A USB pressing fixture testing method and USB pressing fixture

Abstract

The present invention discloses a testing method for a USB pressing jig and a USB pressing jig, the method comprising: performing preliminary detection on a predetermined area of ​​the pressing jig according to the operation data of the pressing jig; determining a target detection area according to the preliminary detection data; performing laser induced breakdown spectroscopy scanning on the target detection area to obtain spectral data; fusing the preliminary detection data and the spectral data to generate pollution characteristic data; performing time series analysis on the pollution characteristic data and historical pollution data to obtain pollution trend data; performing multi-physical field coupling analysis on the performance of the USB interface based on the pollution characteristic data and the pollution trend data to obtain a performance impact evaluation result; formulating and executing a differentiated cleaning strategy according to the evaluation result to clean the pressing jig. The technical solution of the present invention realizes efficient detection and trend prediction of contamination on the surface of the jig, and dynamically optimizes the cleaning strategy, which can effectively improve the performance of the jig and the long-term reliability of the USB interface.

Description

Technical Field

[0001] The present invention relates to the technical field of jig detection, and in particular to a testing method of a USB pressing jig and the USB pressing jig. Background Art

[0002] The USB pressing jig is a key device widely used in the manufacturing process of USB interface components to achieve precise pressing operations. Its structure usually includes core components such as solenoid valves, cylinders, upper molds and lower molds. Among them, the solenoid valve controls the air pressure changes of the cylinder to achieve precise adjustment of the pressing action; the cylinder is driven by air pressure to provide a smooth and efficient pressing force; the upper mold and the lower mold are used for the working parts that are in direct contact with the USB interface components. The design is usually customized according to the shape of the USB interface to ensure the accuracy and uniformity of the pressing. During operation, the jig controls the movement of the cylinder through the signal of the solenoid valve. The upper mold and the lower mold are closed or separated under the action of the cylinder, so as to perform precise mechanical pressing operations on the USB connector components to be processed. In this process, the stability of the pressure curve, the cleanliness of the mold surface and the repeatability of the pressing action have an important impact on the quality of the USB interface.

[0003] However, the existing USB pressing jigs have exposed some problems during long-term operation, which have affected their performance and service life. Since the jig needs to be in direct contact with the metal contacts of the USB connector components during repeated pressing operations, trace amounts of metal particles and conductive debris are easily accumulated on its surface. These microscopic contaminants may have no obvious effect on the pressing effect in the short term, but over time, these contaminants will gradually cover the key contact parts of the jig, resulting in uneven contact during the pressing process. In addition, environmental conditions (such as changes in humidity and temperature) and pressure fluctuations in the cylinder may aggravate the cumulative effect of contaminants, causing performance degradation on the mold surface. At the same time, these contaminants may be transferred to the metal contacts of the USB interface, causing signal interference, increased contact resistance, and even the risk of signal transmission interruption, seriously affecting the performance of the USB connector. The existing jigs lack an efficient detection and evaluation mechanism, and cannot monitor and analyze the accumulation of these microscopic contaminants in real time, which brings greater uncertainty to the formulation of subsequent maintenance and cleaning strategies. Summary of the invention

[0004] The main purpose of the present invention is to solve the technical problems that the existing USB pressing fixture is polluted due to the accumulation of microscopic metal particles and conductive debris during long-term operation, and lacks an effective detection and evaluation mechanism, making it impossible to monitor and accurately analyze the pollution status in real time, which may affect the electrical performance of the USB interface and the stability of signal transmission.

[0005] A first aspect of the present invention provides a method for testing a USB pressing fixture, the method comprising:

[0006] Obtain the operation data of the pressing fixture;

[0007] Performing preliminary inspection on a predetermined area of ​​the pressing jig according to the operation data to obtain preliminary inspection data;

[0008] Determine a target detection area according to the preliminary detection data;

[0009] Performing laser induced breakdown spectroscopy scanning on the target detection area to obtain spectral data;

[0010] fusing the preliminary detection data and the spectral data to obtain pollution characteristic data;

[0011] Perform time series analysis based on the pollution characteristic data and historical pollution data to obtain pollution trend data;

[0012] Performing a multi-physics field coupling analysis on the USB interface performance based on the pollution characteristic data and the pollution trend data to obtain a performance impact assessment result;

[0013] A differentiated cleaning strategy is developed and implemented based on the performance impact assessment results to clean the pressing fixture.

[0014] Optionally, the obtaining of operation data of the pressing jig includes:

[0015] Record the cumulative number of pressing times of the pressing fixture;

[0016] Collect pressing force curve data during each pressing process;

[0017] Acquire working environment parameters of the pressing fixture, wherein the working environment parameters include ambient temperature and humidity;

[0018] Detecting electrical connection parameters of the pressing fixture, wherein the electrical connection parameters include contact resistance and signal integrity index;

[0019] The accumulated pressing times, pressing force curve data, working environment parameters and electrical connection parameters are integrated into operation data of the pressing fixture.

[0020] Optionally, performing preliminary detection on a predetermined area of ​​the pressing jig according to the operation data to obtain preliminary detection data includes:

[0021] Analyze the cumulative number of pressing times in the operation data, and trigger preliminary detection when the cumulative number of pressing times reaches a preset threshold;

[0022] Calculating a pressing force deviation value according to the pressing force curve data in the operation data;

[0023] Determining an environmental impact coefficient based on the working environment parameters in the operating data;

[0024] Calculating an electrical performance degradation index using electrical connection parameters in the operation data;

[0025] Generate a heat map of a predetermined area of ​​the pressing fixture by combining the pressing force deviation value, the environmental impact coefficient and the electrical performance attenuation index;

[0026] Performing threshold segmentation on the heat map to identify potential abnormal areas;

[0027] Performing resistance scanning in the potential abnormal area to obtain resistance distribution data;

[0028] Performing micro-spectral imaging on the potential abnormal area to obtain surface reflectance spectrum data;

[0029] The resistance distribution data and the surface reflection spectrum data are fused to generate preliminary detection data.

[0030] Optionally, determining the target detection area according to the preliminary detection data includes:

[0031] Analyzing the resistance distribution and surface reflection spectrum data in the preliminary detection data, identifying areas with abnormal resistance and abnormal surface reflection, and marking these areas as potential contaminated areas;

[0032] Perform spatial overlay analysis on the potential contamination area, the signal transmission path and the power supply point of the USB interface to determine the key overlapping area that affects USB performance;

[0033] According to the location and range of the critical overlapping area and the functional importance of the USB interface, the contamination risk coefficient of each area is calculated;

[0034] Areas where the pollution risk factor exceeds the preset threshold are selected as target detection areas.

[0035] Optionally, performing laser induced breakdown spectroscopy scanning on the target detection area to obtain spectral data includes:

[0036] Performing three-dimensional surface modeling on the target detection area to generate a scanning path adapted to the groove structure of the pressing fixture mold;

[0037] According to the scanning path, dynamically adjust the laser focus to ensure that the laser pulse is perpendicular to the mold surface;

[0038] Double-pulse laser-induced breakdown is performed at each scanning point, the first pulse is used to clean the microscopic contaminants on the mold surface, and the second pulse is used to excite the mold surface material to form plasma;

[0039] Adjust the laser energy density in real time to adapt to the different curvatures and material properties of the mold surface;

[0040] Collect the plasma emission spectrum at each scanning point to obtain original spectrum data;

[0041] According to the depth distribution of the mold groove, the original spectrum data is depth corrected to obtain corrected spectrum data;

[0042] The corrected spectral data of all scanning points are integrated to obtain spectral data, which represents the spectral distribution of the target detection area in the form of a three-dimensional matrix.

[0043] Optionally, the fusing of the preliminary detection data and the spectral data to obtain pollution characteristic data includes:

[0044] Performing spatial registration on the resistance distribution data in the preliminary detection data and the spectrum data to establish a resistance-spectrum correspondence relationship;

[0045] Using a preset data fusion algorithm, the surface reflectance spectrum data in the preliminary detection data is fused with the spectrum data at a feature level;

[0046] Based on the fused data, the principal component analysis method is used to extract pollutant characteristics and determine the pollutant type and concentration distribution;

[0047] Calculate the influence coefficient of the pollutant on the contact resistance of the USB interface by combining the resistance distribution data, the type and concentration distribution of the pollutant;

[0048] The pollutant type, concentration distribution and contact resistance influence coefficient are comprehensively considered to generate multi-dimensional pollution characteristic data.

