Vehicle body comprehensive gauge matching degree evaluation method and system

Abstract

The invention provides a method and a system for evaluating the matching degree of an automobile body comprehensive testing fixture. The method comprises the following steps: respectively acquiring first multi-modal data of an automobile body and second multi-modal data of the comprehensive testing fixture; based on a pre-established vehicle body-gauge matching model, matching the vehicle body with the comprehensive gauge according to the first multi-modal data and the second multi-modal data to obtain a matching result; based on the matching result, the matching degree is evaluated, and an adjustment suggestion of the comprehensive testing fixture is decided; and outputting a matching result, a matching degree and an adjustment suggestion. According to the invention, a worker does not need to manually match the design model or sample of the comprehensive testing fixture with the automobile body according to experience, the labor cost is reduced, the design efficiency of the comprehensive testing fixture is improved, the worker does not need to adjust and decide the designed comprehensive testing fixture according to the matching condition, and the method is very intelligent.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile body detection, and in particular to a matching evaluation method and system for a comprehensive vehicle body inspection tool. Background Art

[0002] At present, in order to inspect the automobile body more efficiently, it is necessary to design a comprehensive inspection fixture, which can be used to inspect multiple components of the automobile body at the same time.

[0003] However, when designing a comprehensive inspection fixture, it is necessary to fully ensure the matching degree between the designed comprehensive inspection fixture and the automobile body, so as to ensure that the comprehensive inspection fixture is competent for inspecting the automobile body.

[0004] However, the matching degree between the designed comprehensive inspection fixture and the car body is mostly determined by the staff based on their experience, matching the design model or sample of the comprehensive inspection fixture with the car body. This has a high labor cost and reduces the design efficiency of the comprehensive inspection fixture. Secondly, the staff needs to make adjustments to the designed comprehensive inspection fixture according to the matching situation, which is not intelligent enough.

[0005] Therefore, a solution is urgently needed. Summary of the invention

[0006] One of the purposes of the present invention is to provide a method for evaluating the matching degree of a vehicle body comprehensive inspection tool. Based on a pre-established vehicle body-inspection tool matching model, the vehicle body is matched with the comprehensive inspection tool according to the first multimodal data of the vehicle body and the second multimodal data of the comprehensive inspection tool to obtain a matching result. Based on the matching result, the matching degree is evaluated and the adjustment suggestion of the comprehensive inspection tool is decided. There is no need for the staff to manually match the design model or sample of the comprehensive inspection tool with the vehicle body based on experience, which reduces the labor cost and improves the design efficiency of the comprehensive inspection tool. There is no need for the staff to make adjustment decisions on the designed comprehensive inspection tool according to the matching situation, which is very intelligent.

[0007] An embodiment of the present invention provides a method for evaluating the matching degree of a vehicle body comprehensive inspection tool, comprising:

[0008] respectively acquiring first multimodal data of the automobile body and second multimodal data of the comprehensive inspection fixture;

[0009] Based on a pre-established vehicle body-gauge matching model, the vehicle body is matched with the comprehensive gauge according to the first multimodal data and the second multimodal data to obtain a matching result;

[0010] Based on the matching results, evaluate the matching degree and make adjustment suggestions for the comprehensive inspection tool;

[0011] Output matching results, matching degree and adjustment suggestions.

[0012] Preferably, the output of the matching results, matching degree and adjustment suggestions includes:

[0013] Based on the matching results and the matching degree, a first visualization model is generated;

[0014] displaying the first visualization model to a user;

[0015] Acquire model record information generated by the user based on the first visualization model within a first period; wherein the start time of the first period is the time when the user starts to view the first visualization model, and the end time is the time when the user first generates a standard model viewing behavior;

[0016] Extract features from model record information to obtain information features;

[0017] Based on the feature partitioning rules, information features are divided into feature sets;

[0018] Determine the indication strategy corresponding to the feature set from the indication strategy library; the indication strategy includes: setting area search rules and target suggestion search rules;

[0019] Based on the setting area search rule, searching for the setting area from the first visualization model;

[0020] Based on the target suggestion search rule, the target suggestion is searched out from the adjustment suggestions;

[0021] The target suggestion is continuously set in the setting area during the second time period; wherein the duration of the second time period is a preset duration value, and is after the second time period and adjacent to the first time period.

