Inspection tool and inspection method

Abstract

The invention discloses a novel inspection fixture and an inspection method, comprising an inspection platform, wherein the inspection platform is provided with an inspection station, the inspection station is provided with an installation notch, the installation notch is provided with an extension mechanism, the extension mechanism comprises a lifting assembly, the driving end of the lifting assembly is provided with a rotating driving member, and the driving end of the rotating driving member is provided with an extension rod; a hot pressing inspection mechanism is provided above the inspection station, the hot pressing inspection mechanism comprises a driving assembly, and a hot pressing assembly arranged at the driving end of the driving assembly, the hot pressing assembly comprises a hot pressing plug, the hot pressing plug is provided with a heating assembly, and one end of the heating assembly is provided with a pressure sensing sheet; through the cooperation of the extension mechanism and the hot pressing inspection mechanism, the actual hot pressing working conditions of components to be tested and the detection of different stress conditions are realized, thereby simulating more complex use conditions, performing more comprehensive measurements and tests, so that the components to be tested can be tested more comprehensively, thereby obtaining more accurate test results.

Description

Technical Field

[0001] The present invention relates to the field of detection technology, and in particular to a detection fixture and a detection method. Background Art

[0002] As electronic devices develop towards high performance, miniaturization and multifunctionality, high-density electrical connectors play a vital role in modern electronic systems. High-density electrical connectors usually integrate multiple metal contacts to achieve efficient electrical signal transmission and are widely used in computers, communication equipment, consumer electronics, automotive electronics, aerospace and other fields. These connectors are not only required to have excellent electrical performance, but also to maintain a stable connection state in complex working environments to ensure the reliable operation of the equipment. With the advancement of technology, the market's performance requirements for high-density electrical connectors are constantly increasing, prompting the development of related testing technologies to ensure that the connectors can meet strict quality standards before leaving the factory to avoid system failures or performance degradation caused by poor connections.

[0003] At present, the detection technology for high-density electrical connectors mainly relies on the combination of traditional mechanical crimping and electrical testing. These methods usually include using a fixed pressure application device to press the metal contacts of the connector together through mechanical pressure, and measuring the contact resistance or signal transmission quality through electrical testing instruments. For example, a common detection device uses a fixed pressure plate and a force sensor to evaluate the contact performance of the connector by applying a predetermined pressure. However, this type of existing technology has many shortcomings. First, the fixed pressure application method cannot simulate the multi-directional forces that the connector may be subjected to in actual use, resulting in deviations between the detection results and the actual working environment, and cannot fully reflect the actual performance of high-density electrical connectors under complex working conditions, thereby affecting the quality control of the product.

[0004] In view of this, it is necessary to improve the inspection equipment of high-density electrical connectors in the prior art to solve the technical problem that the inspection is not comprehensive and accurate enough. Summary of the invention

[0005] The purpose of the present invention is to provide an inspection jig and an inspection method to solve the above technical problems.

[0006] To achieve this object, the present invention adopts the following technical solutions:

[0007] An inspection jig comprises a detection platform, the detection platform is provided with a detection station, the detection station is provided with a mounting notch penetrating the detection platform, the mounting notch is provided with a jacking mechanism, the jacking mechanism comprises a lifting assembly, a rotating driving member is provided at a driving end of the lifting assembly, a jacking rod is provided at a driving end of the rotating driving member, and a circular curved surface is provided at an upper end of the jacking rod;

[0008] A hot-pressing detection mechanism is arranged above the detection station, and the hot-pressing detection mechanism includes a driving component and a hot-pressing component arranged at a driving end of the driving component, and the driving component is used to drive the hot-pressing component to act on the component to be tested along a preset trajectory;

[0009] The hot pressing assembly includes a hot pressing plug for conducting with the component to be tested, the hot pressing plug is provided with a heating assembly, one end of the heating assembly is provided with a pressure sensing sheet, and the pressure sensing sheet is used to detect the feedback pressure of the hot pressing plug.

[0010] Optionally, clamping mechanisms are respectively provided on both sides of the detection station, the clamping mechanisms include a clamping cylinder provided on the detection platform, a piston rod of the clamping cylinder is provided with a clamping block, and two groups of clamping blocks of the clamping mechanisms are respectively arranged opposite to each other;

[0011] The clamping block comprises a main body, the main body is provided with a clamping wall, a pressing portion is extended along the clamping wall, and a flexible material portion is provided on the lower end surface of the pressing portion.

[0012] Optionally, a terminal detection assembly is provided on one side of the detection station, and the terminal detection assembly includes a screw rod arranged along a preset direction, an adjusting pressure block is connected to the screw rod via a connecting nut, and a clamping groove is provided at one end of the adjusting pressure block facing the detection station, and a force measuring element is provided in the clamping groove.

