Multi-dimensional Quality Inspection Method for Fiber Optic Head Locking Joints

Abstract

The present application provides a multi-dimensional quality detection method for fiber optic head locking joints, which relates to the technical field of quality detection. The method includes: obtaining a three-dimensional model of the target joint; performing component detection to construct a three-dimensional component model; combining with the access three-dimensional model to perform simulated locking and fixing and specification matching analysis to obtain simulated locking results and specification quality information; based on the simulated locking results, determining multiple contact points, screening multiple locking deformation points and multiple locking point deformation information, and obtaining multiple locking point component information; performing locking stability analysis and locking health analysis to obtain locking stability information and locking health information; and matching and obtaining quality detection results according to the specification quality information, locking stability information and locking health information. Through the present application, the technical problem in the prior art that the accuracy of evaluating the locking performance of the joint is poor, further affecting the working stability of the joint can be solved, and the technical effect of improving the working stability performance of the joint can be achieved.

Description

Technical Field

[0001] This application relates to the technical field of quality inspection, and particularly to a multi-dimensional quality inspection method for fiber optic head locking joints. Background Art

[0002] The quality inspection of fiber optic head locking joints refers to the process of testing and analyzing fiber optic head locking joints to ensure that they meet the design specifications, performance requirements, and safety standards.

[0003] Currently, the existing methods for judging whether the geometric shape of the fiber optic head locking joint after locking meets the requirements have a low accuracy, which affects the matching degree with the optical fiber or other components, resulting in poor access performance of the joint, seriously affecting the access performance and working stability of the joint, and may bring potential safety risks and an increase in maintenance costs. Therefore, a method is needed to solve the above problems.

[0004] In summary, in the prior art, there are technical problems that since most do not analyze the locking stability and locking health through the deformation information and composition information of the fiber optic head locking joint, it may not be possible to accurately evaluate the locking performance of the joint, resulting in poor working stability of the joint and further affecting the working stability of the joint. Summary of the Invention

[0005] The purpose of this application is to provide a multi-dimensional quality inspection method for fiber optic head locking joints to solve the technical problems in the prior art that since most do not analyze the locking stability and locking health through the deformation information and composition information of the fiber optic head locking joint, it may not be possible to accurately evaluate the locking performance of the joint, resulting in poor working stability of the joint and further affecting the working stability of the joint.

[0006] In view of the above problems, this application provides a multi-dimensional quality inspection method for fiber optic head locking joints.

[0007] The present application provides a multi-dimensional quality detection method for an optical fiber head locking joint. The method includes: performing three-dimensional scanning detection on a target joint to obtain a three-dimensional model of the joint of the target joint. The target joint is an optical fiber head locking joint, including a base part and a locking part. The three-dimensional model of the joint includes a three-dimensional model of the base part and a three-dimensional model of the locking part; performing component detection on the target joint, identifying the three-dimensional model of the joint, and constructing a three-dimensional model of the component; based on the three-dimensional model of the joint, combining with the three-dimensional model of the access at the access position, performing simulated locking fixation and specification matching analysis to obtain a simulated locking result and specification quality information; based on the simulated locking result, determining a plurality of contact points in the three-dimensional model of the component, screening out a plurality of locking deformation points and a plurality of locking point deformation information, and obtaining a plurality of locking point component information based on the indexes of the plurality of locking deformation points; according to the plurality of locking deformation points, the plurality of locking point deformation information and the plurality of locking point component information, performing locking stability analysis and locking health analysis to obtain the locking stability information and locking health information of the locking part; according to the specification quality information, the locking stability information and the locking health information, matching to obtain the quality detection result of the target joint.