[0022] Preferably, the feature division rules include:

[0023] When there is a first target feature in the information feature that matches the trigger feature, a second target feature generated after the first target feature and meeting the feature requirement condition corresponding to the trigger feature is determined from the information feature;

[0024] Combining the first target feature and the second target feature into a feature set;

[0025] and / or,

[0026] Retrieve the standard feature type set;

[0027] Combining the third target features in the information features into a feature set, so that the feature type set formed by combining the feature types of the third target features in the feature set matches the standard feature type set;

[0028] and / or,

[0029] The fourth target features in the information features are combined into a feature set, so that the fourth target features in the feature set have the same corresponding representation type in the representation type library or have a representation type association relationship.

[0030] Preferably, after continuously setting the target suggestion in the setting area during the second period, the method further includes:

[0031] When the user adopts the target suggestion, a second visualization model is generated based on the second multimodal data;

[0032] Based on the target suggestions, determine the adjustment area search rules and adjustment rules;

[0033] Based on the adjustment area search rule, searching for the adjustment area from the second visualization model;

[0034] Coordinately display the setting area and the adjustment area to the user;

[0035] Parse the adjustment process sequence of the adjustment rules;

[0036] According to the sequence order of the adjustment processes in the adjustment process sequence, the adjustment processes are executed on the adjustment areas in sequence;

[0037] Each time the adjustment process is executed, when the adjustment process executed meets the standard process conditions and / or the user requests to modify the adjustment process executed, a process modification interface of the adjustment process executed is generated;

[0038] Display the process modification interface to the user;

[0039] Obtain modification instructions input by the user based on the process modification interface;

[0040] Based on the modification instructions, modify the executed adjustment process;

[0041] Relay executes the modified adjustment process on the adjustment area.

[0042] Preferably, the standard process conditions include:

[0043] The process weight of the executed adjustment process is greater than or equal to the first weight threshold;

[0044] and / or,

[0045] The process weights and sums of adjustment processes that have been executed historically are greater than or equal to the weight and threshold;

[0046] and / or,

[0047] The process weight of the subsequent adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold; the second weight threshold is greater than the first weight threshold.

[0048] An embodiment of the present invention provides a vehicle body comprehensive inspection tool matching evaluation system, comprising:

[0049] An acquisition module, used to respectively acquire first multimodal data of the automobile body and second multimodal data of the comprehensive inspection fixture;

[0050] A matching module, for matching the automobile body with the comprehensive inspection fixture based on a pre-established vehicle body-inspection fixture matching model and the first multimodal data and the second multimodal data to obtain a matching result;

[0051] Evaluation module, used to evaluate the matching degree based on the matching results and make adjustment suggestions for the comprehensive inspection tool;

[0052] The output module is used to output matching results, matching degree and adjustment suggestions.

[0053] Preferably, the output module outputs the matching results, matching degree and adjustment suggestions, including:

[0054] Based on the matching results and the matching degree, a first visualization model is generated;

[0055] displaying the first visualization model to a user;

[0056] Acquire model record information generated by the user based on the first visualization model within a first period; wherein the start time of the first period is the time when the user starts to view the first visualization model, and the end time is the time when the user first generates a standard model viewing behavior;

[0057] Extract features from model record information to obtain information features;

[0058] Based on the feature partitioning rules, information features are divided into feature sets;

[0059] Determine the indication strategy corresponding to the feature set from the indication strategy library; the indication strategy includes: setting area search rules and target suggestion search rules;

[0060] Based on the setting area search rule, searching for the setting area from the first visualization model;

[0061] Based on the target suggestion search rule, the target suggestion is searched out from the adjustment suggestions;

[0062] The target suggestion is continuously set in the setting area during the second time period; wherein the duration of the second time period is a preset duration value, and is after the second time period and adjacent to the first time period.