[0049] Optionally, performing time series analysis on the pollution characteristic data and historical pollution data to obtain pollution trend data includes:

[0050] Performing time alignment and data standardization on the pollution characteristic data and historical pollution data to obtain standardized time series data;

[0051] Using wavelet transform to perform multi-scale decomposition on the standardized time series data to obtain pollution characteristic components at different time scales;

[0052] Applying an autoregressive integrated moving average model to the pollution characteristic components of different time scales to obtain pollution trend prediction results at each scale;

[0053] Performing scale reconstruction according to the pollution trend prediction results at each scale to obtain comprehensive pollution trend prediction data;

[0054] Combined with the working cycle characteristics of the USB interface, the comprehensive pollution trend prediction data is periodically analyzed to obtain pollution trend data that takes periodic effects into account.

[0055] Optionally, performing a multi-physical field coupling analysis on the USB interface performance based on the pollution characteristic data and the pollution trend data to obtain a performance impact assessment result includes:

[0056] Calculating the time-varying contact resistance of key contact points of the USB interface according to the pollution characteristic data and the pollution trend data;

[0057] Utilizing the time-varying contact resistance, analyzing the current distribution change and local heating of the USB interface;

[0058] Based on the current distribution change and local heating conditions, the temperature field and stress field inside the USB interface are calculated;

[0059] According to the temperature field and the stress field, the signal transmission performance, the power transmission efficiency and the mechanical stability of the USB interface are evaluated;

[0060] By integrating the evaluation results of the signal transmission performance, power transmission efficiency and mechanical stability, a multi-dimensional score of the USB interface performance changing over time is generated to obtain a performance impact evaluation result.

[0061] Optionally, formulating and executing a differentiated cleaning strategy according to the performance impact assessment result to clean the pressing jig includes:

[0062] According to the performance impact assessment results, determine the serious contamination areas and contamination types on the pressing jig;

[0063] According to the seriously polluted area and pollution type, a matching cleaning method combination is selected from a preset cleaning method library;

[0064] Based on the combination of cleaning methods, generating a differentiated cleaning strategy including a cleaning sequence, a cleaning intensity, and a cleaning time;

[0065] Performing zone-by-zone cleaning on the pressing jig according to the differentiated cleaning strategy;

[0066] Rapidly test the pressed jig after cleaning to obtain cleaning effect data;

[0067] According to the cleaning effect data, it is determined whether the preset cleaning standard is reached. If not, the process returns to the step of executing the differentiated cleaning strategy until the preset cleaning standard is reached.

[0068] A second aspect of the present invention provides a USB pressing jig, which adopts the test method of the USB pressing jig adopted in the above embodiment.

[0069] The technical solution provided by the embodiments of the present application has at least the following advantages:

[0070] First of all, this solution lays the foundation for a comprehensive analysis of the contamination status by obtaining the operating data of the pressing fixture. The operating data not only includes basic operating parameters such as the cumulative number of pressings of the fixture and the pressing force curve data, but also covers working environment data such as ambient temperature and humidity, as well as electrical performance data such as contact resistance and signal integrity indicators. The acquisition of these data enables the key factors of the fixture's operating status to be fully covered, providing a reliable basis for subsequent analysis. For example, the cumulative number of pressings can intuitively reflect the intensity of fixture usage, while changes in contact resistance can serve as an important signal of the degree of surface contamination.

[0071] Secondly, based on the operation data, this solution designs a preliminary detection link to screen predetermined areas where contamination problems may exist. This process combines data analysis and image processing technology, such as detecting the pressing stability by analyzing the fluctuations in the pressing force curve, evaluating the potential impact of the outside world on the acceleration of contamination through environmental parameters, and intuitively displaying the location and distribution of potential contamination areas on the fixture surface through heat maps generated by resistance scanning and micro-spectral imaging. This detection method can accurately locate areas where contamination may exist through multi-parameter joint analysis, improve detection efficiency and reduce unnecessary global scanning.

[0072] After locking the target detection area, this solution uses laser induced breakdown spectroscopy technology to conduct in-depth detection of the fixture surface. Laser induced breakdown spectroscopy (LIBS) uses high-energy laser pulses to act on the target surface to form a tiny plasma. By analyzing the spectral characteristics of the plasma, the composition information of the pollutants can be obtained. The advantages of this technology are its non-contact and high sensitivity. It can accurately identify trace pollutants such as metal particles and conductive debris, and provide their concentration and distribution information. In addition, the accuracy of the spectral data is ensured by dynamically adjusting the laser focus and depth correction. This step provides a scientific basis for the accurate identification and quantification of pollutants.

[0073] Afterwards, by spatially registering and feature fusing the preliminary detection data with the spectral data, the distribution characteristics and types of contaminants and their impact on the contact resistance of the USB interface can be revealed. Specifically, the resistance distribution data reflects the overall condition of the electrical properties of the fixture surface, while the spectral data reveals the composition and concentration of microscopic contamination. The combination of the two not only improves the accuracy of the analysis, but also provides key input for subsequent performance evaluation.

[0074] Subsequently, this solution dynamically predicts the pollution characteristic data through time series analysis. This step uses historical pollution data to compare with real-time data, combined with wavelet transform and autoregressive model, to predict pollution trends on multiple time scales. The advantage of this prediction method is that it can detect potential pollution deterioration trends in advance, provide early warning information for maintenance and cleaning, and avoid further accumulation of problems.

[0075] Finally, this solution evaluates the performance of the USB interface through multi-physics field coupling analysis. Based on the pollution characteristic data and pollution trend data, the time-varying characteristics of the contact resistance are analyzed, and the impact of pollution on signal transmission, current distribution, temperature field and mechanical stability is calculated. For example, when pollutants cause the contact resistance to increase, it will cause the local current density to increase, thereby generating additional local heating, further affecting signal integrity and power transmission efficiency. Through multi-dimensional performance scoring, this solution can provide a scientific basis for differentiated cleaning strategies to ensure the targeted and efficient cleaning.

[0076] In summary, the solution of this application has built a complete technical chain from data acquisition to pollution detection, trend prediction, performance evaluation and formulation of cleaning strategies, which scientifically solves the problems of inaccurate pollution detection, incomplete impact assessment and inefficient cleaning treatment in the operation of existing USB pressing fixtures. Through the innovative combination of technical means, the present invention effectively improves the reliability of fixture operation and ensures the long-term performance and service life of the USB interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] 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 the structures shown in these drawings without paying creative work.

[0078] Figure 1 Flow chart of a method for testing a USB pressing fixture according to an embodiment of the present invention;

[0079] Figure 2 A schematic diagram of an embodiment of a USB pressing jig body.

[0080] Description of Figure Numbers:

[0081] 1. Air filter for air pressure regulation; 2. Air cylinder; 3. Upper die; 4. Lower die.

[0082] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0083] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments 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.

[0084] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back...), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0085] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, which must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0086] An embodiment of the present application provides a method for testing a USB pressing fixture. Figure 1 A flow chart of a method for testing a USB pressing fixture provided in an embodiment of the present application. In this embodiment, the method includes:

[0087] See also Figure 1 , obtain the operation data of the pressing fixture;

[0088] In one embodiment of the present invention, the obtaining of the operating data of the pressing jig includes: recording the cumulative number of pressings of the pressing jig; collecting pressing force curve data during each pressing process; obtaining the working environment parameters of the pressing jig, the working environment parameters including ambient temperature and humidity; detecting the electrical connection parameters of the pressing jig, the electrical connection parameters including contact resistance and signal integrity indicators; integrating the cumulative number of pressings, pressing force curve data, working environment parameters and electrical connection parameters into the operating data of the pressing jig.

[0089] Specifically, first, in order to record the cumulative number of pressings of the pressing jig, in some embodiments, a counting module can be set in the control system of the pressing jig. The counting module can identify each complete pressing action based on the movement of the cylinder. When the pressing cylinder completes a complete stroke from the initial state to the end state of pressing, the counting module will receive a trigger signal and record it incrementally in its memory. The reliability of this method stems from the mechanical consistency of the pressing action and the clarity of the control signal, which can accurately accumulate the number of pressings. For example, assuming that a jig completes 500 pressing operations in a day, the counting module will store 500 as the cumulative number of pressings for the day and dynamically update it over time. The advantage of recording the cumulative number of pressings is that the data can directly reflect the frequency of use and load intensity of the jig, providing a quantitative basis for determining whether the jig has reached the maintenance or detection threshold in subsequent detection.