[0013] Optionally, the driving assembly includes a first linear module arranged along the X-axis direction, a driving end of the first linear module is provided with a second linear module, and the second linear module is arranged along the Y-axis direction;

[0014] A bracket is provided at the driving end of the second linear module, a lifting cylinder is provided on the bracket along the vertical direction, and the driving end of the lifting cylinder is connected to the hot pressing assembly.

[0015] Optionally, the hot pressing assembly includes a connecting block, which is threadedly connected to the piston rod of the lifting cylinder; a plurality of guide columns are provided at the lower end of the connecting block, one end of the guide column is slidably connected to a mounting block, wherein a force measuring spring is sleeved on the guide column, one end of the force measuring spring is arranged to contact the pressure sensing plate for transmitting pressure to the pressure sensing plate.

[0016] The present invention also provides an inspection method, which is applied to the inspection fixture as described above, and the inspection method comprises:

[0017] Place the components to be tested on the testing station and connect the test circuit, start the extension mechanism and the hot pressing detection mechanism, drive the extension rod to move upward through the lifting assembly to lift the components to be tested, measure the initial pressure through the pressure sensor, and record the feedback signal of the test circuit to obtain the initial state data;

[0018] The push rod is driven to rotate at an angle to change the force angle of the component to be tested. During the rotation process, the pressure sensor is used to monitor the pressure change in real time, and the feedback signal of the test circuit is continuously recorded to obtain dynamic force data.

[0019] Fix the components to be tested at the testing station, start the hot pressing assembly, heat the hot pressing plug to a preset temperature, and drive the hot pressing plug to act on the upper surface of the components to be tested along a preset trajectory through the driving assembly. During the action, the fluctuation of the feedback signal is monitored and recorded through the test circuit to obtain the hot pressing monitoring data under the action of the heating trajectory;

[0020] Pre-process the collected initial data, dynamic stress data and thermal pressure monitoring data, perform multi-dimensional fusion on the data collected at different stages to form a comprehensive feature vector, and use the feature extraction algorithm of principal component analysis to extract the key characteristic parameters of the components under different stress and heating conditions;

[0021] Pre-constructing a support vector machine model, and training the support vector machine model through feature vectors and key feature parameters to obtain a performance test model;

[0022] During the inspection process, the characteristic parameters collected in real time are input into the trained performance inspection model, the input data is analyzed, and the judgment results of the performance of the components to be tested are output.

[0023] Optionally, the collected initial data, dynamic force data and thermal pressure monitoring data are preprocessed, and the data collected at different stages are multi-dimensionally integrated to form a comprehensive feature vector, specifically including:

[0024] Perform time synchronization processing on the collected initial data, dynamic force data and thermal pressure monitoring data, and perform baseline calibration on each data set;

[0025] A low-pass filter is used to filter the initial data, dynamic force data, and thermal pressure monitoring data to remove high-frequency interference signals, and then a median filter algorithm is used to smooth the data to further reduce the impact of instantaneous noise and outliers.

[0026] Identify and remove abnormal points and outliers in the data set, and use interpolation methods to fill in missing data.

[0027] Optionally, the identifying and removing of abnormal points and outliers in the data set and filling missing data with an interpolation method may further include:

[0028] The initial data, dynamic force data and thermal pressure monitoring data are standardized respectively so that the data of different dimensions have the same dimensions;

[0029] A normalization algorithm is used to scale each standardized data set to a range between 0 and 1 to eliminate scale differences between different data sources;

[0030] The pre-processed initial data, dynamic force data and thermal pressure monitoring data are multi-dimensionally fused according to time series to form a comprehensive multi-dimensional data matrix;

[0031] The time domain and frequency domain features are extracted from the fused multidimensional data matrix, and the time-frequency analysis method is introduced to extract the dynamic characteristics of the components under different stress and heating conditions to construct a preliminary feature vector.

[0032] Optionally, the feature extraction algorithm using principal component analysis is used to extract key characteristic parameters of the components to be tested under different stress and heating conditions, specifically including:

[0033] Perform principal component analysis on the constructed feature vector, calculate the variance contribution rate of each principal component, and select the principal component whose cumulative contribution rate reaches the preset threshold;

[0034] The selected principal components are used as key feature parameters to form a low-dimensional feature vector;

[0035] The correlation analysis method is used to further screen the extracted main components, retain the characteristic parameters most relevant to the performance of the components to be tested, and optimize the feature reconstruction of the retained key characteristic parameters;

[0036] The extracted feature vectors are verified through an independent verification set, and the verified comprehensive feature vectors and key feature parameters are stored in the database.

