Method and system for predicting service life of electric connector

Abstract

The invention relates to the technical field of electric signal processing, in particular to an electric connector service life prediction method and system. The method comprises the following steps: continuously monitoring the electrical properties of the contact element of the electric connector, and recording the change of a contact resistance value as an abnormal initial site when the change of the contact resistance value is detected; acquiring a surface image of the electric connector according to the abnormal initial site; contact surface abrasion and scratches of the surface image of the electric connector are detected, and connector defects of the contact surface are recognized and marked as a connector structure defect area; carrying out area overall physical hardness detection on the defect area of the connector structure to obtain the overall hardness amount of the connector area; and carrying out hardness sudden change part identification on the overall hardness amount of the connector region, and recording as a connector hardness abnormal region. According to the invention, through an electric signal processing technology and an image identification technology, comprehensive evaluation of the performance of the electric connector is realized, so that the accuracy of predicting the service life of the electric connector is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical signal processing, and particularly relates to a method and system for predicting the life of an electrical connector. Background Art

[0002] An electrical connector is an electronic component used to achieve electrical connection, and is widely used in fields such as electronic devices, communication systems, automobiles, aerospace, etc.; the contact of the electrical connector is the core component of the electrical connector for achieving electrical connection; the housing of the electrical connector is used to protect the internal contacts and insulators, providing mechanical protection and environmental sealing. The life prediction of electrical connectors usually ignores the change of material properties. On the one hand, it is specifically manifested that the decrease of material hardness will lead to the decline of the mechanical properties of the contacts, thus affecting the reliability of the electrical connector; however, in the prior art, there is a lack of means for real-time monitoring and evaluation of material hardness, and it is impossible to accurately judge whether the material properties have changed abnormally. On the other hand, the life prediction of electrical connectors often ignores the influence of the housing structure tightness on the life. Insufficient housing tightness will cause external environmental factors (such as moisture, dust, etc.) to enter the inside of the electrical connector, accelerating its aging and failure; however, in the prior art, there is a lack of means for detecting and evaluating the housing tightness, resulting in the inability to comprehensively evaluate the health status of the electrical connector. Summary of the Invention

[0003] Based on this, it is necessary to provide a method and system for predicting the life of an electrical connector to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for predicting the life of an electrical connector, the method includes the following steps:

[0005] Step S1: Continuously monitor the electrical performance of the contacts of the electrical connector, and when it is detected that the contact resistance value changes, record it as the abnormal initial site;

[0006] Step S2: Collect the surface image of the electrical connector according to the abnormal initial site; detect the wear and scratches on the contact surface of the surface image of the electrical connector, identify the connector defects on the contact surface, and mark them as the connector structure defect areas;

[0007] Step S3: Perform regional overall physical hardness detection on the connector structure defect areas to obtain the overall hardness of the connector area; identify the hardness mutation parts of the overall hardness of the connector area and record them as the connector hardness abnormal areas; perform electrical connector material deformation detection on the connector hardness abnormal areas to generate the connector material deformation degree value;

[0008] Step S4: Determine the corresponding electrical connector housing according to the connector structure defect areas; perform housing structure sealing detection on the electrical connector housing to generate the housing structure sealing degree value;

[0009] Step S5: Perform electrical connector performance evaluation based on the deformation degree value of the connector material and the sealing degree value of the housing structure to obtain electrical connector performance data; predict the life of the electrical connector through the electrical connector performance data to generate an electrical connector life prediction report.