[0063] Preferably, the feature division rules include:

[0064] When there is a first target feature in the information feature that matches the trigger feature, a second target feature generated after the first target feature and meeting the feature requirement condition corresponding to the trigger feature is determined from the information feature;

[0065] Combining the first target feature and the second target feature into a feature set;

[0066] and / or,

[0067] Retrieve the standard feature type set;

[0068] Combining the third target features in the information features into a feature set, so that the feature type set formed by combining the feature types of the third target features in the feature set matches the standard feature type set;

[0069] and / or,

[0070] The fourth target features in the information features are combined into a feature set, so that the fourth target features in the feature set have the same corresponding representation type in the representation type library or have a representation type association relationship.

[0071] Preferably, after the output module continuously sets the target suggestion in the setting area during the second period, the output module further includes:

[0072] Interaction modules for:

[0073] When the user adopts the target suggestion, a second visualization model is generated based on the second multimodal data;

[0074] Based on the target suggestions, determine the adjustment area search rules and adjustment rules;

[0075] Based on the adjustment area search rule, searching for the adjustment area from the second visualization model;

[0076] Coordinately display the setting area and the adjustment area to the user;

[0077] Parse the adjustment process sequence of the adjustment rules;

[0078] According to the sequence order of the adjustment processes in the adjustment process sequence, the adjustment processes are executed on the adjustment areas in sequence;

[0079] Each time the adjustment process is executed, when the adjustment process executed meets the standard process conditions and / or the user requests to modify the adjustment process executed, a process modification interface of the adjustment process executed is generated;

[0080] Display the process modification interface to the user;

[0081] Obtain modification instructions input by the user based on the process modification interface;

[0082] Based on the modification instructions, modify the executed adjustment process;

[0083] Relay executes the modified adjustment process on the adjustment area.

[0084] Preferably, the standard process conditions include:

[0085] The process weight of the executed adjustment process is greater than or equal to the first weight threshold;

[0086] and / or,

[0087] The process weights and sums of adjustment processes that have been executed historically are greater than or equal to the weight and threshold;

[0088] and / or,

[0089] The process weight of the subsequent adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold; the second weight threshold is greater than the first weight threshold.

[0090] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0091] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0093] Figure 1 A schematic diagram of a vehicle body comprehensive inspection fixture matching evaluation method according to an embodiment of the present invention;

[0094] Figure 2 Schematic diagram of a vehicle body comprehensive inspection fixture matching evaluation system in an embodiment of the present invention. DETAILED DESCRIPTION

[0095] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0096] The embodiment of the present invention provides a method for evaluating the matching degree of a vehicle body comprehensive inspection tool. Figure 1 As shown, including:

[0097] S1, respectively obtaining first multimodal data of the automobile body and second multimodal data of the comprehensive inspection fixture;

[0098] S2, based on a pre-established vehicle body-gauge matching model, matching the vehicle body with the comprehensive gauge according to the first multimodal data and the second multimodal data to obtain a matching result;

[0099] S3. Based on the matching results, evaluate the matching degree and make adjustment suggestions for the comprehensive inspection tool;

[0100] S4. Output matching results, matching degree and adjustment suggestions.

[0101] The first multimodal data includes: the size data of the automobile body, the 3D scanning model, etc.; the second multimodal data includes: the design specifications, size data, 3D scanning model, etc. of the comprehensive inspection tool; a body-inspection tool matching model is pre-established, and the body-inspection tool matching model can match the automobile body with the comprehensive inspection tool according to the first multimodal data and the second multimodal data to obtain a matching result; the body-inspection tool matching model can be a matching rule between the automobile body and the comprehensive inspection tool set by the technician, an analysis standard for the matching situation, etc., for example: installing the 3D scanning model of the comprehensive inspection tool on the 3D scanning model of the automobile body, analyzing the fit, etc.; based on the matching result, the matching degree is evaluated, and the adjustment suggestion of the comprehensive inspection tool is decided. When evaluating the matching degree, the matching degree evaluation standard set by the technician can be used, for example: when the fit is 100%, the matching degree is output as 100%. When deciding the adjustment suggestion, the deficiencies of the comprehensive inspection tool can be determined, and adjustment suggestions can be given according to the deficiencies; finally, the matching result, matching degree and adjustment suggestion are output.