[0008] The technical solution provided in the present application has at least the following technical effects or advantages:

[0009] By performing three-dimensional scanning detection on the target joint to obtain a three-dimensional model of the joint of the target joint. The target joint is an optical fiber head locking joint, including a base part and a locking part. The three-dimensional model of the joint includes a three-dimensional model of the base part and a three-dimensional model of the locking part; performing component detection on the target joint, identifying the three-dimensional model of the joint, and constructing a three-dimensional model of the component; based on the three-dimensional model of the joint, combining with the three-dimensional model of the access at the access position, performing simulated locking fixation and specification matching analysis to obtain a simulated locking result and specification quality information; based on the simulated locking result, determining a plurality of contact points in the three-dimensional model of the component, screening out a plurality of locking deformation points and a plurality of locking point deformation information, and obtaining a plurality of locking point component information based on the indexes of the plurality of locking deformation points; according to the plurality of locking deformation points, the plurality of locking point deformation information and the plurality of locking point component information, performing locking stability analysis and locking health analysis to obtain the locking stability information and locking health information of the locking part; according to the specification quality information, the locking stability information and the locking health information, matching to obtain the quality detection result of the target joint. That is to say, by analyzing the locking stability and locking health through the deformation information and component information of the optical fiber head locking joint, the technical goal of improving the accuracy of evaluating the locking performance of the joint is finally achieved, and the technical effect of improving the working stability performance of the joint is achieved.

[0010] The above description is only an overview of the technical solution of the present application. In order to better understand the technical means of the present application, it can be implemented according to the content of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are hereby given. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary, and for those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to the provided drawings.

[0012] Figure 1 It is a schematic flow chart of the multi-dimensional quality detection method for the fiber optic head locking joint of the present application;

[0013] Figure 2 It is a schematic flow chart of obtaining the three-dimensional model of the component in the multi-dimensional quality detection method for the fiber optic head locking joint of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] By providing a multi-dimensional quality detection method for a fiber optic head locking joint, the present application solves the technical problems in the prior art that since most do not analyze the locking stability and locking health by the deformation information and component information of the fiber optic head locking joint, it may not be possible to accurately evaluate the locking performance of the joint, resulting in poor working stability of the joint and further affecting the working stability of the joint. The technical goal of improving the accuracy of evaluating the locking performance of the joint is achieved, and the technical effect of improving the working stability of the joint is achieved.

[0015] Next, the technical solutions in the present application will be clearly and completely described with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application. Additionally, it should be noted that for the sake of description, only the parts related to the present application are shown in the drawings rather than all of them.

[0016] Embodiment 1

[0017] Please refer to the appended Figure 1 , the present application provides a multi-dimensional quality detection method for a fiber optic head locking joint, and the method specifically includes the following steps:

[0018] Step 1: Perform three-dimensional scanning and detection on the target connector to obtain the three-dimensional model of the target connector. The target connector is a fiber optic head locking connector, which includes a base part and a locking part. The three-dimensional model of the connector includes the three-dimensional model of the base part and the three-dimensional model of the locking part.

[0019] Specifically, the fiber optic head locking connector refers to the connector inserted at the end of the fiber optic network cable of the router. The target connector refers to the fiber optic head locking connector to be subjected to multi-dimensional quality inspection. The target connector includes a base part and a locking part. The base part refers to the main body part of the connector, and the locking part refers to the part of the connector where the fixing buckle is located. Use a three-dimensional scanner to perform a full-range scan on the target connector, import the scanned data, obtain the structural characteristics of the target connector, divide the data into the base part and the locking part, and perform three-dimensional modeling on them respectively to obtain the three-dimensional model of the base part and the three-dimensional model of the locking part, and combine and construct to obtain the three-dimensional model of the connector.

[0020] Step 2: Perform component detection on the target connector, identify the three-dimensional model of the connector, and construct the three-dimensional model of the components.

[0021] Specifically, by analyzing the plastic components of the target connector, the components at multiple positions are obtained. For example, it is obtained that the plastic is uneven, contains uneven structures such as rigid molecular chains, or there are impurities and other positions. Perform three-dimensional modeling on the target connector to obtain the three-dimensional model of the connector, and identify according to multiple positions in the three-dimensional model to obtain the three-dimensional model of the components.

