tool is used for performing quality evaluation and comprehensive error optimization calculation on the contour surface generated by the fitting operation, determining the contour surface fitting accuracy by the method of collecting sampling points to evaluate distance error, and feeding back the overall deviation evaluation result of the fitted contour surface;

[0007] The task data integration tool is an algorithm tool for executing the related data configuration in the component operation execution process;

[0008] The task data integration tool constructs a data warehouse to obtain contour corresponding trajectory data from the contour surface optimization module.

[0009] The global surface optimization tool comprises a contour surface smoothness constraint condition set, a contour surface smoothness constraint sub-module, a curvature change constraint sub-module and an optimization result calculation sub-module;

[0010] The contour surface fairing constraint condition set is used for centralized storage of constraint condition data, including position constraint conditions and boundary constraint conditions, wherein the position constraint conditions are used for ensuring the approximation accuracy of the contour surface to the original data points, and the boundary constraint conditions are used for ensuring that the boundary condition in the parameter line direction of the contour surface is unchanged in the contour surface fairing processing process;

[0011] The contour surface fairing constraint sub-module is used for establishing a simplified contour surface strain energy model, and the contour surface fairing constraint function is realized through the model;

[0012] The curvature change constraint sub-module is used for establishing a contour surface curvature change model, two partial derivatives of the contour surface curvature are approximated by using the second-order difference of the contour surface curvature along the double equal parameter direction, the partial derivatives are solved by fitting the contour surface expression, and the curvature change constraint function is realized through the model;

[0013] The optimization result calculation sub-module is based on the contour surface fairing constraint and the curvature change constraint model, the contour surface fairing model is solved, the model expression solving calculation is performed by using the quadratic programming method with linear constraints taking the contour surface control vertex as a variable, the contour surface optimization model containing the contour surface fairing constraint criterion is established, and the contour surface result optimization calculation function is realized.

[0014] The fitted contour surface evaluation optimization tool includes an evaluation benchmark construction sub-module, an average error calculation sub-module and a comprehensive deviation feedback sub-module;

[0015] The evaluation benchmark construction sub-module is used for performing the establishment of the evaluation benchmark, constructing the corresponding point on the fitted contour surface through the matching of the plane projection point of the acquisition point and the tangent plane equation of the fitted contour surface, performing the tangent plane equation solving by substituting the corresponding point normal vector, and obtaining the evaluation benchmark model;

[0016] The average error calculation sub-module is used for calculating the shortest distance from the sampling point to the fitted contour surface;

[0017] The comprehensive deviation feedback sub-module is used for calculating the overall error of the contour surface fitting; based on the average error, the fitting error of the contour surface can be calculated, and when the fitting deviation meets the detection requirement, the fitted contour surface is the contour of the outer surface of the fuel assembly to be operated.

[0018] The task data integration tool includes a task report framework integration sub-module, an operation object data integration sub-module, a task resource data integration sub-module, a motion control data integration sub-module, integrated process information and a data interaction interface;

[0019] The task report framework integration submodule obtains data from the component operation plan set, the equipment information set, the personnel information set and the report framework set in the task data configuration library through a data interaction interface, generates operation report framework data combination G mr-f ; and performs bidirectional data interaction with the task generation module and the operation report generation module through the data interaction interface;

[0020] The operation object data integration submodule obtains data from the component operation plan set in the task data configuration library through a data interaction interface, and generates operation object data combination G m-o ; and performs bidirectional data interaction with the task generation module and the operation report generation module through the data interaction interface;

[0021] The task resource data integration submodule obtains data from the component operation plan set and the personnel information set in the task data configuration library through a data interaction interface, and generates task resource data combination G t-r ; and performs bidirectional data interaction with the task generation module and the operation report generation module through the data interaction interface;

[0022] The motion control data integration submodule obtains device parameter information and control card interface authorization from the equipment information set in the task data configuration library through a data interaction interface, and generates motion control data combination G m-c ; and performs bidirectional data interaction with the task generation module and the operation report generation module through the data interaction interface;

[0023] The integrated process information set provides temporary storage intermediate data combination G t-s during integration and assembly calculation processes.

[0024] The data interaction interface is used for executing data interaction transmission between functional modules.

[0025] The task data integration tool includes a task data configuration library index, a component operation plan set, an equipment information set, a personnel information set and a report framework set;

[0026] The data configuration library index I d-w records all data set registration information in the current task data configuration library, including an entry number subset SC n , a data association relationship subset SC r , a key field subset SC k , a data update state subset SC s , and has a structure of I d-w <SC n |SC r |SC k |SC s >;

[0027] The component operation plan set C p Recording operation plan information, including the periodic operation plan subset SP st-p , the regular operation plan subset SP rt-p , structured as C p <SP st-p |SP rt-p >;

[0028] The device information set C d Recording operation device related information, including the device parameter subset SD d-p , the control card interface subset SD c-i , the device trajectory / key positioning point information subset SD t-loc , structured as C d <SD d-p |SD c-i |SD t-loc >;

[0029] The personnel information set C m Recording operation task personnel related information, including the operation authorization subset SM p-c , the historical task subset SM p-h , structured as C m <SM p-c |SM p-h >;

[0030] The report framework set C r Recording operation report file related information, including the periodic report subset SR s-r , the regular report subset SR c-r , structured as C r <SR s-r |SR c-r >.

[0031] A fuel assembly operation robot positioning method based on adaptive contour feature matching, comprising the following steps:

[0032] Step 1: Contour data sampling;

[0033] Step 2: Initial contour surface generation;

[0034] Step 3: Contour surface contour fitting optimization;

[0035] Step 4: Operation task configuration;

[0036] Step 5: Operation task generation;

[0037] Step 6: Task execution and recording;

[0038] Step 7: Operation result feedback.

[0039] The step 1 comprises:

[0040] Step 11: Data channel construction

[0041] Sensor interface initialization, real-time data acquisition of three-coordinate probe and ranging probe;

[0042] Step 12: Data framework construction

[0043] Through the scanning strategy generation submodule, the scanning strategy is generated, and the scanning path and sampling interval data are created;

[0044] Step 13: Data content saving

[0045] Through the scanning contour generation submodule, the scanning contour data generation is executed, and the rough contour point cloud data is saved.