[0102] The present application is based on a pre-established vehicle body-gauge fixture matching model. According to the first multimodal data of the vehicle body and the second multimodal data of the comprehensive gauge fixture, the vehicle body is matched with the comprehensive gauge fixture to obtain a matching result. Based on the matching result, the matching degree is evaluated and adjustment suggestions for the comprehensive gauge fixture are decided. There is no need for staff to manually match the design model or sample of the comprehensive gauge fixture with the vehicle body based on experience, which reduces labor costs and improves the design efficiency of the comprehensive gauge fixture. There is no need for staff to make adjustments and decisions on the designed comprehensive gauge fixture based on the matching situation, which is very intelligent.

[0103] In one embodiment, the outputting of the matching results, matching degree and adjustment suggestions includes:

[0104] Based on the matching results and the matching degree, a first visualization model is generated;

[0105] The first visualization model is displayed to the user; the user can intuitively and comprehensively view the matching results and the matching degree by viewing the first visualization model; when generating the first visualization model, a three-dimensional model of the matching part (the part where the comprehensive inspection tool fits the car body, etc.) and the non-matching part (the part where the comprehensive inspection tool does not fit the car body, etc.) in the matching result can be generated and used as the first visualization model;

[0106] Obtain model record information generated by the user based on the first visual model within the first time period; wherein the start time of the first time period is the time when the user starts to view the first visual model, and the end time is the time when the user first generates a standard model viewing behavior; the user may be a design manager of a comprehensive inspection fixture, etc.; the model record information may be the sequential viewing content of the user viewing the first visual model, the model operation generated when viewing the first visual model, etc.; when the user generates a standard model viewing behavior, it means that the user needs to be assisted by adjustment suggestions, for example: the standard model viewing behavior is to continuously view the part of the same comprehensive inspection fixture that does not fit the car body for more than 3 minutes, indicating that the user is thinking about how to adjust the comprehensive inspection fixture of this part and needs to be assisted by adjustment suggestions;

[0107] Extract features of the model record information to obtain information features; the information features are features of the model record information, such as: the content types that are viewed in sequence, etc.;

[0108] Based on the feature partitioning rules, information features are divided into feature sets;

[0109] Determine the indication strategy corresponding to the feature set from the indication strategy library; the indication strategy includes: setting area search rules and target suggestion search rules; a feature set represents a situation in which the user needs to be assisted by adjustment suggestions, and there are indication strategies corresponding to different feature sets in the indication strategy library, and the indication strategy is a strategy for indicating how the system uses the adjustment suggestions for future assistance in this situation; setting area search rules is a rule for searching for areas where target suggestions are set, and the target suggestion search rules are rules for searching for target suggestions in the adjustment suggestions that are valuable for user assistance, for example: if the information feature in the feature set is to check the part where the rear of the car does not fit the comprehensive inspection fixture, then the corresponding setting area is the rear part of the car in the first visualization model, and the target suggestion is a suggestion for adjusting the comprehensive inspection fixture related to the rear part of the car;

[0110] Based on the setting area search rule, searching for the setting area from the first visualization model;

[0111] Based on the target suggestion search rule, the target suggestion is searched out from the adjustment suggestions;

[0112] The target suggestion is continuously set in the setting area during the second time period, wherein the duration of the second time period is a preset duration value, and is after the second time period and adjacent to the first time period. The preset duration value may be 3 minutes.

[0113] When outputting matching results, matching degrees and adjustment suggestions, the embodiment of the present invention introduces a first visualization model, obtains model record information, determines an indication strategy based on the model record information, and assists users based on the indication strategy, which greatly improves the humanization and is more intelligent; it is convenient for users to quickly adjust the comprehensive inspection tool in combination with the system output.