[0090] Secondly, when collecting the pressing force curve data during each pressing process, it is necessary to combine sensor technology and signal processing algorithms. The pressing force curve is a dynamic characteristic curve that reflects the changes in the pressure applied by the fixture. Usually during the pressing process, the pressure shows a trend of gradually increasing, reaching a peak, and then gradually decreasing over time. In order to obtain this curve, a force sensor can be installed on the force transmission path of the fixture's cylinder or the pressing mold, and the output signal of the sensor can be recorded in real time through the data acquisition module. By matching the pressure value with the time point one by one, a complete pressing force curve is generated. The collection of the pressing force curve can determine whether there is an abnormality in the pressing action (such as too low or too high pressure), and on the other hand, it can provide preliminary clues for contamination detection. For example, abnormal pressing force indicates contamination or wear on the fixture surface.

[0091] In addition, detecting the electrical connection parameters of the pressing fixture (including contact resistance and signal integrity indicators) is an important step in evaluating the performance of the fixture. The contact resistance can reflect the electrical performance between the fixture surface and the USB connector contacts, while the signal integrity indicators can indicate whether there is interference or attenuation during signal transmission. To achieve this function, tools such as resistance measuring instruments and oscilloscopes can be used to measure the resistance value of the fixture contact points immediately after the pressing operation, and to capture and analyze the signal transmission waveform. For example, in one measurement, the recorded value of the contact resistance may increase from the initial 10 milliohms to 50 milliohms, indicating that contamination or poor contact has occurred on the fixture surface. In addition, by analyzing the eye diagram of the signal waveform, it can be determined whether there is a problem with the signal integrity, such as deformation of the waveform edge or increased jitter. Through the detection of these parameters, not only can the direct impact of contamination on electrical performance be clarified, but also support can be provided for the formulation of cleaning strategies.

[0092] Finally, the cumulative number of pressing times, pressing force curve data, working environment parameters and electrical connection parameters are integrated into the operation data of the pressing fixture, which can be achieved by building a data management system. In this system, data from different sources are synchronized through timestamps to form a complete data chain. For example, the record of a certain pressing operation includes 1000 pressing times, 500 Newtons of pressing force curve peak, 75% of ambient humidity, and 40 milliohms of contact resistance. These data are integrated to form a complete operation data entry and stored in the database. The advantage of integrating operation data is that it associates data of different categories, which is convenient for subsequent analysis and modeling. For example, through the operation data of multiple pressing operations, the relationship between pollution characteristics and pressing times, mechanical curves and environmental factors can be analyzed to form a more scientific prediction model.

[0093] By implementing each step through the above method, key data during the operation of the pressing fixture can be fully and accurately captured, providing reliable technical support for subsequent contamination detection and performance evaluation, thereby effectively solving the problem of difficult monitoring and analysis of fixture contamination.

[0094] Please continue reading Figure 1 , performing preliminary inspection on a predetermined area of ​​the pressing fixture according to the operation data to obtain preliminary inspection data;

[0095] In one embodiment of the present invention, the method of performing preliminary detection on a predetermined area of ​​the pressing fixture according to the operating data to obtain preliminary detection data includes: analyzing the cumulative number of pressings in the operating data, and triggering preliminary detection when the cumulative number of pressings reaches a preset threshold; calculating the pressing force deviation value according to the pressing force curve data in the operating data; determining the environmental impact coefficient based on the working environment parameters in the operating data; calculating the electrical performance attenuation index using the electrical connection parameters in the operating data; generating a heat map of the predetermined area of ​​the pressing fixture by combining the pressing force deviation value, the environmental impact coefficient and the electrical performance attenuation index; performing threshold segmentation on the heat map to identify potential abnormal areas; performing resistance scanning on the potential abnormal areas to obtain resistance distribution data; performing micro-spectral imaging on the potential abnormal areas to obtain surface reflection spectrum data; and performing data fusion on the resistance distribution data and the surface reflection spectrum data to generate preliminary detection data.

[0096] Specifically, the cumulative number of pressing times It is the basic data for judging the operating status of the pressing jig. The frequency of use of the jig is closely related to the accumulation of surface contamination, so the threshold is set. Monitor the cumulative number of pressings. The pressing control module records the completion signal of each pressing, and the system accumulates the number in real time. .when For example, taking HIWIN pneumatic fixture as an example, the experiment shows that the surface contamination degree increases significantly after 3000 pressings, so the system is set = 3000. This method ensures the accuracy of detection timing through experimental calibration and avoids the waste of resources and risks caused by frequent or delayed detection.

[0097] The pressing force curve reflects the dynamic relationship between pressure and time during the pressing process. The standard pressing curve is The actual measured curve is The pressing force deviation value is calculated by comparing the maximum deviation of the two, and the formula is:

[0098] .

[0099] in, Indicates the deviation value. If the deviation value increases significantly, it indicates that there is contamination on the surface of the fixture. For example, the actual curve recorded in a certain pressing shows that the peak pressure is 15% lower than the standard value, and the shape of the pressure distribution curve is offset. Combined with experimental analysis, this is related to the accumulation of particles on the surface of the fixture affecting the contact uniformity. The calculation of the pressing force deviation value intuitively reflects the mechanical anomaly of the fixture during the pressing process, providing an important basis for subsequent testing.

[0100] Working environment parameters (such as temperature T and humidity H) directly affect the attachment and diffusion of pollutants. The environmental impact coefficient is calculated by the following formula:

[0101] .

[0102] in, and is a weight coefficient, which indicates the relative contribution of temperature and humidity to pollution. For example, when the ambient humidity is higher than 80% and the temperature reaches 35°C, the humidity has a higher weight because high humidity accelerates the attachment of particles, while high temperature leads to an increase in oxidation reactions. By quantifying the environmental impact coefficient, the potential acceleration of the accumulation of pollutants in the working environment of the fixture can be more accurately evaluated.

[0103] The electrical performance degradation index combines the contact resistance and signal integrity indicators. The contact resistance change rate is calculated as:

[0104] .

[0105] in, is the current contact resistance, is the initial contact resistance, and N is the cumulative number of press-fits. Signal integrity indicators are measured through eye diagram jitter values. Indicates. Electrical performance degradation index The calculation formula is:

[0106] .

[0107] in, and Indicates the weight of contact resistance and signal integrity on performance degradation. For example, a test shows It increased by 50%, and the signal jitter value increased significantly, indicating that the contamination on the surface of the fixture is having an adverse effect on the electrical performance.

[0108] Combining the pressure deviation value, environmental impact coefficient and electrical performance attenuation index, a heat map of the predetermined area is generated through image processing technology. The heat map uses color coding (such as red, yellow, and green) to intuitively reflect the pollution risk level. For example, the red area corresponds to a high pollution risk, while the green area represents an area in good condition. By performing threshold segmentation on the heat map, potential abnormal areas can be quickly identified and the key inspection areas for subsequent detection can be located.

[0109] In abnormal areas, resistance scanning technology is used to obtain resistance distribution data. For example, areas with high resistance values ​​(such as 150mΩ) indicate poor contact or surface contamination. In the same area, reflectance spectrum data is collected through micro-spectral imaging technology. For example, a characteristic absorption peak at a wavelength of 450nm indicates that oxide particles are attached to the area.

[0110] The resistance distribution data is spatially registered with the spectral data to ensure that each spatial point contains both electrical and optical properties. Fusion algorithms (such as principal component analysis) are used to extract contamination features. For example, the fused data of a certain area shows that the resistance value increases by 50%, and the spectral absorption intensity is significantly enhanced. Combined with database matching, it is inferred that the contaminant in this area is iron oxide particles with a concentration of about 2µg / mm². The preliminary test data not only reveals the type and concentration of the contaminant, but also quantifies its specific impact on the performance of the fixture.

[0111] Through this complete implementation process, each step converts raw data into accurate detection information in a scientific and quantifiable way, which not only solves the technical problem of difficult-to-monitor pollution accumulation, but also provides comprehensive support for performance evaluation and cleaning strategy formulation, thereby significantly improving the reliability and maintenance efficiency of the fixture.