[0046] The step 2 comprises:

[0047] Step 21: Data loading

[0048] The rough contour data loading interface is called, and the data loading operation is executed;

[0049] Step 22: Constraint condition construction

[0050] The constraint condition set data construction is judged, including one-to-one correspondence, shape similarity, and smoothness;

[0051] Step 23: Initial contour surface parameter calculation

[0052] The initial contour surface parameter calculation submodule is called, and the data point in the initial contour surface parameter value solving is executed;

[0053] Step 24: Solution of overdetermined linear equations

[0054] The error calculation submodule is called, and the overdetermined linear equations are established and solved using the Householder transformation method;

[0055] Step 25: Error comparison calculation

[0056] The error vector calculation and error threshold comparison iteration are executed, and the initial contour surface is generated.

[0057] The step 3 comprises:

[0058] Step 31: Data loading

[0059] The initial contour surface data is loaded and stored in the initial contour surface data storage library;

[0060] Step 32: Global surface optimization

[0061] Call the global surface optimization tool to execute the contour surface fairing constraint and the curvature variation constraint; call the contour surface fairing constraint submodule to establish a contour surface strain energy simplified expression; call the curvature variation constraint submodule to establish a contour surface curvature variation expression and solve it; call the optimization result calculation submodule to establish a generalized energy expression containing the contour surface fairing criterion based on the contour surface strain energy variation and the curvature variation; call the optimization result calculation submodule to execute the contour surface fairing model solution and obtain the optimized data;

[0062] Step 33: fitting contour surface optimization

[0063] Call the fitting contour surface evaluation optimization tool to execute the evaluation benchmark construction, average error calculation and comprehensive deviation feedback; call the evaluation benchmark construction submodule to execute the tangent plane equation establishment; call the average error calculation submodule to calculate the shortest distance from the sampling point to the contour surface; call the comprehensive deviation feedback submodule to execute the contour surface fitting error calculation and feed back the calculation evaluation result;

[0064] Step 34: data storage

[0065] The optimized contour surface data storage is executed, and related data is transmitted to the trajectory / key positioning point subset in the device information set of the task data configuration library for operation task data integration.

[0066] The step 4 comprises:

[0067] Step 41: the task configuration module reads the component operation plan set from the task data configuration library, executes the analysis of the periodic operation plan information or the regular operation plan information according to the preset requirements, executes the plan data assembly by the operation plan configuration submodule, and stores the assembly result into the configuration process information set;

[0068] Step 42: the task configuration module reads the component operation device information set from the task data configuration library, executes the analysis of the device technical parameters and the control card interface adaptation information according to the preset requirements, executes the device related data assembly by the operation device configuration submodule, and stores the assembly result into the configuration process information set;

[0069] Step 43: the task configuration module reads the personnel information set from the task data configuration library, executes the analysis of the operation authorization and the historical task information according to the preset requirements, executes the related data assembly by the configuration submodule, and stores the assembly result into the configuration process information set;

[0070] Step 44: according to the calculation results of steps 41 to 43, the task configuration module reads the report framework set from the task data configuration library, executes the report type analysis according to the preset requirements, completes the report related data assembly to form complete task configuration data, and stores the assembly result into the configuration process information set;

[0071] Step 45: According to the result of step 44, the complete task configuration data is transmitted to the task generation module through the data interaction interface.

[0072] The step 5 comprises:

[0073] Step 51: The task generation module obtains the task configuration data from the task configuration module through the data interaction interface;

[0074] Step 52: The task generation module calls the motion control data integration submodule of the task data integration tool, executes the motion axis parameter configuration of the motion operation device through the technical parameter dynamic calculation submodule, and stores the configuration result into the assembly process information set; during the configuration calculation process, the task data integration tool accesses the task data configuration library for information supplement;

[0075] Step 53: The task generation module calls the operation object data integration submodule, the task resource data integration submodule and the task report framework integration submodule of the task data integration tool, executes the operation report data assembly required through the process parameter intelligent calculation submodule, and stores the assembly result into the assembly process information set; during the configuration calculation process, the task data integration tool accesses the task data configuration library for information supplement;

[0076] Step 54: Based on the assembly results of steps 51 to 53, the task generation module executes the final configuration and merging of the task entry information through the task assembly submodule, and stores the merging result into the assembly process information set;

[0077] Step 55: According to the result of step 54, the final task entry data is transmitted to the task execution module through the data interaction interface.

[0078] The step 6 comprises:

[0079] Step 61: The task execution module obtains the task entry data from the task generation module through the data interaction interface;

[0080] Step 62: The task execution module executes data analysis through the task entry processing submodule, and stores the analysis process data into the task process information set;

[0081] Step 63: According to the preset requirements and the actual needs of the field operation, the full-automatic execution submodule of the task execution module performs full-automatic operation, and the motion axis state information, trajectory record information and nondestructive testing signal feedback information in the operation process are uniformly stored into the task process information set; in the manual operation mode, the semi-automatic execution submodule of the task execution module performs operation, and the motion axis state information, trajectory record information and nondestructive testing signal feedback information in the operation process are uniformly stored into the task process information set;

[0082] Step 64: After the completion of the tasks in steps 61 to 63, the task process information set is read by the operation process data integration submodule of the task execution module, the integration and assembly of the data required for the operation report are performed, and the TDC file required for the operation report generation is formed;

[0083] Step 65: The TDC file generated in step 64 is transmitted to the operation report generation module through the data interaction interface.

[0084] The step 7 comprises:

[0085] Step 71: The TDC file transmitted by the task execution module is obtained through the data interaction interface;

[0086] Step 72: The TDC file is parsed by the TDC file record traversal submodule and the TDC file processing submodule of the operation report generation module, and the parsed data is stored in the report generation process information set;

[0087] Step 73: The parsed data of step 72 is executed by the operation result data integration submodule of the operation report generation module to classify and read the key information, and the read data is stored in the report generation process information set;

[0088] Step 74: Based on the result of step 73, according to the actual report generation requirement on site, the WORD file generation module or the PDF file generation module of the operation report generation module is used to complete the file generation and export of the final format of the operation report;

[0089] Step 75: According to the operation report and the corresponding operation result obtained in step 74, the data interaction interface is used to transmit the operation report to the task data integration tool, and the task data configuration library is updated, the historical operation result is archived, and the generation of the WORD file and the PDF file of the inspection report is verified by the WORD file generation submodule and the PDF file generation submodule of step 74.