[0037] Optionally, the pre-constructing a support vector machine model and training the support vector machine model through feature vectors and key feature parameters to obtain a performance test model specifically includes:

[0038] Set the initial hyperparameters of the support vector machine model, including the penalty factor C and kernel function parameters, and perform preliminary parameter selection through grid search or random search method to find the best hyperparameter combination;

[0039] Dividing the preprocessed feature vector and key feature parameter data sets according to a preset ratio;

[0040] The training set data is validated using k-fold cross validation. The training set is further divided into k subsets, and k-1 subsets are used for training in turn, and the remaining subset is used for validation to evaluate the performance of the model on different data subsets.

[0041] Use the training set data to train the support vector machine model and iteratively optimize the model hyperparameters; optimize the penalty factor C and kernel function parameter σ of the support vector machine model through hyperparameter adjustment guided by cross-validation results;

[0042] Use the test set data to evaluate the trained support vector machine model and calculate the performance indicators of the model's accuracy, recall, and F1 score;

[0043] The performance of support vector machine models under different kernel functions and parameter settings is compared, and the optimal support vector machine model is selected using performance indicators as the final performance test model.

[0044] Compared with the prior art, the present invention has the following beneficial effects: during the test, the components to be tested are first placed on the test station, and the connecting wires of the components to be tested are connected to the test circuit of the test platform. The test is divided into two parts. In the first part of the test, the extension mechanism is operated, and the lifting rod is driven to move upward by the lifting assembly to lift the components to be tested. At the same time, the hot pressing detection mechanism is pressed down to make the hot pressing plug contact with the upper surface of the components to be tested, so as to achieve the circuit conduction of the components to be tested. The initial pressure is measured by the pressure sensor sheet, and the feedback signal corresponding to the test circuit is recorded. Then, the rotating driving member drives the extension rod to rotate the angle, thereby changing the force angle of the components to be tested. During this period, the pressure change value is monitored in real time by the pressure sensor sheet, and recorded. The second part of the test is to fix the component to be tested at the detection station, operate the hot pressing assembly to heat the hot pressing plug to a preset temperature, and then operate the driving assembly to drive the hot pressing plug to act on the upper surface of the component to be tested along a preset trajectory. During this period, the fluctuation of the feedback signal is monitored by the test circuit to complete the detection; this fixture realizes the actual hot pressing working conditions of the component to be tested and the detection of different stress conditions through the cooperation of the top extension mechanism and the hot pressing detection mechanism, thereby simulating more complex operating conditions and conducting more comprehensive measurements and tests, so that the components to be tested can be subjected to more comprehensive and representative performance tests, thereby obtaining more accurate test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0046] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0047] Figure 1 This is a schematic diagram of the structure of the inspection fixture of the first embodiment;

[0048] Figure 2 This is a schematic diagram of the detection main body structure of the inspection fixture of the first embodiment;

[0049] Figure 3 This is a schematic diagram of the structure of the testing platform of the testing fixture of the first embodiment;

[0050] Figure 4 This is a schematic structural diagram of the clamping mechanism of the inspection fixture of the first embodiment;

[0051] Figure 5 This is a schematic diagram of the structure of the terminal detection assembly of the inspection fixture of the first embodiment;

[0052] Figure 6 This is a schematic structural diagram of the clamping mechanism of the inspection fixture of the first embodiment;

[0053] Figure 7 Schematic diagram of the structure of the hot pressure detection mechanism of the inspection fixture of the first embodiment.

[0054] Illustrations: detection platform 100, detection station 101, installation notch 102, extension mechanism 200, lifting assembly 210, rotary drive member 220, extension rod 230, circular surface 231, hot pressing detection mechanism 300, drive assembly 310, hot pressing assembly 320, hot pressing plug 321, heating assembly 322, pressure sensor 323, clamping mechanism 400, clamping cylinder 410, clamping block 420, main body 421, clamping wall 422, pressing part 423, terminal detection assembly 500, screw rod 520, adjusting pressure block 510, clamping groove 511, connecting block 324, guide column 325, component to be tested 600. DETAILED DESCRIPTION

[0055] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] In the description of the present invention, it should be understood that the terms "upper", "lower", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. It should be noted that when a component is considered to be "connected" to another component, it may be directly connected to the other component or there may be a centrally arranged component at the same time.

[0057] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0058] Embodiment 1:

[0059] Combination Figures 1 to 7 As shown, an embodiment of the present invention provides an inspection fixture, including an inspection platform 100, wherein the inspection platform 100 is provided with an inspection station 101, wherein the inspection station 101 is provided with an installation notch 102 penetrating the inspection platform 100, wherein the installation notch 102 is provided with an extension mechanism 200, wherein the extension mechanism 200 includes a lifting assembly 210, wherein a rotating driving member 220 is provided at a driving end thereof, wherein an extension rod 230 is provided at a driving end thereof, and a circular curved surface 231 is provided at an upper end portion of the extension rod 230; the setting of the circular curved surface 231 can ensure smooth force on the component 600 to be tested in all directions during the process in which the rotating driving member 220 drives the extension rod 230 to rotate at an angle, i.e., it is adapted to the force angle adjustment.