[0112] Please continue reading Figure 1 , determining a target detection area according to the preliminary detection data;

[0113] In one embodiment of the present invention, determining the target detection area based on the preliminary detection data includes: analyzing the resistance distribution and surface reflection spectrum data in the preliminary detection data, identifying areas with abnormal resistance and abnormal surface reflection, and marking these areas as potential contamination areas; performing spatial superposition analysis on the potential contamination areas with the signal transmission path and power supply points of the USB interface to determine the key overlapping areas that affect USB performance; calculating the pollution risk coefficient of each area based on the location and range of the key overlapping areas and the functional importance of the USB interface; and selecting areas with pollution risk coefficients exceeding a preset threshold as target detection areas.

[0114] Specifically, by analyzing the resistance distribution and surface reflection spectrum data in the preliminary detection data, areas with abnormal resistance and abnormal surface reflection can be identified. The resistance distribution data reflects the electrical performance status of different areas on the fixture surface, while the surface reflection spectrum data provides information on the optical properties and contaminant composition of the surface material. The abnormal resistance area can be obtained by analyzing the local changes in the resistance distribution data. For example, the resistance gradient detection algorithm is used to calculate the resistance change rate between adjacent spatial points:

[0115] .

[0116] in, Represents a spatial coordinate point The resistance value, and represents adjacent spatial points, represents the resistance gradient. If the resistance exceeds the set threshold, the area is identified as an abnormal resistance area. At the same time, the abnormal area of ​​the surface reflectance spectrum is determined by comparing the difference between the characteristic absorption peak of the spectral curve and the standard spectral template. For example, the reflectance spectrum of a certain area has a specific absorption peak at 450nm, indicating that there is oxide particle contamination in the area. In this way, the abnormal points of the electrical and optical properties of the fixture surface can be marked as potential contamination areas.

[0117] Next, the potential contamination area is spatially superimposed with the signal transmission path and power supply point of the USB interface to further screen the key areas that have the most significant impact on USB performance. The core of the spatial superposition analysis is to calculate the spatial distance between the potential contamination area and the signal transmission path and power supply point. The formula is as follows:

[0118] .

[0119] in, Indicates the center point of the potential contamination area A reference point on the signal transmission path or power supply point The Euclidean distance between . Indicates the set critical distance threshold. The potential contamination area is determined to overlap with the signal transmission path or power supply point. It is determined based on the actual physical characteristics and electrical layout of the USB interface. For example, for a certain USB interface, set =1mm to ensure that the overlap area accurately covers the critical impact range of signals and power. In actual operation, if the center point of a potential contamination area The closest point to the USB data channel path is 0.8mm, then the condition is met , the area is determined to be the key overlapping area.

[0120] After screening out the key overlapping areas, the pollution risk coefficient of each area is calculated based on the location and scope of these areas and the functional importance of the USB interface. The pollution risk coefficient reflects the potential threat of pollution in the area to the performance of the USB interface, and the calculation formula is:

[0121] .

[0122] in, represents the area of ​​the polluted area, is the functional importance weight corresponding to the region, and The functional importance weight is assigned according to the distribution of key parts of the USB interface. For example, the weight value of the signal path area will be higher than that of the non-critical structure area. If the area of ​​a contaminated area is 2mm² and highly overlaps with the data channel, its functional weight is 0.9, and the weight coefficient =0.6, =0.4, then the risk factor is:

[0123] =0.6×2+0.4×0.9=1.74.

[0124] Finally, the risk factors of all contaminated areas are compared with the preset thresholds. Compare and select ≥ Assume that the threshold is set to 1.5, and the risk factor of the aforementioned area is 1.74, which exceeds the threshold, so it is preferentially selected as the target detection area.

[0125] Through this systematic analysis process, the areas that have the greatest impact on the performance of the USB interface can be accurately identified and prioritized for subsequent inspection and cleaning. The advantage of this method is that it combines the electrical and optical properties of the fixture with the functional layout of the USB interface, and through the comprehensive analysis of multi-dimensional data, it achieves high accuracy in contamination location and efficient allocation of inspection resources, thus providing a strong scientific basis for subsequent maintenance.

[0126] Please continue reading Figure 1 , performing laser induced breakdown spectroscopy scanning on the target detection area to obtain spectral data;

[0127] In one embodiment of the present invention, the target detection area is subjected to laser induced breakdown spectroscopy scanning to obtain spectral data, including: three-dimensional surface modeling of the target detection area to generate a scanning path adapted to the groove structure of the pressing fixture mold; according to the scanning path, the laser focus is dynamically adjusted to ensure that the laser pulse is perpendicular to the mold surface; double-pulse laser induced breakdown is performed at each scanning point, the first pulse is used to clean microscopic contaminants on the mold surface, and the second pulse is used to excite the mold surface material to form plasma; the laser energy density is adjusted in real time to adapt to different curvatures and material properties of the mold surface; the plasma emission spectrum of each scanning point is collected to obtain original spectral data; according to the depth distribution of the mold groove, the original spectral data is depth corrected to obtain corrected spectral data; the corrected spectral data of all scanning points are integrated to obtain spectral data, and the spectral data represents the spectral distribution of the target detection area in the form of a three-dimensional matrix.

[0128] Specifically, first, in order to perform 3D surface modeling of the target detection area, a high-precision scanning system is required to perform 3D measurement of the mold surface of the fixture. The purpose of 3D surface modeling is to obtain the true geometric shape of the mold groove, including curvature changes, depth distribution, and edge contours. This process is usually expressed in the form of a coordinate point cloud, that is, through the 3D coordinates of the space points Represents the geometric structure of the mold surface. Through the fitting algorithm, the point cloud data is converted into a continuous three-dimensional surface model. For example, for a USB pressing fixture, the mold surface has multiple groove structures of varying depths. The result of surface modeling can accurately reflect the shape and distribution of these grooves. The advantage of three-dimensional modeling is that it provides an accurate geometric basis for subsequent laser path planning, ensuring that the scanning path can fully cover the target detection area.

[0129] Next, based on the results of 3D surface modeling, a scanning path adapted to the mold groove structure is generated. The design of the scanning path needs to take into account the curvature of the mold surface and the groove depth to ensure that the laser beam can act on each surface point at a vertical angle. Path generation uses piecewise linear fitting or curve interpolation methods to decompose complex 3D surfaces into multiple scannable linear path segments. For example, on a mold containing multiple hemispherical grooves, path planning will prioritize covering the bottom and edge areas of the grooves to ensure that these areas are not missed due to geometric complexity. Through path planning, laser scanning can efficiently and comprehensively cover the target inspection area.

[0130] During the scanning process, dynamically adjusting the laser focus is a key step to ensure that the laser pulse is perpendicular to the mold surface. The adjustment of the laser focus needs to be based on the 3D modeling data, and the normal vector direction of each scanning point needs to be calculated in real time. The laser beam is made to act perpendicularly on the mold surface by controlling the angle of the laser head. This dynamic adjustment avoids the loss of laser energy or the reduction of detection accuracy due to angle deviation. For example, in the groove edge area, due to the large surface inclination, the normal calibration of the laser beam can significantly improve the intensity and consistency of the spectral signal.

[0131] A double-pulse laser-induced breakdown operation is performed at each scanning point, where the first pulse is used to clean the microscopic contaminants on the mold surface, and the second pulse is used to excite the mold material to form plasma. The principle of the double-pulse technology is to remove attached particles and contaminants through the first lower-energy laser pulse to ensure that the signal will not be interfered by the contaminants during subsequent spectral analysis, while the second higher-energy laser pulse directly excites the material on the mold surface, generates high-temperature plasma and releases spectral signals. For example, at a scanning point at the bottom of the groove, after the attached metal particles are removed by the double-pulse operation, the spectral analysis can directly obtain the composition information of the mold material without being interfered by the absorption spectrum of the contaminants.

[0132] Real-time adjustment of laser energy density is the key to adapting to different curvatures and material properties of the mold surface. The adjustment of laser energy density is based on the surface curvature and the thermophysical properties of the material, and the laser power is dynamically adjusted through a feedback control system. For example, for metal materials with higher thermal conductivity, the laser energy needs to be slightly increased to ensure the full formation of plasma, while in the edge area with larger curvature, reducing the laser energy can avoid material damage caused by over-excitation. The advantage of this dynamic adjustment is that it achieves uniform excitation of different surface areas and improves the reliability of spectral data.