[0114] In one embodiment, the feature partitioning rules include:

[0115] When there is a first target feature in the information feature that matches the trigger feature, a second target feature generated after the first target feature and meeting the feature requirement condition corresponding to the trigger feature is determined from the information feature; the first target feature that matches the trigger feature and the second target feature selected using the feature requirement condition can form a feature set, representing a situation in which the user needs to be assisted by adjustment suggestions, for example: the trigger feature is to check the right rearview mirror part of the car body with a low fit to the comprehensive inspection fixture, and the feature requirement condition is to select the feature of checking the left rearview mirror part of the car body with a low fit to the comprehensive inspection fixture. In this way, the first target feature and the second target feature reflect the situation in which the user needs to adjust the part of the comprehensive inspection fixture that checks the left and right rearview mirrors of the car and obtains auxiliary suggestions;

[0116] Combining the first target feature and the second target feature into a feature set;

[0117] and / or,

[0118] Retrieve the standard feature type set;

[0119] The third target features in the information features are combined into a feature set, so that the feature type set formed by the feature types of the third target features in the feature set matches the standard feature type set; a standard feature type set can also be set to combine the third target features in the information features into a feature set, so that the feature type set formed by the feature types of the third target features in the feature set matches the standard feature type set; the third target features of each feature type in the feature type set can jointly represent a situation in which the user needs to be assisted by adjustment suggestions; for example: the feature types in the standard feature type set are to check the part where the headlights of the car body are not fitted in the comprehensive inspection fixture, check the internal structure of the headlights of the car body, etc., which means that the user needs to be assisted in adjusting the part of the comprehensive inspection fixture corresponding to the headlights of the car body;

[0120] and / or,

[0121] The fourth target features in the information features are combined into a feature set, so that the fourth target features in the feature set have the same corresponding representation types in the representation type library or have a representation type association relationship. There are representation types corresponding to different fourth target features in the representation type library, and the representation type represents the type of assistance that the user wants to get assistance; when the representation types of different fourth target features have a representation type association relationship, it means that different fourth target features can jointly represent a situation in which the user needs to get assistance with adjustment suggestions; when the representation types of different fourth target features are the same, they can also jointly represent a situation in which the user needs to get assistance with adjustment suggestions; for example: the representation types of the fourth target features in the feature set are all characterized as the need to get adjustment assistance for the part of the comprehensive inspection fixture corresponding to the car body.

[0122] The model records information with many information features. It is complicated to directly determine the situations in which users need assistance with adjustment suggestions based on all the information features, and the efficiency of determination is also low. The embodiment of the present invention can solve this problem; it introduces multiple feature division rules, divides the information features, and forms feature sets, so that each feature set represents a situation in which the user needs assistance with adjustment suggestions, which greatly improves the working efficiency of the system.

[0123] In one embodiment, after continuously setting the target suggestion in the setting area during the second period, the method further includes:

[0124] When the user adopts the target suggestion, a second visualization model is generated based on the second multimodal data; the second visualization model may be a three-dimensional model of the comprehensive inspection tool;

[0125] Based on the target suggestion, determine the adjustment area search rules and adjustment rules; the target suggestion will point out the area where the comprehensive inspection tool needs to be adjusted, then the adjustment area search rules can be determined, and it will also point out how to adjust, then the adjustment rules will be determined;

[0126] Based on the adjustment area search rule, searching for the adjustment area from the second visualization model;

[0127] Coordinately display the setting area and the adjustment area to the user;

[0128] Parse the adjustment process sequence of the adjustment rule; the adjustment process sequence includes multiple adjustment processes when the adjustment rule is executed;

[0129] According to the sequence order of the adjustment processes in the adjustment process sequence, the adjustment processes are executed on the adjustment areas in sequence;

[0130] Each time the adjustment process is executed, when the adjustment process executed meets the standard process conditions and / or the user requests to modify the adjustment process executed, a process modification interface of the adjustment process executed is generated;

[0131] A process modification interface is displayed to the user; the process modification interface has multiple options for modifying the execution process, and modification instructions can be entered based on the option selection;

[0132] Obtain modification instructions input by the user based on the process modification interface;

[0133] Based on the modification instructions, modify the executed adjustment process;

[0134] Relay executes the modified adjustment process on the adjustment area.

[0135] In one embodiment, the standard process conditions include:

[0136] The process weight of the executed adjustment process is greater than or equal to the first weight threshold;

[0137] and / or,

[0138] The process weights and sums of adjustment processes that have been executed historically are greater than or equal to the weight and threshold;

[0139] and / or,

[0140] The process weight of the subsequent adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold; the second weight threshold is greater than the first weight threshold.