[0060] A hot press detection mechanism 300 is arranged above the detection station 101. The hot press detection mechanism 300 includes a driving component 310 and a hot press component 320 arranged at the driving end of the driving component 310. The driving component 310 is used to drive the hot press component 320 to act on the component to be tested 600 along a preset trajectory; the hot press component 320 includes a hot press plug 321 for conducting with the component to be tested 600, the hot press plug 321 is provided with a heating component 322, and a pressure sensor sheet 323 is provided at one end of the heating component 322. The pressure sensor sheet 323 is used to detect the feedback pressure of the hot press plug 321.

[0061] The working principle of the present invention is as follows: during the inspection, the component 600 to be tested is first placed on the inspection station 101, and the connecting wire of the component 600 to be tested is connected to the test circuit of the inspection platform 100. The test is divided into two parts. In the first part of the test, the extension mechanism 200 is operated, and the extension rod 230 is driven to move upward through the lifting assembly 210 to lift the component 600 to be tested. At the same time, the hot pressing detection mechanism 300 is pressed down to make the hot pressing plug 321 contact with the upper surface of the component 600 to be tested, so as to achieve the circuit conduction of the component 600 to be tested. The initial pressure is measured by the pressure sensor sheet 323, and the feedback signal corresponding to the test circuit is recorded. Then, the rotating driving member 220 drives the extension rod 230 to rotate at an angle, thereby changing the force angle of the component 600 to be tested. During this period, the pressure change value is monitored in real time through the pressure sensor sheet 323. , and record the fluctuation of the feedback signal of the test circuit; the second part of the test, by fixing the component 600 to be tested on the detection station 101, the hot pressing assembly 320 operates to heat the hot pressing plug 321 to a preset temperature, and then the driving assembly 310 operates to drive the hot pressing plug 321 to act on the upper surface of the component 600 to be tested along a preset trajectory. During this period, the fluctuation of the feedback signal is monitored by the test circuit to complete the detection; this fixture realizes the actual hot pressing working conditions of the component 600 to be tested, as well as the detection of different stress conditions through the cooperation of the top extension mechanism 200 and the hot pressing detection mechanism 300, thereby simulating more complex use conditions, and performing more comprehensive measurements and tests, so that the component 600 to be tested can be subjected to more comprehensive and representative performance tests, thereby obtaining more accurate test results.

[0062] In this embodiment, clamping mechanisms 400 are respectively provided on both sides of the detection station 101, and the clamping mechanism 400 includes a clamping cylinder 410 arranged on the detection platform 100, and the piston rod of the clamping cylinder 410 is provided with a clamping block 420, and the clamping blocks 420 of the two groups of clamping mechanisms 400 are respectively arranged opposite to each other; the clamping block 420 includes a main body 421, and the main body 421 is provided with a clamping wall 422, and a pressing portion 423 is extended along the clamping wall 422, and the lower end surface of the pressing portion 423 is provided with a flexible material portion.

[0063] During operation, the two clamping blocks 420 are driven to approach each other by the clamping cylinder 410, thereby clamping the component 600 to be tested located in the middle to meet the needs of the hot pressure test, or the two clamping blocks 420 are not completely clamped, but a certain space is reserved, so that during the lifting process, the jacking machine can provide flexible space on the one hand, and on the other hand, it can prevent the component 600 to be tested from falling through the restriction of the clamping wall 422.

[0064] In this embodiment, a terminal detection assembly 500 is provided on one side of the detection station 101, and the terminal detection assembly 500 includes a screw rod 520 arranged along a preset direction, and an adjusting pressure block 510 is connected to the screw rod through a connecting nut. A clamping groove 511 is provided at one end of the adjusting pressure block 510 facing the detection station 101, and a force measuring element is provided in the clamping groove 511.

[0065] It should be noted that a terminal detection component 500 is also provided in the present scheme, the purpose of which is to detect the terminals of the component 600 to be tested. The specific process is: the terminal of the component 600 to be tested is inserted into the position of the card slot 511, and maintains abutment with the force measuring element. During the operation of the driving component 310 to drive the hot pressing plug 321 to act on the component 600 to be tested along a preset trajectory, the force condition of the force measuring element is used to detect the stability of the terminal of the component 600 to be tested, thereby achieving comprehensive detection of the component 600 to be tested.