[0090] The present application has the advantages that the present application can realize one-key adaptive execution of component operation work, realizes accurate operation positioning through high-precision contour modeling, reduces the operation technical dependence on operators by adapting to various motion control cards in a configuration mode, and improves the safety of equipment operation. The core of the method is to complete high-precision modeling of the component contour, and to realize modularization and automation processing of the nuclear fuel assembly operation task by using a special data integration tool in a configuration mode, while adapting to different component operation robot devices and control cards, improving positioning accuracy and reducing additional debugging workload caused by changes in the hardware of the operation robot device. The complete method and system form a standardized framework through the functional modules of task configuration, task generation, task execution and operation report generation. BRIEF DESCRIPTION OF DRAWINGS

[0091] Figure 1 schematic diagram of a global surface optimization tool;

[0092] Figure 2 schematic diagram of a fitting contour surface evaluation optimization tool;

[0093] Figure 3 schematic diagram of a task data integration tool structure;

[0094] Figure 4 schematic diagram of a task data configuration library structure;

[0095] Figure 5 schematic diagram of a fuel assembly operating robot positioning system based on adaptive contour feature matching provided by the present application;

[0096] Figure 6 flow chart of a fuel assembly operating robot positioning method based on adaptive contour feature matching provided by the present application. DETAILED DESCRIPTION

[0097] The present application will be further described in detail below in combination with the accompanying drawings and specific embodiments.

[0098] For nuclear industry fuel assembly detection and operation business, it is necessary to improve work efficiency under the condition of ensuring the safety of fuel assemblies, so three-dimensional modeling can be performed on the outer surface contour of the fuel assembly to accurately position the operating robot. The present application can perform contour reconstruction by laser scanning the surface of the fuel assembly to meet the high-precision positioning requirements of the assembly surface when implementing automatic detection, and provide a configuration solution for robot motion control. By constructing a motion control card adaptation library with pre-configuration function, a special algorithm tool library and loading contour data, a motion control scheme of the operating robot trajectory with operation result feedback function is formed. The present application can be used as an independent functional module, and is suitable for various types of fuel assembly replacement maintenance, outer surface non-destructive testing and measurement processes, and realizes the accurate positioning of intelligent robots in the three-dimensional space of the outer surface of the operated object.

[0099] The present application mainly solves two types of problems, including: 1) generating a high-precision contour surface of the fuel assembly by fitting method from a series of spatial discrete points, while optimizing the contour surface to present local unevenness, dramatic fluctuation of normal vector, and too large curvature change, etc. Unsmooth shape phenomenon, and improving the positioning accuracy of the fuel assembly surface; 2) based on the obtained high-precision contour surface data, generating a robot motion trajectory according to the coordinate information of the target point.

[0100] The present application analyzes business needs, and is specifically divided into two parts of "contour generation" and "operation control implementation"; for fuel assembly surface contour generation, the present application designs a "rough contour information generation module", an "initial contour surface model generation module" and a "contour surface fine optimization module" covering the whole process of contour construction around two key technologies of "global surface optimization tool" and "fitting contour surface fine optimization tool"; in addition, according to the needs of data processing and integration of the robot device in the operation task process, a functional module covering the whole process of fuel assembly operation business is designed around the key technology of "task data integration tool (TDI)" and the supporting task data configuration library (TDC), including: a task configuration module (TC), a task generating module (TG), a task executing module (TE) and a task report generating module (TRG); the following is the detailed content of the technical scheme.

[0101] A fuel assembly operation robot positioning system based on adaptive contour feature matching, comprising a global surface optimization tool, a fitting contour surface evaluation optimization tool, a task data integration tool and a task data configuration library.

[0102] The global surface optimization tool realizes conversion of the collected contour data into ideal contour surface information after optimization by constraint processing of contour surface smoothness and curvature variation, and the structure is shown in Figure 1 The global surface optimization tool comprises a contour surface smoothness constraint condition set, a contour surface smoothness constraint sub-module, a curvature variation constraint sub-module and an optimization result calculation sub-module.

[0103] The contour surface smoothness constraint condition set is used for centralized storage of constraint condition data, and comprises a position constraint condition and a boundary constraint condition, wherein the position constraint condition is used for ensuring the approximation accuracy of the contour surface to the original data points, and the boundary constraint condition is used for ensuring that the boundary condition of the contour surface along the equal parameter line direction is unchanged in the contour surface smoothness processing process.

[0104] The contour surface smoothness constraint sub-module is used for establishing a simplified contour surface strain energy model, and the model has good calculation stability and smoothness, and realizes the contour surface smoothness constraint function through the model.

[0105] The curvature variation constraint sub-module is used to establish a curvature variation model of the profile surface, the model uses a second-order difference of the profile surface curvature along the bi-isoparametric direction to approximate two partial derivatives of the profile surface curvature, and solves the partial derivatives by fitting the profile surface expression, and the curvature variation constraint function is realized through the model.

[0106] The optimization result calculation sub-module is based on the profile surface fairing constraint and the curvature variation constraint model, the profile surface fairing model is solved, a quadratic programming method with linear constraints of the profile surface control vertex as variables is used to perform the model expression solving calculation, a profile surface optimization model containing the profile surface fairing constraint criterion is established, and the profile surface result optimization calculation function is realized.

[0107] Function description:

[0108] ①The profile surface fairing constraint condition set: a special data structure used to store constraint condition related data, specifically including position constraint condition data (used to ensure the approximation accuracy of the profile surface to the original data points) and boundary constraint condition data (used to ensure that the boundary range of the profile surface along the isoparametric line direction is unchanged during the profile surface fairing process);

[0109] ②The profile surface fairing constraint sub-module: using a simplified profile surface strain energy model operator, performing fuel assembly profile surface fairing curve constraint to form an ideal model;

[0110] ③The curvature variation constraint sub-module: using an approximation operator (specifically, a second-order difference of the profile surface curvature along the bi-isoparametric direction to approximate two partial derivatives of the profile surface curvature), and simultaneously solving the partial derivatives by using a fitting profile surface operator, finally generating a profile surface curvature variation constraint model, and realizing the curvature variation constraint function through the model;

[0111] ④The optimization result calculation sub-module: a quadratic programming method with linear constraints of the profile surface control vertex as variables is used to perform the model expression solving calculation, and a profile surface optimization model containing the profile surface fairing constraint criterion is established.