[0141] When the executed adjustment process meets the standard process conditions, it means that the user needs to be assisted to modify the executed adjustment process; in the standard process conditions, the larger the adjustment weight of the adjustment process, the greater the degree of change to the comprehensive inspection fixture after the adjustment process is executed; the first weight threshold can be 8; the second weight threshold can be 12; the weight and threshold can be 35; when the process weight of the executed adjustment process is greater than or equal to the first weight threshold, the degree of change is large, and the user may need to adjust the process; when the process weight and the process weight of the adjustment process executed in history are greater than or equal to the weight and threshold, it means that the overall degree of change in history is large, and the user may need to adjust the process; when the process weight of the next adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold, it means that when executing the next adjustment process, the degree of change is large, and when executing the previous adjustment process, it is necessary to ensure that the process execution is reasonable, and the user may need to adjust the process. Setting multiple standard process conditions fully guarantees the accuracy and rationality of the timing of assisting users to modify the process, and is also more humane.

[0142] The embodiment of the present invention provides a vehicle body comprehensive inspection tool matching evaluation system, such as Figure 2 As shown, including:

[0143] An acquisition module 1 is used to respectively acquire first multimodal data of the vehicle body and second multimodal data of the comprehensive inspection fixture;

[0144] A matching module 2 is used to match the automobile body with the comprehensive inspection fixture based on a pre-established vehicle body-inspection fixture matching model and the first multimodal data and the second multimodal data to obtain a matching result;

[0145] Evaluation module 3 is used to evaluate the matching degree based on the matching results and make adjustment suggestions for the comprehensive inspection tool;

[0146] The output module 4 is used to output the matching results, matching degree and adjustment suggestions.

[0147] The output module outputs the matching results, matching degree and adjustment suggestions, including:

[0148] Based on the matching results and the matching degree, a first visualization model is generated;

[0149] displaying the first visualization model to a user;

[0150] Acquire model record information generated by the user based on the first visualization model within a first period; wherein the start time of the first period is the time when the user starts to view the first visualization model, and the end time is the time when the user first generates a standard model viewing behavior;

[0151] Extract features from model record information to obtain information features;

[0152] Based on the feature partitioning rules, information features are divided into feature sets;

[0153] Determine the indication strategy corresponding to the feature set from the indication strategy library; the indication strategy includes: setting area search rules and target suggestion search rules;

[0154] Based on the setting area search rule, searching for the setting area from the first visualization model;

[0155] Based on the target suggestion search rule, the target suggestion is searched out from the adjustment suggestions;

[0156] The target suggestion is continuously set in the setting area during the second time period; wherein the duration of the second time period is a preset duration value, and is after the second time period and adjacent to the first time period.

[0157] The feature division rules include:

[0158] When there is a first target feature in the information feature that matches the trigger feature, a second target feature generated after the first target feature and meeting the feature requirement condition corresponding to the trigger feature is determined from the information feature;

[0159] Combining the first target feature and the second target feature into a feature set;

[0160] and / or,

[0161] Retrieve the standard feature type set;

[0162] Combining the third target features in the information features into a feature set, so that the feature type set formed by combining the feature types of the third target features in the feature set matches the standard feature type set;

[0163] and / or,

[0164] The fourth target features in the information features are combined into a feature set, so that the fourth target features in the feature set have the same corresponding representation type in the representation type library or have a representation type association relationship.

[0165] After the output module continuously sets the target suggestion in the setting area during the second period, the output module further includes:

[0166] Interaction modules for:

[0167] When the user adopts the target suggestion, a second visualization model is generated based on the second multimodal data;

[0168] Based on the target suggestions, determine the adjustment area search rules and adjustment rules;

[0169] Based on the adjustment area search rule, searching for the adjustment area from the second visualization model;

[0170] Coordinately display the setting area and the adjustment area to the user;

[0171] Parse the adjustment process sequence of the adjustment rules;

[0172] According to the sequence order of the adjustment processes in the adjustment process sequence, the adjustment processes are executed on the adjustment areas in sequence;

[0173] Each time the adjustment process is executed, when the adjustment process executed meets the standard process conditions and / or the user requests to modify the adjustment process executed, a process modification interface of the adjustment process executed is generated;

[0174] Display the process modification interface to the user;

[0175] Obtain modification instructions input by the user based on the process modification interface;

[0176] Based on the modification instructions, modify the executed adjustment process;

[0177] Relay executes the modified adjustment process on the adjustment area.