[0066] In this embodiment, the driving assembly 310 includes a first linear module arranged along the X-axis direction, and a second linear module is arranged at the driving end of the first linear module, and the second linear module is arranged along the Y-axis direction; a bracket is arranged at the driving end of the second linear module, and a lifting cylinder is arranged on the bracket along the vertical direction, and the driving end of the lifting cylinder is connected to the hot pressing assembly 320. Thus, the three degrees of freedom of the X-axis, Y-axis and Z-axis are realized to drive the hot pressing assembly 320 to move, so as to realize the driving of the preset trajectory.

[0067] In this embodiment, the hot pressing assembly 320 includes a connecting block 324, which is threadedly connected to the piston rod of the lifting cylinder; a plurality of guide columns 325 are provided at the lower end of the connecting block 324, and one end of the guide column 325 is slidably connected to a mounting block, wherein a force measuring spring is sleeved on the guide column 325, and one end of the force measuring spring is arranged to contact the pressure sensing plate 323 for transmitting pressure to the pressure sensing plate 323.

[0068] In this solution, the actual heat-pressure working condition of the component 600 to be tested is detected by the elastic force fed back by the force measuring spring, and the elastic force feedback is used for indirect detection to avoid pressure loss of the pressure sensing sheet 323.

[0069] Embodiment 2:

[0070] The present invention also provides an inspection method, which is applied to the inspection fixture of the first embodiment, and the inspection method includes:

[0071] S1, place the component to be tested 600 on the testing station 101 and connect the test circuit, start the extension mechanism 200 and the hot pressing detection mechanism 300, drive the extension rod 230 to move upward through the lifting assembly 210 to lift the component to be tested 600, measure the initial pressure through the pressure sensor sheet 323, and record the feedback signal of the test circuit to obtain the initial state data.

[0072] S2, driving the extension rod 230 to rotate the angle, changing the force angle of the component 600 to be tested. During the rotation process, the pressure sensor sheet 323 is used to monitor the pressure change in real time, and the feedback signal of the test circuit is continuously recorded to obtain dynamic force data.

[0073] S3, fix the component to be tested 600 on the inspection station 101, start the hot pressing assembly 320, heat the hot pressing plug 321 to a preset temperature, and drive the hot pressing plug 321 along a preset trajectory to act on the upper surface of the component to be tested 600 through the driving assembly 310. During the action, the fluctuation of the feedback signal is monitored and recorded through the test circuit to obtain the hot pressing monitoring data under the action of the heating trajectory.

[0074] S4, pre-processing the collected initial data, dynamic stress data and thermal pressure monitoring data, multi-dimensionally integrating the data collected at different stages to form a comprehensive feature vector, and using the feature extraction algorithm of principal component analysis to extract key feature parameters of the component 600 under different stress and heating conditions.

[0075] S5, pre-build a support vector machine model, and train the support vector machine model through feature vectors and key feature parameters to obtain a performance test model.

[0076] S6, during the inspection process, the characteristic parameters collected in real time are input into the trained performance inspection model, the input data is analyzed, and the judgment result of the performance of the component 600 to be tested is output.

[0077] The beneficial effects of this method are as follows: first, the synchronous operation of the extension mechanism 200 and the hot pressing detection mechanism 300 ensures the initial state acquisition; second, the design of the angle rotation and the hot pressing trajectory simulates the complex working conditions in actual use, and improves the representativeness and comprehensiveness of the test data; the data preprocessing and multi-dimensional data fusion steps effectively integrate the detection data of different stages, and use principal component analysis to extract key feature parameters, thereby improving the depth and accuracy of data analysis; through the training and application of the support vector machine model, the inspection method has efficient automatic judgment capabilities, which significantly improves the intelligence level of detection; this inspection method not only improves the accuracy and efficiency of detection, but also realizes intelligent and automated comprehensive performance evaluation through data processing, significantly enhances the practicality and adaptability of the inspection fixture, and realizes comprehensive detection of the components 600 to be tested under various stress and heating conditions.

[0078] In this embodiment, it is specifically described that step S4 specifically includes:

[0079] S401, performing time synchronization processing on the collected initial data, dynamic force data and thermal pressure monitoring data, and performing baseline calibration on each data set;

[0080] Ensure that the timestamps of each data set are consistent and eliminate the time offset caused by the difference in device response time. Perform baseline calibration on each data set to eliminate the influence of external factors such as ambient temperature and humidity on the measurement results of the pressure sensor 323 and ensure the accuracy of the data.

[0081] S402, apply a low-pass filter to perform noise filtering on the initial data, dynamic force data and thermal pressure monitoring data to remove high-frequency interference signals, and then use a median filter algorithm to smooth the data to further reduce the impact of instantaneous noise and outliers; improve the stability and reliability of the data.