[0133] Subsequently, the plasma emission spectrum of each scanning point is collected and the raw spectrum data is obtained. The plasma emission spectrum is recorded by a spectrometer, reflecting the elemental composition and physical state of the excited material. For example, at a certain scanning point, a strong peak of a specific wavelength (such as 500nm) appears in the spectrum, which corresponds to the characteristic emission of a certain metal element in the mold material. These raw spectrum data provide the basis for subsequent depth correction.

[0134] In order to make the spectral data more accurate, the original spectral data needs to be depth corrected according to the depth distribution of the mold groove. The goal of depth correction is to compensate for the effect of groove depth on spectral signal intensity, such as signal attenuation caused by different optical path lengths. The correction method is based on the depth attenuation model, and the formula is:

[0135]

[0136] in, is the corrected spectral intensity, is the original spectral intensity, is the attenuation coefficient, is the groove depth. After correction, the spectral data can more accurately reflect the actual composition of the mold material.

[0137] Finally, the corrected spectral data of all scanning points are integrated to generate a three-dimensional matrix of spectral data to represent the spectral distribution of the target detection area. The three-dimensional matrix is ​​represented by spatial coordinates Each point contains the corresponding spectral information. For example, in the spectral matrix of the groove area, the distribution of the characteristic peak of a certain pollutant in a specific area can be clearly seen. The advantage of this three-dimensional spectral data is that it presents the pollution and material information of the target area in an intuitive way, providing comprehensive support for subsequent pollution assessment and cleaning strategy formulation.

[0138] Through the detailed implementation of the above steps, a complete analysis system was built from three-dimensional modeling to spectral data integration, which achieved precise scanning of the target area and accurate acquisition of spectral features, significantly improving detection efficiency and data quality.

[0139] Please continue reading Figure 1 , fusing the preliminary detection data and the spectral data to obtain pollution characteristic data;

[0140] In one embodiment of the present invention, the preliminary detection data and the spectral data are fused to obtain pollution characteristic data, including: spatially aligning the resistance distribution data in the preliminary detection data and the spectral data to establish a resistance-spectrum correspondence; using a preset data fusion algorithm to perform feature-level fusion of the surface reflection spectrum data in the preliminary detection data and the spectral data; based on the fused data, using principal component analysis to extract pollutant characteristics and determine the pollutant type and concentration distribution; combining the resistance distribution data, pollutant type and concentration distribution to calculate the influence coefficient of pollutants on the contact resistance of the USB interface; and comprehensively combining the pollutant type, concentration distribution and contact resistance influence coefficient to generate multi-dimensional pollution characteristic data.

[0141] Specifically, first of all, spatial registration of the resistance distribution data and spectral data in the preliminary test data is the basis of the whole process. The purpose of spatial registration is to align data from different sources so that data at the same spatial position can correspond to the same coordinate system. The resistance distribution data reflects the electrical properties of different positions on the fixture surface, while the spectral data provides information on the composition of the contaminants. The spatial registration of the two requires ensuring that each spatial point (such as the three-dimensional coordinate ) contain both resistance value and spectral feature information. Registration can be achieved through geometric calibration of the same reference point. For example, the structural feature points on the mold surface are used as reference points, and the two-dimensional grid of resistance distribution is aligned with the three-dimensional matrix of spectral data through coordinate transformation. For example, if the resistance value of a point is 100mΩ, and its corresponding spectrum shows a strong absorption peak at a wavelength of 450nm, this information can be accurately bound to the spatial coordinates of the point through registration. The advantage of this spatial registration is that it lays the foundation for subsequent data fusion and ensures that multiple data can be analyzed in the same space.

[0142] After completing the spatial registration, the preset data fusion algorithm is used to perform feature-level fusion of the surface reflectance spectrum data and the spectral data. The goal of data fusion is to combine the advantages of the two types of data, combining the surface pollution characteristics in the surface reflectance spectrum with the pollutant component information in the spectral data to obtain a more complete description of the pollutant characteristics. The feature-level fusion method can use an algorithm based on weighted linear superposition, normalizing the feature vectors of each type of data and then performing a weighted combination based on the importance weight of the feature. The specific formula is:

[0143] .

[0144] in, represents the fused feature vector, and Represent the feature vectors of surface reflectance spectrum data and spectral data respectively, and is the feature weight, which is determined by experiments. For example, in a certain area, the surface reflectance spectrum shows a smooth surface feature, while the spectral data shows a strong absorption peak at the characteristic wavelength of metal oxides. Through fusion, it can be concluded that the pollutant type in this area is oxidized metal particles. The advantage of feature-level fusion is that it retains the key information of both data at the same time, thus providing more dimensional support for pollutant analysis.

[0145] Based on the fused data, the use of principal component analysis to extract pollutant characteristics is a key step to further determine the type and concentration distribution of pollutants. Principal component analysis (PCA) uses dimensionality reduction technology to project multidimensional data into a low-dimensional space and extract the most representative pollutant characteristics. The specific method is to calculate the covariance matrix of the fused data, solve its eigenvalues ​​and eigenvectors, and project the data to the direction of the eigenvector with the largest eigenvalue. For example, the fused data of a certain area contains information on multiple pollutants in a high-dimensional space. PCA can extract the main components and classify the main components to determine that the pollutant type in the area is iron oxide, and calculate its concentration to be 2µg per square millimeter. The advantage of principal component analysis is that it can effectively reduce the redundancy of data, highlight the main pollution characteristics, and provide an efficient tool for further analysis of pollution distribution.

[0146] Combining the resistance distribution data, pollutant type and concentration distribution, the influence coefficient of pollutants on the contact resistance of the USB interface can be calculated. The change in contact resistance directly reflects the degree of influence of pollutants on the electrical performance of the fixture. The calculation formula of the influence coefficient is:

[0147] .

[0148] in, represents the influence coefficient, Indicates the change in contact resistance caused by contaminants, Indicates the change in pollutant concentration. For example, in a certain area, the pollutant concentration increases from 2µg / mm² to 4µg / mm², and the contact resistance increases from 100mΩ to 150mΩ. The calculated impact coefficient is: =25mΩ / (µg / mm2). This coefficient intuitively quantifies the impact of pollutants on electrical properties and provides a quantitative basis for subsequent performance evaluation.

[0149] Finally, multi-dimensional pollution feature data is generated by integrating the pollutant type, concentration distribution and contact resistance influence coefficient. Multi-dimensional pollution feature data is indexed by spatial coordinates, and each point contains the type and concentration of the pollutant and its comprehensive impact on electrical properties. For example, in the feature data of a certain pollution-concentrated area, the concentration distribution map of iron oxide particles and the corresponding contact resistance changes can be clearly seen. These data can provide clear guidance for the formulation of cleaning strategies.

[0150] Through the above process, each step is closely centered around the goal, ensuring that data acquisition, analysis, and integration are scientific and logical. The multi-dimensional pollution feature data generated in the end can fully reflect the pollution status of the fixture, improving the accuracy and efficiency of pollution analysis. The advantage of this method is that it integrates the advantages of multi-source data, provides comprehensive pollution assessment results through precise calculation and analysis, and provides important technical support for fixture maintenance and USB interface performance assurance.

[0151] Please continue reading Figure 1 , performing time series analysis based on the pollution characteristic data and historical pollution data to obtain pollution trend data;

[0152] In one embodiment of the present invention, the time series analysis is performed on the pollution characteristic data and the historical pollution data to obtain the pollution trend data, including: time alignment and data standardization of the pollution characteristic data and the historical pollution data to obtain standardized time series data; multi-scale decomposition of the standardized time series data using wavelet transform to obtain pollution characteristic components of different time scales; applying an autoregressive integral moving average model to the pollution characteristic components of different time scales to obtain pollution trend prediction results of each scale; reconstructing the scale according to the pollution trend prediction results of each scale to obtain comprehensive pollution trend prediction data; and performing periodic analysis on the comprehensive pollution trend prediction data in combination with the working cycle characteristics of the USB interface to obtain pollution trend data that takes periodic effects into account.