[0178] The standard process conditions include:

[0179] The process weight of the executed adjustment process is greater than or equal to the first weight threshold;

[0180] and / or,

[0181] The process weights and sums of adjustment processes that have been executed historically are greater than or equal to the weight and threshold;

[0182] and / or,

[0183] The process weight of the subsequent adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold; the second weight threshold is greater than the first weight threshold.

[0184] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for evaluating the matching degree of a vehicle body comprehensive inspection tool, characterized in that: include: respectively acquiring first multimodal data of the automobile body and second multimodal data of the comprehensive inspection fixture; Based on a pre-established vehicle body-gauge matching model, the vehicle body is matched with the comprehensive gauge according to the first multimodal data and the second multimodal data to obtain a matching result; Based on the matching results, evaluate the matching degree and make adjustment suggestions for the comprehensive inspection tool; Output matching results, matching degree and adjustment suggestions.

2. The vehicle body comprehensive inspection fixture matching evaluation method according to claim 1, characterized in that: The output matching results, matching degree and adjustment suggestions include: Based on the matching results and the matching degree, a first visualization model is generated; displaying the first visualization model to a user; Acquire model record information generated by the user based on the first visualization model within a first period; wherein the start time of the first period is the time when the user starts to view the first visualization model, and the end time is the time when the user first generates a standard model viewing behavior; Extract features from model record information to obtain information features; Based on the feature partitioning rules, information features are divided into feature sets; Determine the indication strategy corresponding to the feature set from the indication strategy library; the indication strategy includes: setting area search rules and target suggestion search rules; Based on the setting area search rule, searching for the setting area from the first visualization model; Based on the target suggestion search rule, the target suggestion is searched out from the adjustment suggestions; The target suggestion is continuously set in the setting area during the second time period; wherein the duration of the second time period is a preset duration value, and is after the second time period and adjacent to the first time period.

3. The vehicle body comprehensive inspection fixture matching evaluation method as claimed in claim 2, characterized in that: The feature division rules include: When there is a first target feature in the information feature that matches the trigger feature, a second target feature generated after the first target feature and meeting the feature requirement condition corresponding to the trigger feature is determined from the information feature; Combining the first target feature and the second target feature into a feature set; and / or, Retrieve the standard feature type set; Combining the third target features in the information features into a feature set, so that the feature type set formed by combining the feature types of the third target features in the feature set matches the standard feature type set; and / or, The fourth target features in the information features are combined into a feature set, so that the fourth target features in the feature set have the same corresponding representation type in the representation type library or have a representation type association relationship.

4. The vehicle body comprehensive inspection fixture matching evaluation method as claimed in claim 2, characterized in that: After the target suggestion is continuously set in the setting area during the second period, the method further includes: When the user adopts the target suggestion, a second visualization model is generated based on the second multimodal data; Based on the target suggestions, determine the adjustment area search rules and adjustment rules; Based on the adjustment area search rule, searching for the adjustment area from the second visualization model; Coordinately display the setting area and the adjustment area to the user; Parse the adjustment process sequence of the adjustment rules; According to the sequence order of the adjustment processes in the adjustment process sequence, the adjustment processes are executed on the adjustment areas in sequence; Each time the adjustment process is executed, when the adjustment process executed meets the standard process conditions and / or the user requests to modify the adjustment process executed, a process modification interface of the adjustment process executed is generated; Display the process modification interface to the user; Obtain modification instructions input by the user based on the process modification interface; Based on the modification instructions, modify the executed adjustment process; Relay executes the modified adjustment process on the adjustment area.