[0022] Step 3: Based on the three-dimensional model of the connector, combined with the three-dimensional model of the access position, perform simulated locking and fixing and specification matching analysis to obtain the simulated locking result and the specification quality information.

[0023] Specifically, the three-dimensional model of the access position refers to the three-dimensional model of the position where the network cable is inserted. For example, the three-dimensional model of the interface on the router. For example, the simulated locking and fixing refers to the insertion of the connector simulated by three-dimensional animation technology to obtain the simulated locking result. The specification matching analysis refers to the analysis of the dimensional specification matching between the target connector and the three-dimensional model of the access position. Among them, due to production errors, the produced target connector may have dimensional errors, resulting in a decrease in the matching degree. Therefore, the matching deviation is obtained as the specification quality information.

[0024] Step 4: Based on the simulated locking result, determine and obtain multiple contact points in the three-dimensional model of the components, screen out multiple locking deformation points and multiple locking point deformation information, and obtain multiple locking point component information based on the indexing of the multiple locking deformation points.

[0025] Specifically, based on the results of simulating locking and fixing, multiple contact points between the target joint and the access interface during the access process are obtained, and multiple locking deformation points of the locking part are obtained. Among them, the target joint is fixed within the access interface through buckle deformation, and then multiple locking point deformation information and multiple locking point component information are obtained.

[0026] Step Five: Based on the multiple locking deformation points, multiple locking point deformation information, and multiple locking point component information, perform locking stability analysis and locking health analysis to obtain the locking stability information and locking health information of the locking part;

[0027] Specifically, due to errors in the size specifications of the target joint, it may cause changes in the actual deformation contact points during access. Based on the position, deformation conditions, and components of the actual deformation points, analyze the stability degree after access and the health information of the locking part to obtain the locking stability information and locking health information of the locking part, which are used to analyze the joint quality. For example, the stability degree includes the probability of joint detachment. The health information of the locking part includes the probability of excessive deformation of the deformed part and fracture due to brittle components.

[0028] Step Six: Based on the specification quality information, locking stability information, and locking health information, match and obtain the quality inspection result of the target joint.

[0029] Specifically, match the quality inspection results of historical time based on the specification quality information, locking stability information, and locking health information of the target joint as the quality inspection result of the target joint.

[0030] The multi-dimensional quality inspection method for the fiber optic head locking joint can achieve the technical goal of improving the accuracy of evaluating the locking performance of the joint and achieve the technical effect of improving the working stability performance of the joint.

[0031] Further, the present application further includes the following steps:

[0032] Select multiple key positions on the target joint, where the multiple key positions include connection positions and edge positions;

[0033] Perform component detection on the multiple key positions to obtain multiple position component information;

[0034] Use the multiple position component information to identify multiple key positions on the three-dimensional model of the joint and perform interpolation identification on other multiple positions to obtain the component three-dimensional model.

[0035] Specifically, as Figure 2As shown, the connection position is the position where the target joint is connected to other components. The material composition of the connection position is crucial for the performance and reliability of the target joint. Therefore, multiple points need to be selected at the connection of the target joint as key positions. The edge position is the boundary position of the target joint. The edge position may be affected by factors such as stress concentration and wear, so it is also a key position for component detection. The key positions are obtained by combining the connection position and the edge position.

[0036] Then, component detection is performed on multiple key positions. For example, by means of component detection methods such as energy spectrum analysis and X-ray diffraction, component information of multiple positions is obtained.