[0153] Specifically, first of all, time alignment and data standardization of pollution characteristic data and historical pollution data are the basis for ensuring the accuracy of time series analysis. Pollution characteristic data are collected in real time during the detection process, including multi-dimensional data such as pollutant type, concentration distribution and contact resistance influence coefficient, while historical pollution data are related data sets recorded previously. Since the collection of the two sets of data may have inconsistent timestamps, it is necessary to align the time axis through an interpolation algorithm so that the data at each time point can be accurately matched. For example, during the detection process, if the time interval of the pollution characteristic data is 1 hour, and the recording time interval of the historical data is 2 hours, it is necessary to interpolate the historical data to generate a time distribution consistent with the real-time data. The completion of time alignment ensures the temporal consistency of subsequent data fusion and analysis.

[0154] After time alignment is completed, it is necessary to standardize the pollution characteristic data and historical pollution data. Due to the different dimensions and ranges of characteristics such as pollutant concentration and resistance change, direct analysis will lead to deviations in the results. Standardization is done by removing the mean and unitizing the data so that the data is expressed in the form of a standard normal distribution. The formula is:

[0155] .

[0156] in, is the standardized data, is the original data, and are the mean and standard deviation of the data respectively. The standardized time series data ensures that different features are analyzed on the same scale, thus avoiding the excessive influence of certain features on the analysis results.

[0157] Next, multi-scale decomposition of standardized time series data is a key step in analyzing the changing trend of pollution characteristics. Wavelet transform is a method that can analyze signals in both time and frequency domains. By decomposing the time series into characteristic components of multiple different time scales, it can reveal the changing trend of pollution characteristics in different time ranges. The formula of wavelet transform is:

[0158] .

[0159] in, Representation scale and location The transformation result is: is a time series signal, is the wavelet function, represents the complex conjugate operation. By adjusting the scale parameter , we can obtain pollution characteristic components from short-term changes to long-term trends. For example, the time series of a pollutant concentration shows details of daily fluctuations in small-scale components and seasonal slow growth trends in large-scale components.

[0160] After obtaining the pollution characteristic components at different time scales, the autoregressive integrated moving average model (ARIMA) is applied to predict the trend of each component. The ARIMA model accurately models the pollution trend by combining the autoregressive characteristics, difference operation and moving average characteristics of the time series. The form of the ARIMA model is:

[0161] .

[0162] in, is the current value of the time series, , is the autoregressive coefficient, and is the moving average coefficient, is a random error term. By fitting components of different time scales, short-term fluctuations and long-term trends can be predicted. For example, the short-term component prediction of pollution characteristics shows that the concentration of pollutants will increase in the next week due to the increase in the frequency of compression, while the long-term component prediction shows that the concentration of pollutants shows a periodic decrease on a longer time scale.

[0163] After completing the predictions at each time scale, the pollution trend prediction results at different time scales are integrated into comprehensive pollution trend prediction data through scale reconstruction. The purpose of scale reconstruction is to combine short-term fluctuations and long-term trends to form a more comprehensive pollution prediction result. For example, in a reconstructed comprehensive trend, it is possible to see the detailed changes in daily pollutant concentrations and their overall change trends throughout the season at the same time.

[0164] Finally, combined with the working cycle characteristics of the USB interface, a periodic analysis of the comprehensive pollution trend prediction data is performed. The working cycle characteristics of the USB interface include the pressing frequency, working time distribution, etc. These factors have a direct impact on the accumulation of pollution. The periodic analysis extracts the periodic component in the pollution trend through Fourier transform, and the formula is:

[0165] .

[0166] in, is the frequency component, is a time series signal, is the length of the signal. By analyzing the frequency components, it is possible to identify the main periods of pollutant concentration and compare them with the operating cycle of the USB interface. For example, in one analysis, it was found that the main period of pollutant concentration coincided with the weekly operating cycle of the fixture, indicating that the operating frequency has a significant impact on the accumulation of pollutants.

[0167] Through the above steps, the pollution trend data that takes into account the periodic impact can not only accurately reflect the short-term changes and long-term trends of pollutants, but also reveal the relationship between pollution accumulation and working mode in combination with the actual working characteristics of the USB interface. The advantage of this method is that it achieves a comprehensive prediction of pollution trends through multi-scale and multi-dimensional analysis, providing a scientific basis for fixture maintenance and pollution prevention and control, while ensuring that the prediction results are highly timely and practical.

[0168] Please continue reading Figure 1 , performing a multi-physical field coupling analysis on the USB interface performance based on the pollution characteristic data and the pollution trend data to obtain a performance impact assessment result;

[0169] In one embodiment of the present invention, the multi-physical field coupling analysis of the USB interface performance based on the pollution characteristic data and the pollution trend data is performed to obtain a performance impact evaluation result, including: calculating the time-varying contact resistance of the key contact points of the USB interface according to the pollution characteristic data and the pollution trend data; analyzing the current distribution changes and local heating conditions of the USB interface by using the time-varying contact resistance; calculating the temperature field and stress field inside the USB interface based on the current distribution changes and local heating conditions; evaluating the signal transmission performance, power transmission efficiency and mechanical stability of the USB interface according to the temperature field and stress field; and generating a multi-dimensional score of the USB interface performance over time by integrating the evaluation results of the signal transmission performance, power transmission efficiency and mechanical stability to obtain a performance impact evaluation result.

[0170] Specifically, first, the time-varying contact resistance of the key contact points of the USB interface is calculated based on the pollution characteristic data and pollution trend data. The pollution characteristic data includes the type, concentration and distribution of pollutants, while the pollution trend data describes the change pattern of these characteristics over time. The change of contact resistance is mainly affected by the dynamic change of pollutant concentration, so it is necessary to combine the trend of contact point pollution concentration over time to dynamically model the contact resistance. For example, assuming that the pollutant concentration increases linearly over a period of time, the initial contact resistance is 10mΩ, and the pollution characteristic data shows that the pollution concentration of the contact point increases by 2µg / mm² per month, the contact resistance may increase from 10mΩ to 30mΩ over time. Through this modeling process, the impact of pollution on the electrical performance of the contact point can be effectively quantified.

[0171] After obtaining the time-varying contact resistance, it is necessary to further analyze the current distribution changes and local heating of the USB interface. The change in current distribution can be achieved by simulating the impact of the contact point resistance distribution on the current path. In areas with high contact point resistance, the resistance to current flow will increase significantly, resulting in current redistribution. This change causes the current density in some areas to increase significantly, while the current flow in other areas decreases. The local heating situation is analyzed through the relationship between current density and contact resistance. When the current density increases and the contact resistance is large, the area will generate higher Joule heat. This phenomenon is particularly significant in highly polluted areas. For example, in an area with a contact resistance of 50mΩ and a local current density increased to 0.2A / mm², the local temperature may be significantly higher than the surrounding area. This analysis not only reveals the abnormal current distribution caused by pollution, but also provides input conditions for subsequent heat conduction calculations.

[0172] Based on the change in current distribution and local heating, the temperature field and stress field inside the USB interface can be further calculated. The temperature field reflects the thermal distribution state of the USB interface under the influence of pollution, while the stress field describes the thermal expansion effect caused by temperature changes. The temperature field calculation is based on the law of heat conduction, taking into account the distribution of heat sources and the thermal conductivity of materials. For example, in the local heating area, due to the concentration of heat and poor thermal conductivity, the temperature may reach 80°C, while the temperature in the surrounding area is maintained below 40°C. The stress field calculation needs to be combined with the distribution of the temperature field to calculate the stress distribution through the thermal expansion coefficient and the elastic modulus of the material. For example, in the edge area of ​​the interface, due to the large temperature difference, a stress peak of more than 200MPa may be formed, posing a threat to the mechanical stability of the interface.

[0173] After completing the calculation of the temperature field and stress field, the signal transmission performance, power transmission efficiency and mechanical stability of the USB interface need to be evaluated. Signal transmission performance is mainly evaluated by analyzing the impact of electrical performance changes on signal waveforms, such as whether the eye diagram jitter value in signal integrity increases significantly. Power transmission efficiency evaluates the power loss of the USB interface under high contact resistance and abnormal current distribution. Higher contact resistance will lead to a significant reduction in power transmission efficiency. Mechanical stability analyzes the stress distribution in the stress field to determine whether there is an area that exceeds the yield strength of the material, thereby evaluating the structural integrity of the USB interface under the influence of contamination. For example, in a high stress area, the stress reaches 250MPa, while the yield strength of the material is 300MPa. Although it has not exceeded the safety limit, long-term high stress will cause fatigue damage.