[0112] The fitting profile surface evaluation optimization tool is used to perform quality evaluation and comprehensive error optimization calculation on the profile surface generated by the fitting operation, the profile surface fitting accuracy is determined by the method of collecting sampling points to evaluate distance error, and finally the overall deviation evaluation result of the fitting profile surface is fed back; the structural diagram is shown Figure 2 , including an evaluation reference construction sub-module, an average error calculation sub-module, and a comprehensive deviation feedback sub-module.

[0113] Evaluation benchmark construction submodule: used for performing the establishment of evaluation benchmark, constructing the tangent plane equation of the corresponding point on the fitting contour surface through the matching of the planar projection point of the acquisition point and the fitting contour surface, solving the tangent plane equation by substituting the normal vector of the corresponding point into the calculation (fitted contour surface pair), and obtaining the evaluation benchmark model.

[0114] Average error calculation submodule: used for calculating the shortest distance from the sampling point to the fitting contour surface.

[0115] Comprehensive deviation feedback submodule: used for calculating the overall error of the contour surface fitting; based on the average error, the fitting error of the contour surface can be calculated, and when the fitting deviation meets the detection requirement, the fitting generated contour surface is the contour of the outer surface of the fuel assembly to be operated.

[0116] Function implementation:

[0117] ① Evaluation benchmark construction submodule: first, construct the equation, construct the tangent plane equation of the corresponding point on the fitting contour surface through the matching of the planar projection point of the acquisition point and the fitting contour surface, solve the tangent plane equation by substituting the normal vector of the corresponding point into the calculation (fitted contour surface pair), and obtain the evaluation benchmark model;

[0118] ② Average error calculation submodule: calculate the shortest distance from the sampling point to the fitting contour surface to obtain the average error result;

[0119] ③ Comprehensive deviation feedback submodule: based on the result of the average error calculation submodule, perform the fitting error calculation of the contour surface, and obtain the overall error result of the contour surface fitting.

[0120] Task data integration tool (TDI) is a special algorithm tool for configuring related data in the execution process of component operation, and the structural diagram is shown in Figure 3 , specifically including: task report framework integration submodule, operation object data integration submodule, task resource data integration submodule, motion control data integration submodule, integrated process information set, and data interaction interface.

[0121] Task report framework integration submodule: obtains data from the component operation plan set, device information set, personnel information set, and report framework set in the task data configuration library through the data interaction interface, generates operation report framework data combination G mr-f based on the pre-set report template in the report framework set; and can perform bidirectional data interaction with the task generation module and the operation report generation module through the data interaction interface.

[0122] Operation object data integration submodule: obtains data from the component operation plan set in the task data configuration library through the data interaction interface, and generates operation object data combination G m-o; can carry on two-way data interaction with task generation module and operation report generation module through data interaction interface.

[0123] Task resource data integration submodule: through data interaction interface, data is obtained from component operation plan set and personnel information set in task data configuration library, and task resource data combination G t-r ; can carry on two-way data interaction with task generation module and operation report generation module through data interaction interface.

[0124] Motion control data integration submodule: through data interaction interface, device parameter information and control card interface authorization are obtained from device information set in task data configuration library, and motion control data combination G m-c ; can carry on two-way data interaction with task generation module and operation report generation module through data interaction interface.

[0125] Integrated process information set: provides temporary storage of intermediate data G in calculation process such as integration and assembly t-s .

[0126] Data interaction interface: used for data interaction transmission between functional modules in system.

[0127] Function description:

[0128] ①Task report framework integration submodule: the specific implementation is to call data interaction interface, read data from task data configuration library (sources include: component operation plan set, device information set, personnel information set and report framework set), and generate operation report framework data combination G mr-f , namely the required task report framework;

[0129] ②Operation object data integration submodule: calling data interaction interface, data is read from component operation plan set in task data configuration library to generate operation object data combination G m-o .

[0130] ③Task resource data integration submodule: calling data interaction interface, data is read from component operation plan set and personnel information set in task data configuration library to generate task resource data combination G t-r ;

[0131] ④Motion control data integration submodule: calling data interaction interface, device parameter information and control card interface authorization information are read from device information set in task data configuration library to generate motion control data combination G m-c ;

[0132] The above several submodules are used for data summarization operation.

[0133] The task data integration tool (TDI) is used to build the complete data warehouse, and the trajectory data corresponding to the contour is obtained from the contour surface optimization module Figure 4 , and specifically includes a task data configuration library index, a component operation plan set, a device information set, a personnel information set, and a report framework set.

[0134] Data configuration library index I d-w : records all data set registration information in the current task data configuration library, including entry number subset SC n , data association relationship subset SC r , key field subset SC k , data update state subset SC s , structure I d-w <SC n |SC r |SC k |SC s >.

[0135] Component operation plan set C p : records operation plan information, including periodic operation plan subset SP st-p , regular operation plan subset SP rt-p , structure C p <SP st-p |SP rt-p >.

[0136] Device information set C d : records operation device related information, including device parameter subset SD d-p , control card interface subset SD c-i , device trajectory / key positioning point information subset SD t-loc , structure C d <SD d-p |SD c-i |SD t-loc >.

[0137] Personnel information set C m : records operation task personnel related information, including operation authorization subset SM p-c , historical task subset SM p-h , structure C m <SM p-c |SM p-h >.

[0138] Report framework set C r : records operation report file related information, including periodic report subset SR s-r , regular report subset SR c-r , structure C r <SRs-r |SR c-r >.

[0139] “Task Data Configuration Library (TDC)”, as a supporting data warehouse of “Task Data Integration Tool (TDI)”, is a complete data structure, including Task Data Configuration Library Index, Component Operation Plan Set, Device Information Set, Personnel Information Set and Report Framework Set, a total of 5 parts, which belongs to the storage of different types of specific data storage sets.