[0082] S403, identifying and removing abnormal points and outliers in the data set, and using interpolation methods to fill in missing data;

[0083] First, identify and remove abnormal points and outliers in the data set. Statistical analysis methods (such as Z-scores and box plots) are used to detect and remove data points that deviate from the normal range to ensure the overall consistency of the data set. Subsequently, interpolation methods (such as linear interpolation and spline interpolation) are used to fill in missing data and restore the continuity and integrity of the data. This step not only improves the integrity of the data set, but also reduces analytical errors caused by missing or abnormal data, ensuring the accuracy of subsequent processing steps.

[0084] S404, standardizing the initial data, dynamic force data and thermal pressure monitoring data respectively so that data of different dimensions have the same dimension.

[0085] The initial data, dynamic force data and hot pressure monitoring data are standardized respectively. The purpose of standardization is to convert data of different dimensions into the same dimension and eliminate the data deviation caused by the dimension difference. The specific operation includes subtracting the mean of each data set and dividing it by the standard deviation, so that the mean of the data set is zero and the standard deviation is one. This processing step ensures that different data sources have the same scale and distribution characteristics in the subsequent multidimensional fusion and feature extraction process, and improves the uniformity and comparability of data processing.

[0086] S405, using a normalization algorithm to scale each standardized data set to a range between 0 and 1, eliminating scale differences between different data sources.

[0087] The normalization algorithm is used to scale the standardized data sets to a range between 0 and 1. Normalization eliminates the scale differences between different data sources through linear transformation, so that all data fluctuate within the same numerical range, which helps to improve the effect of multidimensional data fusion. Common normalization methods include minimum-maximum normalization, which linearly maps data to a predetermined interval.

[0088] S406, performing multi-dimensional fusion of the pre-processed initial data, dynamic force data and thermal pressure monitoring data according to time series to form a comprehensive multi-dimensional data matrix;

[0089] The pre-processed initial data, dynamic force data and thermal pressure monitoring data are multi-dimensionally fused in time series to form a comprehensive multi-dimensional data matrix. The specific operation includes arranging each data set in chronological order and integrating the information of multiple data sources with specific fusion algorithms (such as weighted average and principal component fusion). This process not only retains the time series characteristics of each data set, but also builds a more comprehensive and rich data matrix by integrating the advantages of different data sources.

[0090] S407, extracting time domain and frequency domain features, such as mean, variance, and spectrum energy, from the fused multidimensional data matrix, and introducing a time-frequency analysis method to extract dynamic features of the component under test 600 under different stress and heating conditions, and constructing a preliminary feature vector.

[0091] Time domain and frequency domain features are extracted from the fused multidimensional data matrix. Time domain features include statistical quantities such as mean, variance, kurtosis, and skewness, while frequency domain features extract the spectrum information of the signal through Fourier transform or wavelet transform. In addition, time-frequency analysis methods (such as short-time Fourier transform and wavelet packet transform) are introduced to further extract the dynamic characteristics of the component 600 under different stress and heating conditions. By integrating the characteristics of the time domain and frequency domain, a preliminary feature vector is constructed to enhance the expression ability and information content of the feature vector.

[0092] S408, performing principal component analysis on the constructed feature vector, calculating the variance contribution rate of each principal component, and selecting the principal component whose cumulative contribution rate reaches a preset threshold;

[0093] Perform principal component analysis (PCA) on the constructed feature vector and calculate the variance contribution rate of each principal component. PCA is used to reduce the dimension of high-dimensional feature vectors, select principal components whose cumulative contribution rate reaches a preset threshold (such as 95%), and reduce the feature dimension. The specific operation includes calculating the covariance matrix and eigenvalue decomposition of the feature vector, and selecting the principal components based on the variance contribution rate.

[0094] S409, using the selected principal components as key feature parameters to form a low-dimensional feature vector; retaining the main information of the data, while removing redundant and highly correlated features to improve the training efficiency and accuracy of subsequent models.

[0095] S410, using a correlation analysis method, further screening the extracted principal components, retaining the characteristic parameters most relevant to the performance of the component 600 to be tested, and optimizing the feature reconstruction of the retained key characteristic parameters; improving the expression ability and discrimination performance of the feature vector.

[0096] S411, verify the extracted feature vector through an independent verification set, and store the verified comprehensive feature vector and key feature parameters in the data warehouse.

[0097] The extracted feature vectors are verified through an independent validation set to evaluate their effectiveness and stability in the performance test model. The specific operation includes inputting the feature vector into the pre-divided validation set, calculating the performance indicators of the model on the validation set (such as accuracy, recall, F1 score), and ensuring that the feature vector has good generalization ability. After the verification, the comprehensive feature vector and key feature parameters are stored in the data warehouse for subsequent machine learning model training and performance determination.