[0174] Finally, the evaluation results of signal transmission performance, power transmission efficiency and mechanical stability are integrated to generate a multi-dimensional score of the USB interface performance over time, and the performance impact evaluation results are obtained. The multi-dimensional score normalizes and comprehensively processes the evaluation results by assigning weights to each performance indicator. For example, if the signal transmission performance score is 0.8, the power transmission efficiency score is 0.9, and the mechanical stability score is 0.7, and the weights of the three are 0.4, 0.3, and 0.3 respectively, then the final comprehensive score is 0.8×0.4+0.9×0.3+0.7×0.3=0.81. The scoring results can quantify the overall changes in USB interface performance and provide a reliable basis for further maintenance and improvement.

[0175] Through the above implementation process, the impact of pollution on the performance of the USB interface is quantified as a time-dynamic evaluation result, and each step is based on pollution characteristics, physical laws and performance indicators. The advantage of this method is that it fully considers the multi-faceted impact of pollution on the electrical, thermal and mechanical properties of the USB interface. The generated multi-dimensional score not only provides a scientific basis for performance evaluation, but can also be used to predict and plan the maintenance cycle of the USB interface, significantly improving the reliability and controllability of the system operation.

[0176] Please continue reading Figure 1 , formulate and implement differentiated cleaning strategies based on the performance impact assessment results to clean the pressing fixture.

[0177] In one embodiment of the present invention, the method of formulating and executing a differentiated cleaning strategy based on the performance impact assessment result to clean the pressing jig includes: determining the severely contaminated areas and contamination types on the pressing jig based on the performance impact assessment result; selecting a matching cleaning method combination from a preset cleaning method library for the severely contaminated areas and contamination types; generating a differentiated cleaning strategy including a cleaning sequence, cleaning intensity, and cleaning time based on the cleaning method combination; performing area-by-area cleaning on the pressing jig according to the differentiated cleaning strategy; performing a rapid inspection on the cleaning jig to obtain cleaning effect data; judging whether the preset cleaning standard is met based on the cleaning effect data, and if not, returning to the step of executing the differentiated cleaning strategy until the preset cleaning standard is met.

[0178] Specifically, first, based on the performance impact assessment results, the severely contaminated areas and types of contamination on the pressing fixture are determined. This process relies on previously generated contamination feature data, which includes the spatial distribution and concentration of contaminants and their impact on electrical properties. The criteria for judging severely contaminated areas can be combined with the threshold analysis of contact resistance changes and contamination concentrations. For example, if the contaminant concentration in a certain area exceeds 5 µg / mm² and causes the contact resistance to increase by more than 50%, the area is judged to be a severely contaminated area. Furthermore, the type of contamination is identified by matching the characteristic peaks of spectral analysis. For example, the characteristic band of iron oxide appears in the spectral data, indicating that the main contaminant in the area is iron oxide particles. This analysis process can accurately identify the type of contaminant and provide a basis for the selection of subsequent cleaning methods.

[0179] After the seriously polluted areas and types of pollution are determined, the next key step is to select a matching cleaning method combination from the preset cleaning method library. The cleaning method library presets cleaning technologies for different types of pollutants. For example, ultrasonic cleaning can be selected for particulate pollutants, while chemical dissolution cleaning is preferred for oxide pollution. The basis for method selection lies in the physical and chemical properties of the pollutants and the adaptability of the cleaning method. For example, for iron oxide particles, it is more efficient to choose a weak acid solution for dissolution cleaning, and combining it with mechanical vibration can enhance the cleaning effect. The advantage of the cleaning method combination is that it improves the cleaning efficiency through the synergistic effect of multiple methods, while avoiding the problem of insufficient or excessive cleaning caused by a single method.

[0180] Based on the selected combination of cleaning methods, a differentiated cleaning strategy including cleaning sequence, cleaning intensity and cleaning time is generated. The formulation of the cleaning sequence needs to take into account the severity of contamination and the physical properties of the fixture surface. For example, give priority to areas with severe contamination to avoid the spread of contamination to other areas. The adjustment of cleaning intensity is based on the adhesion strength of contaminants and the tolerance of the fixture surface material. For example, for fragile mold surfaces, the cleaning intensity needs to be appropriately reduced to avoid surface damage. The setting of cleaning time combines cleaning efficiency and contaminant concentration to ensure that the preset cleaning effect is achieved in the shortest time. The differentiated cleaning strategy achieves precise control of the cleaning process through comprehensive analysis to meet the cleaning needs of different areas and contaminants.

[0181] According to the differentiated cleaning strategy, cleaning the pressing jig in different areas is the core step of cleaning implementation. In this process, the cleaning plan for each area is implemented separately. For example, for the groove area, since there may be a lot of contaminants accumulated, the cleaning time and intensity need to be appropriately increased, and a combination of dissolution cleaning and mechanical cleaning is used. For the flat area, ultrasonic cleaning is more efficient. By treating the different areas, it is ensured that the different contamination conditions on the surface of the jig can be fully cleaned, while avoiding excessive treatment of the uncontaminated areas.

[0182] After the cleaning process is completed, the fixture needs to be quickly tested to obtain cleaning effect data. Rapid testing can be combined with resistance scanning and spectral analysis to determine whether the fixture surface has returned to its initial state after cleaning. For example, if the contact resistance of the cleaned area is restored to 10 mΩ and the characteristic peaks of the contaminants in the spectrum completely disappear, it indicates that the cleaning effect is good. The acquisition of cleaning effect data can directly verify the effectiveness of the cleaning strategy and provide a basis for further adjustments.

[0183] Based on the cleaning effect data, determine whether the preset cleaning standard is met. If the cleaning effect does not meet the standard, for example, the pollutant concentration still exceeds the threshold or the contact resistance has not recovered, it is necessary to return to the differentiated cleaning strategy step, adjust the cleaning parameters and clean again. Such a closed-loop control process ensures that the final cleaning result meets the requirements while avoiding unnecessary waste of resources.

[0184] Through the comprehensive implementation of the above method, each step revolves around pollution analysis, cleaning implementation and effect verification, forming a scientific and efficient cleaning process. The advantage of this method is the formulation and precise execution of cleaning strategies based on pollution characteristics, which not only improves cleaning efficiency, but also reduces the risk of surface damage to the fixture, ensures the full recovery of fixture performance, and provides reliable protection for the long-term stable operation of the USB interface.

[0185] Another embodiment of the present application also provides a USB pressing fixture, which adopts the test method of the USB pressing fixture provided in the above embodiment, and ensures the efficient execution of the test method and the comprehensive optimization of the fixture performance by combining the specific structural design and functional implementation. Figure 2 A USB pressing fixture provided in another embodiment of the present application is described.

[0186] Figure 2 This is a structural diagram of the fixture body of the USB pressing fixture, showing its core components and working principles. The fixture body includes an air pressure regulating air filter 1, a solenoid valve (not shown), a cylinder 2, an upper mold 3 and a lower mold 4. The function of the air pressure regulating air filter 1 is to regulate and filter the compressed air input from the outside, remove impurities and moisture in the air, and ensure that the air quality entering the fixture meets the working requirements. The processed compressed air is transported to the solenoid valve switch through the air path, and the opening and closing of the solenoid valve is precisely controlled by the programmable logic controller (PLC) in the display panel.

[0187] PLC is the core control unit of the fixture, which can control the action of the solenoid valve coil through pulse signals. When the PLC sends a pulse signal to the solenoid valve coil, the piston inside the solenoid valve will move left and right in response to the signal, thereby switching the on and off state of the air circuit. By switching the air circuit, the up and down action control of the cylinder 2 can be achieved. When the cylinder 2 is in motion, it pushes the connected upper mold 3 to move downward along the guide rail, and cooperates with the lower mold 4 to complete the pressing process of the USB connector. The matching accuracy of the upper mold 3 and the lower mold 4 directly affects the pressing effect, so their surfaces are processed with high precision to ensure the flatness and stability of the contact surface.