5. The vehicle body comprehensive inspection fixture matching evaluation method as claimed in claim 4, characterized in that: The standard process conditions include: The process weight of the executed adjustment process is greater than or equal to the first weight threshold; and / or, The process weights and sums of adjustment processes that have been executed historically are greater than or equal to the weight and threshold; and / or, The process weight of the subsequent adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold; the second weight threshold is greater than the first weight threshold.

6. A vehicle body comprehensive inspection fixture matching evaluation system, characterized in that: include: An acquisition module, used to respectively acquire first multimodal data of the automobile body and second multimodal data of the comprehensive inspection fixture; A matching module, for matching the automobile body with the comprehensive inspection fixture based on a pre-established vehicle body-inspection fixture matching model and the first multimodal data and the second multimodal data to obtain a matching result; Evaluation module, used to evaluate the matching degree based on the matching results and make adjustment suggestions for the comprehensive inspection tool; The output module is used to output matching results, matching degree and adjustment suggestions.

7. The vehicle body comprehensive inspection fixture matching evaluation system as claimed in claim 6, characterized in that: The output module outputs the matching results, matching degree and adjustment suggestions, including: Based on the matching results and the matching degree, a first visualization model is generated; displaying the first visualization model to a user; Acquire model record information generated by the user based on the first visualization model within a first period; wherein the start time of the first period is the time when the user starts to view the first visualization model, and the end time is the time when the user first generates a standard model viewing behavior; Extract features from model record information to obtain information features; Based on the feature partitioning rules, information features are divided into feature sets; Determine the indication strategy corresponding to the feature set from the indication strategy library; the indication strategy includes: setting area search rules and target suggestion search rules; Based on the setting area search rule, searching for the setting area from the first visualization model; Based on the target suggestion search rule, the target suggestion is searched out from the adjustment suggestions; The target suggestion is continuously set in the setting area during the second time period; wherein the duration of the second time period is a preset duration value, and is after the second time period and adjacent to the first time period.

8. The vehicle body comprehensive inspection fixture matching evaluation system as claimed in claim 7, characterized in that: The feature division rules include: When there is a first target feature in the information feature that matches the trigger feature, a second target feature generated after the first target feature and meeting the feature requirement condition corresponding to the trigger feature is determined from the information feature; Combining the first target feature and the second target feature into a feature set; and / or, Retrieve the standard feature type set; Combining the third target features in the information features into a feature set, so that the feature type set formed by combining the feature types of the third target features in the feature set matches the standard feature type set; and / or, The fourth target features in the information features are combined into a feature set, so that the fourth target features in the feature set have the same corresponding representation type in the representation type library or have a representation type association relationship.

9. The vehicle body comprehensive inspection fixture matching evaluation system as claimed in claim 7, characterized in that: After the output module continuously sets the target suggestion in the setting area during the second period, the output module further includes: Interaction modules for: When the user adopts the target suggestion, a second visualization model is generated based on the second multimodal data; Based on the target suggestions, determine the adjustment area search rules and adjustment rules; Based on the adjustment area search rule, searching for the adjustment area from the second visualization model; Coordinately display the setting area and the adjustment area to the user; Parse the adjustment process sequence of the adjustment rules; According to the sequence order of the adjustment processes in the adjustment process sequence, the adjustment processes are executed on the adjustment areas in sequence; Each time the adjustment process is executed, when the adjustment process executed meets the standard process conditions and / or the user requests to modify the adjustment process executed, a process modification interface of the adjustment process executed is generated; Display the process modification interface to the user; Obtain modification instructions input by the user based on the process modification interface; Based on the modification instructions, modify the executed adjustment process; Relay executes the modified adjustment process on the adjustment area.

10. The vehicle body comprehensive inspection fixture matching evaluation system as claimed in claim 9, characterized in that: The standard process conditions include: The process weight of the executed adjustment process is greater than or equal to the first weight threshold; and / or, The process weights and sums of adjustment processes that have been executed historically are greater than or equal to the weight and threshold; and / or, The process weight of the subsequent adjustment process executed in the adjustment process sequence is greater than or equal to the second weight threshold; the second weight threshold is greater than the first weight threshold.

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