[0098] In this embodiment, it is specifically described that step S5 specifically includes:

[0099] S501, setting initial hyperparameters of the support vector machine model, including penalty factor C and kernel function parameters, and performing preliminary parameter selection by grid search or random search method to find the best hyperparameter combination;

[0100] Determine the kernel function type of the support vector machine (SVM) model, including but not limited to a linear kernel, a Gaussian radial basis kernel (RBF kernel), a polynomial kernel, etc., and select the most suitable kernel function according to the data distribution characteristics of the component 600 to be tested to optimize the fitting ability and generalization performance of the model.

[0101] S502, divide the preprocessed feature vector and key feature parameter data set according to a preset ratio (for example, 80% as a training set and 20% as a test set); ensure that the data distribution of the training set and the test set is consistent to avoid data leakage and overfitting risks.

[0102] S503, use k-fold cross-validation to validate the training set data, by further dividing the training set into k subsets, using k-1 subsets for training in turn, and the remaining subset for validation, to evaluate the performance of the model on different data subsets; improve the stability and reliability of the model.

[0103] S504, use the training set data to train the support vector machine model and iteratively optimize the model hyperparameters to minimize the classification error of the model on the training data and improve the model's ability to recognize features. Through the hyperparameter adjustment guided by the cross-validation results, the penalty factor C and kernel function parameter σ of the support vector machine model are optimized to improve the prediction accuracy and robustness of the model and prevent overfitting or underfitting.

[0104] S505, using the test set data to evaluate the trained support vector machine model, and calculating the performance indicators of the model such as accuracy, recall and F1 score.

[0105] S506, comparing the performance of the support vector machine models under different kernel functions and parameter settings, and selecting the optimal support vector machine model as the final performance test model using a performance indicator (such as the highest F1 score).

[0106] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An inspection jig, characterized in that: The invention comprises a detection platform, wherein the detection platform is provided with a detection station, wherein the detection station is provided with a mounting notch penetrating the detection platform, wherein the mounting notch is provided with a jacking mechanism, wherein the jacking mechanism comprises a lifting assembly, wherein a rotating driving member is provided at a driving end of the lifting assembly, wherein a jacking rod is provided at a driving end of the rotating driving member, wherein a circular curved surface is provided at an upper end of the jacking rod; wherein the jacking mechanism is provided below the detection station, and the jacking rod is provided from bottom to top toward the detection station; A hot-pressing detection mechanism is arranged above the detection station, and the hot-pressing detection mechanism includes a driving component and a hot-pressing component arranged at a driving end of the driving component, and the driving component is used to drive the hot-pressing component to act on the component to be tested along a preset trajectory; The hot pressing assembly includes a hot pressing plug for conducting with the component to be tested, the hot pressing plug is provided with a heating assembly, one end of the heating assembly is provided with a pressure sensing sheet, and the pressure sensing sheet is used to detect the feedback pressure of the hot pressing plug.

2. The inspection jig according to claim 1, characterized in that: The two sides of the detection station are respectively provided with clamping mechanisms, the clamping mechanisms include a clamping cylinder arranged on the detection platform, the piston rod of the clamping cylinder is provided with a clamping block, and the clamping blocks of the two groups of the clamping mechanisms are respectively arranged opposite to each other; The clamping block comprises a main body, the main body is provided with a clamping wall, a pressing portion is extended along the clamping wall, and a flexible material portion is provided on the lower end surface of the pressing portion.

3. The inspection jig according to claim 2, characterized in that: A terminal detection assembly for detecting the terminals of the components to be tested is arranged on one side of the detection station, and the terminal detection assembly includes a screw rod arranged along a preset direction, and an adjusting pressure block is connected to the screw rod via a connecting nut, and a clamping groove is arranged at one end of the adjusting pressure block facing the detection station, and a force measuring element is arranged in the clamping groove.

4. The inspection jig according to claim 1, characterized in that: The driving assembly includes a first linear module arranged along the X-axis direction, a second linear module is arranged at the driving end of the first linear module, and the second linear module is arranged along the Y-axis direction; A bracket is provided at the driving end of the second linear module, a lifting cylinder is provided on the bracket along the vertical direction, and the driving end of the lifting cylinder is connected to the hot pressing assembly.

5. The inspection jig according to claim 4, characterized in that: The hot pressing assembly includes a connecting block, which is threadedly connected to the piston rod of the lifting cylinder; a plurality of guide columns are arranged at the lower end of the connecting block, one end of each guide column is slidably connected to a mounting block, wherein a force measuring spring is sleeved on the guide column, one end of each force measuring spring is arranged to contact the pressure sensing sheet for transmitting pressure to the pressure sensing sheet.