[0188] The functional design of the fixture supports multiple operation modes. The current PLC system is an editable structure and can be set to manual, semi-automatic or fully automatic mode according to needs. For example, in manual mode, the operator can directly control the action of cylinder 2 through a button or foot valve; in semi-automatic mode, the fixture can automatically complete some actions according to the preset operating procedures; and in fully automatic mode, the PLC controls the operation of the fixture throughout the process according to the pre-programmed logic, which is suitable for high-efficiency production scenarios. In addition, the fixture also supports the setting of the holding time and the counting of the number of pressings. The PLC can flexibly adjust the holding time to adapt to different pressing requirements, and record the cumulative number of pressings of the fixture at the same time, providing a data basis for subsequent maintenance and inspection.

[0189] In terms of the operational safety of the fixture, a two-hand start and foot-operated valve control mechanism are designed. The two-hand start requires the operator to press two start buttons at the same time to activate the fixture action, avoiding the safety risks caused by one-handed accidental triggering; the foot-operated valve control provides a convenient operation option in specific scenarios, such as when quick start or release of compression is required.

[0190] It is worth noting that the USB pressing fixture in this embodiment should be understood in a broad sense. In specific implementation, it may include the parts mentioned in the first embodiment "Testing method of USB pressing fixture". Since the parts involved in this application are all widely used parts, the working principles of these parts will not be described one by one here.

[0191] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for testing a USB pressing fixture, characterized in that: include: Obtain the operation data of the pressing fixture; Performing preliminary inspection on a predetermined area of ​​the pressing jig according to the operation data to obtain preliminary inspection data; The method comprises: performing a preliminary detection on a predetermined area of ​​the pressing fixture according to the operation data to obtain preliminary detection data, including: analyzing the cumulative pressing times in the operation data, and triggering preliminary detection when the cumulative pressing times reaches a preset threshold; calculating a pressing force deviation value according to pressing force curve data in the operation data; determining an environmental impact coefficient based on working environment parameters in the operation data; calculating an electrical performance attenuation index using electrical connection parameters in the operation data; generating a heat map of a predetermined area of ​​the pressing fixture by combining the pressing force deviation value, the environmental impact coefficient and the electrical performance attenuation index; performing threshold segmentation on the heat map to identify potential abnormal areas; performing resistance scanning on the potential abnormal areas to obtain resistance distribution data; performing micro-spectral imaging on the potential abnormal areas to obtain surface reflection spectrum data; and performing data fusion on the resistance distribution data and the surface reflection spectrum data to generate preliminary detection data. Determine a target detection area according to the preliminary detection data; Performing laser induced breakdown spectroscopy scanning on the target detection area to obtain spectral data; fusing the preliminary detection data and the spectral data to obtain pollution characteristic data; Perform time series analysis based on the pollution characteristic data and historical pollution data to obtain pollution trend data; Performing a multi-physics field coupling analysis on the USB interface performance based on the pollution characteristic data and the pollution trend data to obtain a performance impact assessment result; A differentiated cleaning strategy is developed and implemented based on the performance impact assessment results to clean the pressing fixture.

2. The USB pressing fixture testing method according to claim 1, characterized in that: The step of obtaining the operation data of the pressing fixture includes: Record the cumulative number of pressing times of the pressing fixture; Collect pressing force curve data during each pressing process; Acquire working environment parameters of the pressing fixture, wherein the working environment parameters include ambient temperature and humidity; Detecting electrical connection parameters of the pressing fixture, wherein the electrical connection parameters include contact resistance and signal integrity index; The accumulated pressing times, pressing force curve data, working environment parameters and electrical connection parameters are integrated into operation data of the pressing fixture.

3. The USB pressing fixture testing method according to claim 1, characterized in that: The determining of the target detection area according to the preliminary detection data includes: Analyzing the resistance distribution and surface reflection spectrum data in the preliminary detection data, identifying areas with abnormal resistance and abnormal surface reflection, and marking these areas as potential contaminated areas; Perform spatial overlay analysis on the potential contamination area, the signal transmission path and the power supply point of the USB interface to determine the key overlapping area that affects USB performance; According to the location and range of the critical overlapping area and the functional importance of the USB interface, the contamination risk coefficient of each area is calculated; Areas where the pollution risk factor exceeds the preset threshold are selected as target detection areas.

4. The method for testing a USB pressing fixture according to claim 1, wherein: The laser induced breakdown spectroscopy scanning of the target detection area to obtain spectral data includes: Performing three-dimensional surface modeling on the target detection area to generate a scanning path adapted to the groove structure of the pressing fixture mold; According to the scanning path, dynamically adjust the laser focus to ensure that the laser pulse is perpendicular to the mold surface; Double-pulse laser-induced breakdown is performed at each scanning point, the first pulse is used to clean the microscopic contaminants on the mold surface, and the second pulse is used to excite the mold surface material to form plasma; Adjust the laser energy density in real time to adapt to the different curvatures and material properties of the mold surface; Collect the plasma emission spectrum at each scanning point to obtain original spectrum data; According to the depth distribution of the mold groove, the original spectrum data is depth corrected to obtain corrected spectrum data; The corrected spectral data of all scanning points are integrated to obtain spectral data, which represents the spectral distribution of the target detection area in the form of a three-dimensional matrix.

5. The USB pressing fixture testing method according to claim 1, characterized in that: The fusing of the preliminary detection data and the spectral data to obtain pollution characteristic data includes: Performing spatial registration on the resistance distribution data in the preliminary detection data and the spectrum data to establish a resistance-spectrum correspondence relationship; Using a preset data fusion algorithm, the surface reflectance spectrum data in the preliminary detection data is fused with the spectrum data at a feature level; Based on the fused data, the principal component analysis method is used to extract pollutant characteristics and determine the pollutant type and concentration distribution; Calculate the influence coefficient of the pollutant on the contact resistance of the USB interface by combining the resistance distribution data, the type and concentration distribution of the pollutant; The pollutant type, concentration distribution and contact resistance influence coefficient are comprehensively considered to generate multi-dimensional pollution characteristic data.

6. The method for testing a USB pressing fixture according to claim 1, characterized in that: The time series analysis is performed based on the pollution characteristic data and the historical pollution data to obtain the pollution trend data, including: Performing time alignment and data standardization on the pollution characteristic data and historical pollution data to obtain standardized time series data; Using wavelet transform to perform multi-scale decomposition on the standardized time series data to obtain pollution characteristic components at different time scales; Applying an autoregressive integrated moving average model to the pollution characteristic components of different time scales to obtain pollution trend prediction results at each scale; Performing scale reconstruction according to the pollution trend prediction results at each scale to obtain comprehensive pollution trend prediction data; Combined with the working cycle characteristics of the USB interface, the comprehensive pollution trend prediction data is periodically analyzed to obtain pollution trend data that takes periodic effects into account.

7. The USB pressing fixture testing method according to claim 1, characterized in that: The multi-physical field coupling analysis of the USB interface performance based on the pollution characteristic data and the pollution trend data is performed to obtain a performance impact assessment result, including: Calculating the time-varying contact resistance of key contact points of the USB interface according to the pollution characteristic data and the pollution trend data; Utilizing the time-varying contact resistance, analyzing the current distribution change and local heating of the USB interface; Based on the current distribution change and local heating conditions, the temperature field and stress field inside the USB interface are calculated; According to the temperature field and the stress field, the signal transmission performance, the power transmission efficiency and the mechanical stability of the USB interface are evaluated; By integrating the evaluation results of the signal transmission performance, power transmission efficiency and mechanical stability, a multi-dimensional score of the USB interface performance changing over time is generated to obtain a performance impact evaluation result.

8. The method for testing a USB pressing fixture according to claim 1, characterized in that: The method comprises formulating and executing a differentiated cleaning strategy based on the performance impact assessment results to clean the pressing jig, including: According to the performance impact assessment results, determine the serious contamination areas and contamination types on the pressing jig; According to the seriously polluted area and pollution type, a matching cleaning method combination is selected from a preset cleaning method library; Based on the combination of cleaning methods, generating a differentiated cleaning strategy including a cleaning sequence, a cleaning intensity, and a cleaning time; Performing zone-by-zone cleaning on the pressing jig according to the differentiated cleaning strategy; Rapidly test the pressed jig after cleaning to obtain cleaning effect data; According to the cleaning effect data, it is determined whether the preset cleaning standard is reached. If not, the process returns to the step of executing the differentiated cleaning strategy until the preset cleaning standard is reached.

9. A USB pressing fixture, characterized in that: The USB pressing jig adopts the testing method of the USB pressing jig as described in any one of claims 1 to 8.

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