[0037] Next, using the component information of multiple positions, on the three-dimensional model of the joint, identification is carried out according to the corresponding positions of the connection position and the edge position among the key positions. For example, the identification can be color, label or texture, which is used to represent the specific components of that position. Further, for other positions where component detection has not been performed, interpolation methods are used for identification. Among them, based on the known component information of the key positions, interpolation algorithms such as linear interpolation and spline interpolation are used to estimate the components of other positions and perform identification on the three-dimensional model. The identification of the key positions and the interpolation identification of other positions are integrated into the three-dimensional model to obtain the three-dimensional component model.

[0038] By obtaining the three-dimensional model of the fiber optic head locking joint, the component distribution information is further obtained, which provides strong support for the comprehensive analysis and optimization of the target joint.

[0039] Furthermore, this application also includes the following steps:

[0040] Obtain the three-dimensional access model of the access position;

[0041] According to the joint three-dimensional model combined with the access three-dimensional model, perform simulated locking and fixing movement to obtain the simulated locking result, where the simulated locking result includes multiple contact points between the three-dimensional model of the base part and the locking part and the access three-dimensional model;

[0042] According to the joint three-dimensional model and the access three-dimensional model, perform specification matching analysis to obtain the specification quality information of the target joint.

[0043] Specifically, the access three-dimensional model refers to the position where the network cable is inserted. For example, the access three-dimensional model is the three-dimensional model of the interface on the router. Obtain the three-dimensional access model of the access position.

[0044] Then, import the three-dimensional model of the connector and the three-dimensional model of the access component into the simulation software to ensure the correct spatial position relationship between the two. According to actual needs, set the relevant parameters for simulating the locking, fixing, and moving, such as the locking force, moving speed, moving distance, etc. Start the simulation and observe the interaction between the three-dimensional model of the connector and the three-dimensional model of the access component during the simulated locking, fixing, and moving process. The simulation of the three-dimensional model of the connector includes the three-dimensional model of the base part and the locking part. During the three-dimensional model simulation process, record the information of multiple contact points between the three-dimensional model of the base part and the locking part and the three-dimensional model of the access component, which is used to evaluate the locking effect and quality.

[0045] Next, compare the three-dimensional model of the connector with the three-dimensional model of the access component. For example, compare whether the dimensions, shapes, etc. match. Obtain the comparison deviation information as the specification quality information of the target connector.

[0046] By obtaining the matching situation, locking effect, and specification quality information between the fiber optic head locking connector and the access component, it provides strong support for the optimization and upgrade of the product.

[0047] Furthermore, the present application further includes the following steps:

[0048] Based on the detection data record of the fiber optic head locking connector, obtain the set of three-dimensional models of the sample connectors, and combine with the three-dimensional model of the access component to conduct a specification deviation evaluation to obtain the set of sample specification quality information;

[0049] Use the set of three-dimensional models of the sample connectors and the set of sample specification quality information to construct a specification matching analysis model, conduct a specification matching analysis on the three-dimensional model of the connector and the three-dimensional model of the access component, and obtain the specification quality information.

[0050] Specifically, according to the detection data record within the historical events of the fiber optic head locking connector, extract the three-dimensional models of multiple samples of connectors to form the set of three-dimensional models of the sample connectors. For each three-dimensional model of the sample connector, combine with the three-dimensional model of the access component to conduct a specification deviation evaluation. For example, the evaluation indicators can include dimensional deviation, shape deviation, fit clearance, etc., which are used to reflect the matching degree between the sample connector and the access component. Integrate the specification deviation evaluation results of each sample connector to obtain the set of sample specification quality information.

[0051] Then, using machine learning algorithms, deep learning algorithms, etc., training is performed with the three-dimensional model set of the sample connector and the sample specification quality information set as sample input data to construct a specification matching analysis model. The sample input data is divided into sample training data and sample verification data. Among them, the division ratio is custom-set by those skilled in the art according to the actual situation. For example, the division ratio of the sample training data to the sample verification data is 7:3. The specification matching analysis model is trained with the sample training data. If the output of the specification matching analysis model tends to be stable, the specification matching analysis model is verified with the sample verification data. When the output accuracy rate of the specification matching analysis model meets the output accuracy rate threshold of the specification matching analysis model, the training of the specification matching analysis model is completed. Among them, the output accuracy rate threshold of the specification matching analysis model is custom-set by those skilled in the art according to the actual situation. For example, the output accuracy rate threshold of the specification matching analysis model is 80%. The three-dimensional model of the connector and the three-dimensional model of the access are input into the specification matching analysis model for specification matching analysis to obtain the specification quality information of the target connector.