6. A testing method, characterized in that: Applied to the inspection jig according to any one of claims 1 to 5, the two sides of the inspection station of the inspection jig are respectively provided with clamping mechanisms for fixing the components to be tested; the inspection method comprises: Place the components to be tested on the testing station and connect the test circuit, start the extension mechanism and the hot pressing detection mechanism, drive the extension rod to move upward through the lifting assembly to lift the components to be tested, measure the initial pressure through the pressure sensor, and record the feedback signal of the test circuit to obtain the initial state data; The push rod is driven to rotate at an angle to change the force angle of the component to be tested. During the rotation process, the pressure sensor is used to monitor the pressure change in real time, and the feedback signal of the test circuit is continuously recorded to obtain dynamic force data. Fix the components to be tested at the testing station, start the hot pressing assembly, heat the hot pressing plug to a preset temperature, and drive the hot pressing plug to act on the upper surface of the components to be tested along a preset trajectory through the driving assembly. During the action, the fluctuation of the feedback signal is monitored and recorded through the test circuit to obtain the hot pressing monitoring data under the action of the heating trajectory; Pre-process the collected initial data, dynamic stress data and thermal pressure monitoring data, perform multi-dimensional fusion on the data collected at different stages to form a comprehensive feature vector, and use the feature extraction algorithm of principal component analysis to extract the key characteristic parameters of the components under different stress and heating conditions; Pre-constructing a support vector machine model, and training the support vector machine model through feature vectors and key feature parameters to obtain a performance test model; During the inspection process, the characteristic parameters collected in real time are input into the trained performance inspection model, the input data is analyzed, and the judgment results of the performance of the components to be tested are output.

7. The inspection method according to claim 6, characterized in that: The preprocessing of the collected initial data, dynamic force data and thermal pressure monitoring data, and multi-dimensional fusion of the data collected at different stages to form a comprehensive feature vector specifically includes: The collected initial data, dynamic force data and thermal pressure monitoring data are time-synchronized, and each data set is baseline-calibrated; the time synchronization process is to make the timestamps of each data set consistent and eliminate the time offset caused by the difference in equipment response time; A low-pass filter is used to filter the initial data, dynamic force data, and thermal pressure monitoring data to remove high-frequency interference signals, and then a median filter algorithm is used to smooth the data to further reduce the impact of instantaneous noise and outliers. Identify and remove abnormal points and outliers in the data set, and use interpolation methods to fill in missing data.

8. The inspection method according to claim 7, characterized in that: The method further includes identifying and removing abnormal points and outliers in the data set, and filling missing data with interpolation methods, and then: The initial data, dynamic force data and thermal pressure monitoring data are standardized respectively so that the data of different dimensions have the same dimensions; A normalization algorithm is used to scale each standardized data set to a range between 0 and 1 to eliminate scale differences between different data sources; The pre-processed initial data, dynamic force data and thermal pressure monitoring data are multi-dimensionally fused according to time series to form a comprehensive multi-dimensional data matrix; The time domain and frequency domain features are extracted from the fused multidimensional data matrix, and the time-frequency analysis method is introduced to extract the dynamic characteristics of the components under different stress and heating conditions to construct a preliminary feature vector.

9. The inspection method according to claim 8, characterized in that: The feature extraction algorithm using principal component analysis is used to extract key characteristic parameters of the components under different stress and heating conditions, specifically including: Perform principal component analysis on the constructed feature vector, calculate the variance contribution rate of each principal component, and select the principal component whose cumulative contribution rate reaches the preset threshold; The selected principal components are used as key feature parameters to form a low-dimensional feature vector; The correlation analysis method is used to further screen the extracted main components, retain the characteristic parameters most relevant to the performance of the components to be tested, and optimize the feature reconstruction of the retained key characteristic parameters; The extracted feature vectors are verified through an independent verification set, and the verified comprehensive feature vectors and key feature parameters are stored in the database.

10. The inspection method according to claim 6, characterized in that: The pre-construction of the support vector machine model and the training of the support vector machine model by the feature vector and the key feature parameters to obtain the performance test model specifically include: Set the initial hyperparameters of the support vector machine model, including the penalty factor C and kernel function parameters, and perform preliminary parameter selection through grid search or random search method to find the best hyperparameter combination; Dividing the preprocessed feature vector and key feature parameter data sets according to a preset ratio; The training set data is validated using k-fold cross validation. The training set is further divided into k subsets, and k-1 subsets are used for training in turn, and the remaining subset is used for validation to evaluate the performance of the model on different data subsets. Use the training set data to train the support vector machine model and iteratively optimize the model hyperparameters; optimize the penalty factor C and kernel function parameter σ of the support vector machine model through hyperparameter adjustment guided by cross-validation results; Use the test set data to evaluate the trained support vector machine model and calculate the performance indicators of the model's accuracy, recall, and F1 score; The performance of support vector machine models under different kernel functions and parameter settings is compared, and the optimal support vector machine model is selected using performance indicators as the final performance test model.

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