[0140] (2) Function module description

[0141] Rough profile data generation module (RFG): used for performing raw data acquisition and data normalization using sensors, obtaining real-time data of three-coordinate probes and ranging probes through sensor data interfaces, then creating scan paths and sampling interval setting data through a scan strategy generation submodule, and the generated data can be called by external systems to realize point cloud data acquisition and generation; the rough profile data generation module includes a sensor data interface, a scan strategy generation submodule and a scan profile generation submodule; see Figure 5 (1);

[0142] Initial profile surface generation module (ISG): used for performing processing of rough profile data and generation of initial profile surface data; the initial profile surface generation module includes a rough profile data loading interface, a constraint condition set, an initial profile surface parameter calculation submodule and an error calculation submodule; the rough profile data loading interface is used to perform data loading operation, the constraint condition set includes feature corresponding matching conditions, shape similarity conditions and fairness judgment conditions, the initial profile surface parameter calculation submodule is used to solve parameter values of data points on the initial profile surface, and the error calculation submodule is used to establish and solve overdetermined linear equations using the Householder transformation method, as well as error vector calculation, error threshold comparison and iteration; see Figure 5 (2);

[0143] Profile surface optimization module (SO): used for reading initial profile surface data, respectively calling global surface optimization tools and fitting profile surface evaluation optimization tools to perform fitting profile surface optimization and evaluation operations, and finally feeding back optimized profile surface data; the profile surface optimization module includes a data transmission interface, an initial profile surface data storage library and an optimized profile surface data storage library; see Figure 5 (3);

[0144] Task configuration module (TC): used for performing operation plan data, operation device data, and operation personnel information assembly operations related to the content of component operation tasks, and capable of transmitting data with other functional modules through a data interaction interface; the task configuration module includes an operation plan configuration submodule, an operation device configuration submodule, an operation personnel configuration submodule, a configuration process information set, and a data interaction interface; a structural diagram is shown Figure 5 (6);

[0145] Task generation module (TG): based on the processed operation plan, operation device, and operation personnel data fed back by the task configuration module, calls a task data integration tool to perform technical parameter (such as operation device motion axis parameter information and control card motion control configuration information) and process parameter (such as operation object number, material, and replacement / maintenance / detection period) integration calculation required for operation tasks, generates task data, and stores calculation process data to the assembly process information set; the task generation module includes a technical parameter dynamic calculation submodule, a process parameter intelligent calculation submodule, a task assembly submodule, an assembly process information set, and a data interaction interface; a structural diagram is shown Figure 5 (8);

[0146] Task execution module (TE): analyzes the task data provided by the task generation module, obtains task details, and completes full-automatic or semi-automatic execution of operation tasks according to operation steps and motion control system motion axis strategies, and records motion axis trajectories and motion step process during task execution; the task execution module includes a task file processing submodule, a full-automatic execution submodule, a semi-automatic execution submodule, a process recording submodule, an operation process data integration submodule, a task process information set, and a data interaction interface; a structural diagram is shown Figure 5 (10);

[0147] Operation report generation module (MRG): performs a function of generating a component operation report file; the operation report generation module includes a TDC file record traversal submodule, a TDC file processing submodule, an operation result data integration submodule, a WORD file generation module, a PDF file generation module, a report generation process information set, and a data interaction interface; a structural diagram is shown Figure 5 (11)。

[0148] Module descriptions:

[0149] ①Coarse profile data generation module (RFG): directly interfaces with a data acquisition sensor and obtains original profile data collected by the sensor, such as laser radar point cloud data;

[0150] ②Initial profile surface generation module (ISG): performs fine processing on coarse data obtained by the coarse profile data generation module (RFG) to obtain fuel assembly original profile data;

[0151] 3. Contour surface optimization module (SO): to optimize the original contour data of fuel assembly obtained by initial contour surface generation module (ISG);

[0152] 4. Task configuration module (TC): to make initial configuration of fuel assembly operation task; the module will call the aforementioned "task data configuration library (TDC)", which will use the aforementioned "global surface optimization tool" and "fitting contour surface fine optimization tool" two key technologies

[0153] 5. Task generation module (TG): based on the initial configuration of the operation task, form a perfect task data, the module will call the aforementioned "task data integration tool (TDI)";

[0154] 6. Task execution module (TE): based on the task information given by the task generation module (TG), implement the scanning task;

[0155] 7. Operation report generation module (MRG): based on the process information of the task implementation of the task execution module (TE), complete the report data generation, the module will call the aforementioned "task data integration tool (TDI)", and write data to the "task data integration tool (TDI)".

[0156] The above content is completely consistent with "system structure diagram". ​

[0157] The core of the present application is to realize the modularization and automation of nuclear fuel assembly operation task by high-precision modeling of fuel assembly contour, and to adapt to different assembly operation robot equipment, reduce the additional adaptation workload caused by the change of operation robot hardware. The following will be described in detail from the following seven aspects: contour data sampling, initial contour surface generation, contour surface contour fitting optimization, task item configuration, task content generation, operation task execution and process record, and operation result feedback:

[0158] A fuel assembly operation robot positioning method based on adaptive contour feature matching, comprising the following steps:

[0159] Step 1: Contour data sampling

[0160] Step 11: Data channel construction

[0161] The sensor interface is initialized, and real-time data of three-coordinate probe and ranging probe is obtained;

[0162] Step 12: Data frame construction

[0163] ​A scanning strategy generation submodule generates a scanning strategy, creating scanning path and sampling interval data;

[0164] Step 13: Data content saving

[0165] A scanning profile generation submodule executes scanning profile data generation, saving coarse profile point cloud data.

[0166] Step 2: Initial profile surface generation

[0167] Step 21: Data loading

[0168] A coarse profile data loading interface is called to execute data loading operations;

[0169] Step 22: Constraint condition construction

[0170] Constraint condition set data construction is determined, including one-to-one correspondence, shape similarity, and fairness constraints;

[0171] Step 23: Initial profile surface parameter calculation

[0172] An initial profile surface parameter calculation submodule is called to execute data point initial profile surface parameter value solving;

[0173] Step 24: Overdetermined linear equation system solving

[0174] An error calculation submodule is called to execute overdetermined linear equation system establishment and use of the Householder transformation method to execute solving;

[0175] Step 25: Error comparison calculation: execute error vector calculation, error threshold comparison iteration, and initial profile surface generation.