[0052] By constructing a specification matching analysis model, the specification quality of the fiber optic head locking connector can be evaluated more accurately, providing strong support for the quality control and improvement of the product.

[0053] Furthermore, the present application further includes the following steps:

[0054] Based on the multiple contact points between the three-dimensional model of the base part and the three-dimensional model of the locking part and the three-dimensional model of the access in the simulated locking result, the multiple contact points are obtained;

[0055] The contact points between the three-dimensional model of the locking part and the three-dimensional model of the access are selected as the multiple locking deformation points;

[0056] The deformation degree of the multiple locking deformation points in the simulated locking result is obtained as the multiple locking point deformation information;

[0057] Indexing is performed within the three-dimensional model of the composition according to the multiple locking deformation points to obtain multiple locking point composition information.

[0058] Specifically, the multiple contact points between the three-dimensional model of the base part and the three-dimensional model of the locking part and the three-dimensional model of the access in the simulated locking result are extracted to obtain multiple contact points.

[0059] Then, the contact points between the three-dimensional model of the locking part and the three-dimensional model of the access are selected from the multiple contact points as the multiple locking deformation points.

[0060] Next, for each locking deformation point, obtain the deformation conditions during the simulated locking process. For example, the degree of deformation can be quantified by comparing parameters such as the position and shape before and after deformation. Extract the degree of deformation of each locking deformation point to form multiple locking point deformation information.

[0061] Next, using the position information of the locking deformation points, index in the three-dimensional composition model to find the composition information corresponding to each locking deformation point, and obtain multiple locking point composition information.

[0062] By obtaining multiple locking deformation points and their deformation information between the fiber optic head locking joint and the access component, and also obtaining the composition information of these points, it provides data support for in-depth analysis of the locking performance, material characteristics, and potential problems of the joint.

[0063] Furthermore, this application also includes the following steps:

[0064] According to the simulated locking and fixing data records of the fiber optic head locking joint, obtain multiple sample locking deformation point sets, multiple sample locking point deformation information sets, and multiple sample locking point composition information sets;

[0065] According to the simulated locking and fixing data records of the fiber optic head locking joint, based on the joint detachment probability and the locking part fracture probability, obtain multiple sample locking stability information and multiple sample locking health information;

[0066] Using the multiple sample locking deformation point sets, multiple sample locking point deformation information sets, and multiple sample locking point composition information sets as inputs, and respectively using multiple sample locking stability information and multiple sample locking health information as outputs, construct a locking stability analysis branch and a locking health analysis branch to obtain a locking analyzer;

[0067] Based on the locking analyzer, perform locking stability analysis and locking health analysis on the multiple locking deformation points, multiple locking point deformation information, and multiple locking point composition information to obtain the locking stability information and locking health information of the locking part.

[0068] Specifically, extract the locking deformation point records of multiple samples from the simulated locking and fixing data records within the historical time to generate a sample locking deformation point set. Extract the deformation degree records of each sample locking deformation point during the simulation process to generate a sample locking point deformation information set. Extract the composition records of the sample locking points to generate a sample locking point composition information set.

[0069] Then, according to the joint detachment probability and the locking part fracture probability in the simulated locking and fixing data records of the fiber optic head locking joint within the historical time, extract the sample locking stability information and sample locking health information of each joint sample. The sample locking stability information is used to obtain the locking degree information of the sample joint. The sample locking health information is used to obtain the integrity information of the sample joint after deformation caused by locking.

[0070] Next, using a machine learning algorithm, with multiple sets of sample locking deformation points and multiple sets of sample locking point deformation information as input features, and multiple sets of sample locking stability information as the output target, train the locking stability analysis branch. If the output of the locking stability analysis branch tends to be stable, complete the training of the locking stability analysis branch. With multiple sets of sample locking deformation points, multiple sets of sample locking point deformation information, and multiple sets of sample locking point component information as input features, and multiple sets of sample locking health information as the output target, train the locking health analysis branch. If the output of the locking stability analysis branch tends to be stable, complete the training of the locking stability analysis branch. Combine the locking stability analysis branch and the locking health analysis branch to obtain a locking analyzer.

[0071] Next, based on the locking analyzer, input multiple locking deformation points, multiple locking point deformation information, and multiple locking point component information into the locking stability analysis branch and the locking health analysis branch in the locking analyzer to perform locking stability analysis and locking health analysis, and obtain the locking stability information and locking health information of the locking part of the target joint.

[0072] By quantitatively analyzing the locking stability and health of the fiber optic head locking joint, the design, manufacturing, and usage processes of the target joint can be optimized and improved according to the analysis results.

[0073] Furthermore, the present application further includes the following steps:

[0074] According to the detection sample data of the fiber optic head locking joint, obtain a set of sample specification quality information, a set of sample locking stability information, and a set of sample locking health information, and obtain a set of sample quality grades of the fiber optic head locking joint;

[0075] Based on the data categories of the specification quality information, locking stability information, and locking health information, construct the first axis, the second axis, and the third axis in the joint quality classification coordinate system;

[0076] Respectively combine and input the set of sample specification quality information, the set of sample locking stability information, and the set of sample locking health information into the joint quality classification coordinate system to obtain multiple sample points;

[0077] Use the set of sample quality grades to label the multiple sample points to obtain a joint quality classifier;

[0078] Using the joint quality classifier, classify the specification quality information, locking stability information, and locking health information to obtain a quality inspection result.

[0079] Specifically, from the detection sample data of the fiber optic head locking joint, extract the sample specification quality information set of the fiber optic head locking joint, the sample locking stability information set of the fiber optic head locking joint, and the sample locking health information set of the fiber optic head locking joint, and obtain the sample quality grade set of the fiber optic head locking joint. The sample quality grade set is used to obtain the quality level of the fiber optic head locking joint.

[0080] Then, according to the data categories and characteristics of the specification quality information, locking stability information, and locking health information, determine the representation method in the joint quality classification coordinate system. Use the specification quality information as the first axis, the locking stability information as the second axis, and the locking health information as the third axis.

[0081] Next, respectively combine and input the sample specification quality information set, the sample locking stability information set, and the sample locking health information set into the joint quality classification coordinate system. Each sample information corresponds to a point in the joint quality classification coordinate system, and multiple sample points are obtained.

[0082] Next, use the sample quality grade set to label each sample point in the joint quality classification coordinate system, obtain the quality grade corresponding to each sample point, and obtain the joint quality classifier.

[0083] In addition, obtain the specification quality information, locking stability information, and locking health information of the target joint, input them into the joint quality classifier, judge the quality grade of the joint, and output the quality inspection result.

[0084] By evaluating the quality of the fiber optic head locking joint, it provides strong support for quality control and product screening in the production process.

[0085] Furthermore, this application also includes the following steps:

[0086] Input the specification quality information, locking stability information, and locking health information into the joint quality classification coordinate system to obtain a quality point;

[0087] Obtain the N sample points closest to the quality point, where N is an integer greater than 5;

[0088] Calculate and obtain the quality grade of the target joint based on the N sample quality grades of the N sample points as the quality inspection result.

[0089] Specifically, input the specification quality information, locking stability information, and locking health information of the target joint into the joint quality classification coordinate system to obtain a quality point.