[0176] Step 3: Profile surface profile fitting optimization

[0177] Step 31: Data loading

[0178] Initial profile surface data is loaded into an initial profile surface data repository;

[0179] Step 32: Global surface optimization

[0180] A global surface optimization tool is called to execute profile surface fairness constraints and curvature change constraints; a profile surface fairness constraint submodule is called to establish a profile surface strain energy simplified expression; a curvature change constraint submodule is called to establish a profile surface curvature change expression and solve it; an optimization result calculation submodule is called to establish a generalized energy expression containing profile surface fairness criteria based on profile surface strain energy changes and curvature changes; an optimization result calculation submodule is called to execute profile surface fairness model solving, obtaining optimized data;

[0181] Step 33: Fitting Contour Surface Optimization

[0182] The fitting contour surface evaluation optimization tool is called to perform evaluation benchmark construction, average error calculation, and comprehensive deviation feedback; the evaluation benchmark construction submodule is called to perform tangent plane equation establishment; the average error calculation submodule is called to calculate the shortest distance from the sampling points to the contour surface; the comprehensive deviation feedback submodule is called to perform contour surface fitting error calculation and feedback calculation evaluation results.

[0183] Step 34: Data Storage

[0184] Optimized contour surface data storage is performed. At the same time, relevant data is transmitted to the trajectory / key positioning point subset in the device information set of the task data configuration library (TDC) for use in operation task data integration.

[0185] Step 4: Operation Task Configuration

[0186] Step 41: The task configuration module reads the component operation plan set from the task data configuration library, performs periodic operation plan information or regular operation plan information parsing according to preset requirements, performs plan data assembly by the operation plan configuration submodule, and stores the assembly result in the configuration process information set;

[0187] Step 42: The task configuration module reads the component operation device information set from the task data configuration library, performs device technical parameter and control card interface adaptation information parsing according to preset requirements, performs device related data assembly by the operation device configuration submodule, and stores the assembly result in the configuration process information set;

[0188] Step 43: The task configuration module reads the personnel information set from the task data configuration library, performs operation authorization and historical task information parsing according to preset requirements, performs operation personnel related data assembly by the operation personnel configuration submodule, and stores the assembly result in the configuration process information set;

[0189] Step 44: According to the calculation results of steps 41 to 43, the task configuration module reads the report framework set from the task data configuration library, performs report type parsing (periodic report or regular report) according to preset requirements, completes report related data assembly to form complete task configuration data, and stores the assembly result in the configuration process information set;

[0190] Step 45: According to the results of step 44, complete task configuration data is transmitted to the task generation module through the data interaction interface;

[0191] Step 5: Operation Task Generation

[0192] Step 51: The task generation module obtains task configuration data from the task configuration module through the data interaction interface;

[0193] Step 52: The task generation module calls the motion control data integration submodule of the task data integration tool, executes the parameter configuration of each motion axis of the motion operation device through the technical parameter dynamic calculation submodule, and stores the configuration result into the assembly process information set; during the configuration calculation, the task data integration tool accesses the task data configuration library for necessary information supplement;

[0194] Step 53: The task generation module calls the operation object data integration submodule, the task resource data integration submodule, and the task report framework integration submodule of the task data integration tool, executes the data assembly required for the operation report through the process parameter intelligent calculation submodule, and stores the assembly result into the assembly process information set; during the configuration calculation, the task data integration tool accesses the task data configuration library for necessary information supplement;

[0195] Step 54: Based on the assembly results of steps 51 to 53, the task generation module executes the final configuration and merging of the task entry information through the task assembly submodule, and stores the merging result into the assembly process information set;

[0196] Step 55: According to the result of step 54, the final task entry data is transmitted to the task execution module through the data interaction interface;

[0197] Step 6: Task execution and recording

[0198] Step 61: The task execution module obtains the task entry data from the task generation module through the data interaction interface;

[0199] Step 62: The task execution module executes data analysis through the task entry processing submodule, and stores the analysis process data into the task process information set;

[0200] Step 63: According to the preset requirements and the actual needs of the on-site operation, the full-automatic operation submodule of the task execution module can perform full-automatic operation, and the state information of each motion axis, the trajectory record information, and the non-destructive testing signal feedback information during the operation process are uniformly stored into the task process information set; in the manual operation mode, the semi-automatic execution submodule of the task execution module cooperates with the operator to perform the operation work, and the state information of each motion axis, the trajectory record information, and the non-destructive testing signal feedback information during the operation process are uniformly stored into the task process information set;

[0201] Step 64: After the completion of steps 61 to 63, the operation process data integration submodule of the task execution module reads the task process information set, executes the integration and assembly of the data required for the operation report, and forms the TDC file required for the operation report generation;

[0202] Step 65: The TDC file generated by the assembly result of step 64 is transmitted to the operation report generation module through the data interaction interface;

[0203] Step 7: Operation result feedback

[0204] Step 71: Obtain the TDC file delivered by the task execution module through the data interaction interface;

[0205] Step 72: Execute TDC file analysis by the TDC file record traversal submodule and the TDC file processing submodule of the operation report generation module, and store the analysis data into the report generation process information set;

[0206] Step 73: Execute key information classification and reading of the analysis data of step 72 by the operation result data integration submodule of the operation report generation module, and store the reading data into the report generation process information set;

[0207] Step 74: Based on the results of step 73, generate and export the final format file of the operation report according to the actual report generation requirements on site through the WORD file generation module or the PDF file generation module of the operation report generation module;

[0208] Step 75: According to the operation report and the corresponding operation result obtained in step 74, the operation report can be delivered to the task data integration tool through the data interaction interface, uploaded and updated to the task data configuration library, and the historical operation result is archived. Step 74 executes the generation of the WORD file and the PDF file of the inspection report by the WORD file generation submodule and the PDF file generation submodule.