[0090] Then, select an integer N greater than 5 as the number of nearest neighbor sample points. The selection of N is adjusted according to the actual requirements and the distribution of sample points. In the joint quality classification coordinate system, obtain the N nearest neighbor sample points of the quality point. For example, this can be achieved by calculating the Euclidean distance between the quality point and each sample point, and then sorting them according to the distance or similarity, and selecting the top N points.

[0091] Next, according to the N nearest neighbor sample points, extract the corresponding sample quality grades. Based on the N sample quality grades, calculate the quality grade of the target joint as the quality inspection result. For example, take the average or mode of the N sample quality grades as the quality grade of the target joint.

[0092] Evaluate the quality grade of the target joint through the sample information and the quality classification coordinate system to provide support for practical applications.

[0093] In summary, the multi-dimensional quality inspection method for the fiber optic head locking joint provided by this application has the following technical effects:

[0094] By performing three-dimensional scanning inspection on the target joint, obtain the three-dimensional model of the target joint. The target joint is a fiber optic head locking joint, including a base part and a locking part. The three-dimensional model of the joint includes the three-dimensional model of the base part and the three-dimensional model of the locking part; perform component detection on the target joint, identify the three-dimensional model of the joint, and construct the three-dimensional model of the component; based on the three-dimensional model of the joint, combined with the three-dimensional model of the access position at the access point, perform simulated locking fixation and specification matching analysis to obtain the simulated locking result and specification quality information; based on the simulated locking result, determine multiple contact points within the three-dimensional model of the component, and screen out multiple locking deformation points and multiple locking point deformation information. Based on the indices of the multiple locking deformation points, obtain multiple locking point component information; according to the multiple locking deformation points, multiple locking point deformation information, and multiple locking point component information, perform locking stability analysis and locking health analysis to obtain the locking stability information and locking health information of the locking part; according to the specification quality information, locking stability information, and locking health information, match and obtain the quality inspection result of the target joint. That is to say, by analyzing the locking stability and locking health through the deformation information and component information of the fiber optic head locking joint, ultimately achieve the technical goal of improving the accuracy of evaluating the locking performance of the joint, and achieve the technical effect of improving the working stability performance of the joint.

[0095] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0096] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is also intended to include these changes and variations.

Claims

1. Multidimensional quality inspection method for fiber optic head locking joints, characterized in that, The method includes: Performing three-dimensional scanning detection on the target joint to obtain the three-dimensional model of the target joint. The target joint is a fiber optic head locking joint, including a base part and a locking part. The three-dimensional model of the joint includes the three-dimensional model of the base part and the three-dimensional model of the locking part; Performing component detection on the target joint, identifying the three-dimensional model of the joint, and constructing a three-dimensional component model; Based on the three-dimensional model of the joint, combined with the three-dimensional model of the access position at the access location, performing simulated locking fixation and specification matching analysis to obtain simulated locking results and specification quality information, including: Obtaining the three-dimensional model of the access position at the access location; According to the three-dimensional model of the joint combined with the three-dimensional model of the access position, performing simulated locking fixation movement to obtain simulated locking results. Among them, the simulated locking results include multiple contact points between the three-dimensional model of the base part and the locking part and the three-dimensional model of the access position; According to the three-dimensional model of the joint and the three-dimensional model of the access position, performing specification matching analysis to obtain the specification quality information of the target joint; Based on the simulated locking results, determining multiple contact points within the three-dimensional component model, screening out multiple locking deformation points and multiple locking point deformation information, and obtaining multiple locking point component information based on the indexing of the multiple locking deformation points, including: Based on the multiple contact points between the three-dimensional model of the base part and the locking part and the three-dimensional model of the access position in the simulated locking results, obtaining the multiple contact points; Selecting the contact points between the three-dimensional model of the locking part and the three-dimensional model of the access position as the multiple locking deformation points; Obtaining the deformation degree of the multiple locking deformation points in the simulated locking results as multiple locking point deformation information; Indexing according to the multiple locking deformation points within the three-dimensional component model to obtain multiple locking point component information; According to the multiple locking deformation points, multiple locking point deformation information, and multiple locking point component information, performing locking stability analysis and locking health analysis to obtain the locking stability information and locking health information of the locking part; According to the specification quality information, locking stability information, and locking health information, matching to obtain the quality detection result of the target joint.