Claims

1. A positioning system for a fuel assembly handling robot based on adaptive contour feature matching, characterized in that: Includes global surface optimization tools, fitted profile surface evaluation and optimization tools, task data integration tools, and task data configuration libraries; The global surface optimization tool converts the acquired contour data into optimized ideal contour surface information by constraining the changes in the smoothness and curvature of the contour surface. The fitted contour surface evaluation and optimization tool is used to perform quality evaluation and comprehensive error optimization calculation on the contour surface generated by the fitting operation. It determines the fitting accuracy of the contour surface by collecting sampling points to evaluate the distance error and feeds back the overall deviation evaluation result of the fitted contour surface. The task data integration tool is an algorithmic tool for configuring relevant data during the execution of component operations; The task data integration tool constructs a data warehouse and obtains trajectory data corresponding to the contour from the contour surface optimization module.

2. The fuel assembly operation robot positioning system based on adaptive contour feature matching as described in claim 1, characterized in that: The global surface optimization tool includes a set of contour surface smoothing constraint conditions, a contour surface smoothing constraint submodule, a curvature variation constraint submodule, and an optimization result calculation submodule. The contour surface smoothing constraint set is used for centralized storage of constraint data, including position constraints and boundary constraints. The position constraints are used to ensure the approximation accuracy of the contour surface to the original data points, and the boundary constraints are used to ensure that the boundary conditions of the contour surface along the parameter line direction remain unchanged during the contour surface smoothing process. The contour surface smoothing constraint submodule is used to establish a simplified contour surface strain energy model, and the contour surface smoothing constraint function is realized through this model. The curvature variation constraint submodule is used to establish a curvature variation model of the contour surface. It uses the second-order difference of the contour surface curvature along the dual isoparametric direction to approximate the two partial derivatives of the contour surface curvature, and solves the partial derivatives by fitting the contour surface expression. The curvature variation constraint function is realized through this model. The optimization result calculation submodule is based on the contour surface smoothing constraint and curvature change constraint model. The contour surface smoothing model is solved by using a quadratic programming method with linear constraints and contour surface control vertices as variables to solve the model expression and establish a contour surface optimization model that includes contour surface smoothing constraint criteria, thereby realizing the contour surface result optimization calculation function.

3. The fuel assembly operation robot positioning system based on adaptive contour feature matching as described in claim 1, characterized in that: The fitted contour surface evaluation and optimization tool includes an evaluation benchmark construction submodule, an average error calculation submodule, and a comprehensive deviation feedback submodule. The evaluation benchmark construction submodule is used to establish the evaluation benchmark, construct the equation of the tangent plane of the corresponding points on the fitted contour surface through the plane projection points of the collection points, and solve the equation of the tangent plane by substituting the normal vectors of the corresponding points to obtain the evaluation benchmark model. The average error calculation submodule is used to calculate the shortest distance from the sampling point to the fitted contour surface; The integrated deviation feedback submodule is used to calculate the overall error of the contour surface fitting; the fitting error of the contour surface can be calculated based on the average error. When the fitting deviation meets the detection requirements, the fitted contour surface is the outer surface contour of the fuel assembly to be operated.

4. The fuel assembly operation robot positioning system based on adaptive contour feature matching as described in claim 1, characterized in that: The task data integration tool includes a task report framework integration submodule, an operation object data integration submodule, a task resource data integration submodule, a motion control data integration submodule, an integration process information set, and a data interaction interface. The task report framework integration submodule obtains data from the component operation plan set, equipment information set, personnel information set, and report framework set in the task data configuration library through a data interaction interface, and generates an operation report framework data combination G based on the pre-set report template in the report framework set. mr-f It engages in bidirectional data interaction with the task generation module and operation report generation module through a data interaction interface. The operation object data integration submodule obtains data from the component operation plan set in the task data configuration library through a data interaction interface, and generates operation object data combination G. m-o It engages in bidirectional data interaction with the task generation module and operation report generation module through a data interaction interface. The task resource data integration submodule obtains data from the component operation plan set and personnel information set in the task data configuration library through a data interaction interface, and generates a task resource data combination G. t-r It engages in bidirectional data interaction with the task generation module and operation report generation module through a data interaction interface. The motion control data integration submodule obtains device parameter information and control card interface authorization from the device information set in the task data configuration library through a data interaction interface, and generates motion control data combination G. m-c It engages in bidirectional data interaction with the task generation module and operation report generation module through a data interaction interface. The integration process information set provides a temporary storage intermediate data group G during the integration and assembly calculation process. t-s ; The data interaction interface is used to perform data interaction and transmission between functional modules.

5. The fuel assembly operation robot positioning system based on adaptive contour feature matching as described in claim 1, characterized in that: The task data integration tool includes a task data configuration library index, a component operation plan set, a device information set, a personnel information set, and a report framework set; The data configuration library index I d-w Record the registration information of all datasets in the current task data configuration library, including the number of entries in the subset SC. n Data Relationship Subset SC r Key Field Subset SC k Data update status subset SC s The structure is I d-w <SC n |SC r |SC k |SC s >; The component operation plan set C p Record operational plan information, including a subset of periodic operational plans (SP). st-p Standard Operating Procedures (SP) rt-p The structure is C p <SP st-p |SP rt-p >; The device information set C d Record information related to the operating device, including a subset of device parameters SD. d-p Control card interface subset SD c-i Equipment trajectory / key positioning point information subset SD t-loc The structure is C d <SD d-p |SD c-i |SD t-loc >; The personnel information set C m Record information about the personnel performing the operation, including the operation authorization subset SM. p-c Historical mission subset SM p-h The structure is C m <SM p-c SM p-h >; The report framework set C r Record information related to operation report files, including a subset of periodic reports (SR). s-r Regular Report Subset SR c-r The structure is C r <SR s-r |SR c-r > 6. A method for locating a fuel assembly manipulator robot based on adaptive contour feature matching, characterized in that, Includes the following steps: Step 1: Contour data sampling; Step 2: Initial contour surface generation; Step 3: Contour surface contour fitting optimization; Step 4: Configure operation tasks; Step 5: Task generation; Step 6: Task execution and recording; Step 7: Feedback on operation results.

7. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 1 includes: Step 11: Data Channel Construction Initialize the sensor interface and acquire real-time data from the coordinate measuring machine and distance measuring probes; Step 12: Data Framework Construction The scanning strategy generation submodule generates the scanning strategy and creates the scanning path and sampling interval data. Step 13: Save data content The scanning contour generation submodule generates scanning contour data and saves the coarse contour point cloud data.

8. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 2 includes: Step 21: Data Loading Call the coarse outline data loading interface to perform the data loading operation; Step 22: Constraint Construction The data construction of the constraint condition set includes one-to-one correspondence, shape similarity, and smoothness; Step 23: Calculation of initial profile surface parameters Call the initial contour surface parameter calculation submodule to solve for the initial contour surface parameter values ​​of the data points; Step 24: Solving the overdetermined linear equation system Call the error calculation submodule to establish the overdetermined linear equation system and solve it using the Haushard transform method; Step 25: Error Comparison Calculation Perform error vector calculation and error threshold comparison iteration to generate the initial contour surface.

9. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 3 includes: Step 31: Data Loading Load the initial contour surface data and store it in the initial contour surface data repository. Step 32: Global Surface Optimization The process involves: invoking the global surface optimization tool to apply surface smoothing and curvature variation constraints; invoking the surface smoothing constraint submodule to establish a simplified expression for surface strain energy; invoking the curvature variation constraint submodule to establish and solve the surface curvature variation expression; invoking the optimization result calculation submodule to establish a generalized energy expression incorporating the surface smoothing criterion based on surface strain energy variation and curvature variation; and invoking the optimization result calculation submodule to solve the surface smoothing model and obtain the optimized data. Step 33: Fitting Contour Surface Optimization The process involves calling the fitted contour surface evaluation and optimization tool to perform evaluation benchmark construction, average error calculation, and comprehensive deviation feedback; calling the evaluation benchmark construction submodule to establish the tangent plane equation; calling the average error calculation submodule to calculate the shortest distance from the sampling point to the contour surface; and calling the comprehensive deviation feedback submodule to calculate the contour surface fitting error and provide feedback on the evaluation results. Step 34: Data Storage The system optimizes the data storage of the contour surface and simultaneously transfers the relevant data to a subset of trajectory / key positioning points in the device information set of the task data configuration library for use in the integration of operational task data.

10. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 4 includes: Step 41: The task configuration module reads the component operation plan set from the task data configuration library, performs parsing of periodic operation plan information or regular operation plan information according to preset requirements, and the operation plan configuration submodule performs plan data assembly. The assembly result is stored in the configuration process information set. Step 42: The task configuration module reads the component operation device information set from the task data configuration library, performs parsing of device technical parameters and control card interface adaptation information according to preset requirements, and the operation device configuration submodule performs device-related data assembly. The assembly result is stored in the configuration process information set. Step 43: The task configuration module reads the personnel information set from the task data configuration library, performs operation authorization and parsing of historical task information according to preset requirements, and the configuration sub-module performs relevant data assembly. The assembly result is stored in the configuration process information set. Step 44: Based on the calculation results of steps 41 to 43, the task configuration module reads the report framework set from the task data configuration library, performs report type parsing according to preset requirements, completes the assembly of report-related data to form complete task configuration data, and stores the assembly result in the configuration process information set; Step 45: Based on the results of Step 44, transmit the complete task configuration data to the task generation module through the data interaction interface.

11. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 5 includes: Step 51: The task generation module obtains task configuration data from the task configuration module through the data interaction interface; Step 52: The task generation module calls the motion control data integration submodule of the task data integration tool, and executes the configuration of each motion axis parameter of the motion operation device through the technical parameter dynamic calculation submodule. The configuration result is stored in the assembly process information set. During the configuration calculation process, the task data integration tool accesses the task data configuration library to supplement information. Step 53: The task generation module calls the operation object data integration submodule, task resource data integration submodule, and task report framework integration submodule of the task data integration tool. It then uses the process parameter intelligent calculation submodule to assemble the data required for the operation report and stores the assembly results in the assembly process information set. During the configuration calculation process, the task data integration tool accesses the task data configuration library to supplement information. Step 54: Based on the assembly results of steps 51 to 53, the task generation module performs the final configuration and merging of task item information through the task assembly submodule, and the merging result is stored in the assembly process information set. Step 55: Based on the results of Step 54, transmit the final task entry data to the task execution module through the data interaction interface.

12. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 6 includes: Step 61: The task execution module obtains task entry data from the task generation module through the data interaction interface; Step 62: The task execution module performs data parsing through the task entry processing submodule, and the parsing process data is stored in the task process information set; Step 63: According to the preset requirements and the actual needs of on-site operation, the fully automatic execution submodule of the task execution module performs fully automatic operation. During the operation, the status information of each motion axis, trajectory recording information, and non-destructive testing signal feedback information are uniformly stored in the task process information set. In manual operation mode, the semi-automatic execution submodule of the task execution module performs the operation. During the operation, the status information of each motion axis, trajectory recording information, and non-destructive testing signal feedback information are uniformly stored in the task process information set. Step 64: After the tasks in steps 61 to 63 are completed, the operation process data integration submodule of the task execution module reads the task process information set, performs the integration and assembly of the data required for the operation report, and forms the TDC file required for the generation of the applicable operation report. Step 65: The TDC file generated from the assembly results in Step 64 is transmitted to the operation report generation module through the data interaction interface.

13. The method for locating a fuel assembly manipulator robot based on adaptive contour feature matching as described in claim 6, characterized in that, Step 7 includes: Step 71: Obtain the TDC file transmitted by the task execution module through the data interaction interface; Step 72: Perform TDC file parsing by traversing the TDC file record of the operation report generation module and the TDC file processing module, and store the parsed data into the report generation process information set; Step 73: The operation result data integration submodule of the operation report generation module performs key information classification and reading on the parsed data of step 72, and stores the read data into the report generation process information set; Step 74: Based on the results of Step 73, and according to the actual on-site report generation requirements, use the WORD file generation module or PDF file generation module of the operation report generation module to generate and export the final format of the operation report. Step 75: Based on the operation report and corresponding operation results obtained in Step 74, the data is transmitted to the task data integration tool through the data interaction interface, uploaded and updated to the task data configuration library, and historical operation results are archived. Step 74 is executed by the WORD file generation submodule and the PDF file generation submodule to generate the inspection report WORD file and PDF file.

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