2. The method according to claim 1, wherein Performing component detection on the target joint and identifying the three-dimensional model of the joint, including: Selecting multiple key positions on the target joint. Among them, the multiple key positions include the connection position and the edge position; Performing component detection on the multiple key positions to obtain multiple position component information; Using the multiple position component information to identify multiple key positions on the three-dimensional model of the joint and performing interpolation identification on other multiple positions to obtain the three-dimensional component model.

3. The method according to claim 1, characterized in that, According to the three-dimensional model of the joint and the three-dimensional model of the access position, performing specification matching analysis, including: Based on the detection data record of the fiber optic head locking joint, obtaining a set of three-dimensional models of sample joints, and combining with the three-dimensional model of the access position to perform specification deviation evaluation to obtain a set of sample specification quality information; Using the three-dimensional model set of the sample joints and the set of sample specification quality information, a specification matching analysis model is constructed to perform specification matching analysis on the three-dimensional model of the joint and the three-dimensional model of the access, and the specification quality information is obtained.

4. The method according to claim 1, characterized in that Based on the multiple locking deformation points, multiple locking point deformation information, and multiple locking point component information, locking stability analysis and locking health analysis are performed, including: According to the simulated locking and fixing data records of the fiber optic head locking joint, a set of multiple sample locking deformation points, a set of multiple sample locking point deformation information, and a set of multiple sample locking point component information are obtained; According to the simulated locking and fixing data records of the fiber optic head locking joint, based on the joint detachment probability and the locking part fracture probability, a set of multiple sample locking stability information and a set of multiple sample locking health information are obtained; Using the set of multiple sample locking deformation points, the set of multiple sample locking point deformation information, and the set of multiple sample locking point component information as inputs, and using the set of multiple sample locking stability information and the set of multiple sample locking health information as outputs respectively, a locking stability analysis branch and a locking health analysis branch are constructed to obtain a locking analyzer; Based on the locking analyzer, locking stability analysis and locking health analysis are performed on the multiple locking deformation points, multiple locking point deformation information, and multiple locking point component information to obtain the locking stability information and locking health information of the locking part.

5. The method according to claim 1, characterized in that, According to the specification quality information, locking stability information, and locking health information, the quality detection result of the target joint is obtained by matching, including: According to the detection sample data of the fiber optic head locking joint, a set of sample specification quality information, a set of sample locking stability information, and a set of sample locking health information are obtained, and a set of sample quality grades of the fiber optic head locking joint is obtained; Based on the data categories of the specification quality information, locking stability information, and locking health information, the first axis, the second axis, and the third axis in the joint quality classification coordinate system are constructed; The set of sample specification quality information, the set of sample locking stability information, and the set of sample locking health information are respectively combined and input into the joint quality classification coordinate system to obtain multiple sample points; Using the set of sample quality grades, the multiple sample points are marked to obtain a joint quality classifier; Using the joint quality classifier, the specification quality information, locking stability information, and locking health information are classified to obtain the quality detection result.

6. The method according to claim 5, wherein Using the joint quality classifier, the specification quality information, locking stability information, and locking health information are classified to obtain the quality detection result, including: The specification quality information, locking stability information, and locking health information are input into the joint quality classification coordinate system to obtain a quality point; Obtain the N sample points closest to the quality point, where N is an integer greater than 5; According to the N sample quality grades of the N sample points, the quality grade of the target joint is calculated and used as the quality detection result.

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