[0010] The present invention continuously monitors the electrical performance of the electrical connector contacts. Once the contact resistance value changes, it is immediately recorded as the abnormal initial site. This real-time monitoring and precise recording method ensure the timely capture of changes in the performance of the electrical connector, avoiding the missed key abnormal information due to monitoring delay, laying a solid foundation for subsequent detection and evaluation, effectively improving the accuracy and reliability of the performance monitoring of the electrical connector, and enabling subsequent detection and evaluation to be carried out based on accurate initial data. According to the abnormal initial site, the surface image of the electrical connector is collected, and the wear and scratches on the contact surface in the image are detected to identify the connector defects on the contact surface and mark them as the connector structure defect areas. This step realizes the comprehensive detection and precise identification of the surface defects of the electrical connector through image acquisition and analysis technology. It can not only detect tiny defects that are difficult to detect by the naked eye, but also accurately locate and mark the defects, providing a clear regional guidance for subsequent targeted detection and evaluation, greatly improving the efficiency and accuracy of the electrical connector defect detection, and helping to timely discover potential performance hazards. The physical hardness of the connector structure defect area is detected to obtain the connector hardness value and compared with the preset hardness value to judge the connector hardness abnormal area; then the electrical connector material deformation detection is carried out on the hardness abnormal area to generate the connector material deformation degree value. This in-depth detection process analyzes the structural performance of the electrical connector from two key dimensions of physical hardness and material deformation. Through the comparison with the standard hardness value and the quantitative evaluation of the deformation degree, it can accurately identify the performance weak links caused by insufficient hardness or material deformation, providing more comprehensive and accurate quantitative data for subsequent performance evaluation, significantly enhancing the accuracy and reliability of the electrical connector performance evaluation, and making the evaluation results more scientific and persuasive. According to the connector structure defect area, the corresponding electrical connector housing is determined, and the housing structure seal detection is carried out on the housing to generate the housing structure seal degree value. This step incorporates the sealing performance of the electrical connector housing into the evaluation scope, quantifies the housing structure seal degree through scientific detection means, and further improves the electrical connector performance evaluation system. As an important factor affecting the performance and life of the electrical connector, the detection result of the housing sealing performance can provide a key basis for evaluating the reliability of the electrical connector in a complex environment, ensuring the comprehensiveness and integrity of the performance evaluation, and helping to more accurately predict the performance and service life of the electrical connector in actual applications. Based on the connector material deformation degree value and the housing structure seal degree value, the electrical connector performance evaluation is carried out to obtain the electrical connector performance data, and based on this, the electrical connector life is predicted to generate the electrical connector life prediction report. This step comprehensively uses the key data obtained in the previous steps to realize the comprehensive evaluation of the electrical connector performance and the precise prediction of the life. The generated life prediction report can provide accurate and reliable data support for the use, maintenance and replacement of the electrical connector, helping users to formulate reasonable maintenance plans and replacement strategies in advance, and reducing the equipment downtime risk caused by electrical connector failures.

[0011] Preferably, step S1 includes the following steps:

[0012] Step S11: Monitor and partition the electrical connector contacts. Starting from the starting end of the electrical connector contacts, the first 1 / 3 part of the total length of the contacts is marked as the front-end monitoring area; the part from 1 / 3 to 2 / 3 of the total length of the contacts is marked as the middle-end monitoring area; the part from 2 / 3 of the total length of the contacts to the end is marked as the back-end monitoring area;

[0013] Step S12: Collect the contact resistance values in sequence at set time intervals in the front-end monitoring area, middle-end monitoring area, and back-end monitoring area. Among them, the set time interval is set to pause for 1 minute after the first collection, pause for 2 minutes after the second collection, pause for 3 minutes after the third collection, and the pause time increases by 1 minute each time compared to the previous one;

[0014] Step S13: Process the collected contact resistance values, calculate the average value in three consecutive collections for each monitoring area, and obtain the change trend of the average regional resistance;

[0015] Step S14: Determine the slope of the resistance change trend based on the change trend of the average regional resistance. If the slope of the resistance change trend is greater than the preset slope of the resistance change trend, it is determined that there is a mutation in the contact resistance value;

[0016] Step S15: When there is a mutation in the contact resistance value, map the monitoring area of the electrical connector contacts and record this monitoring area as the abnormal initial site.

[0017] By dividing the electrical connector contacts into three monitoring areas: front-end, middle-end, and back-end, and collecting the contact resistance values in sequence at specific time intervals, calculating the change trend of the average resistance of each area and the slope of the resistance change trend, the present invention can accurately locate the area where the contact resistance value mutates and record it as the abnormal initial site. This method of zonal monitoring and dynamic time interval collection realizes the refined monitoring of the resistance changes in different parts of the electrical connector contacts, can timely and accurately capture the resistance mutation situation, provides more accurate and reliable initial data for the subsequent performance evaluation and life prediction of the electrical connector, effectively improves the accuracy and reliability of the electrical connector life prediction, ensures the performance stability and reliability of the electrical connector in practical applications, reduces the failure risk caused by abnormal contact resistance, and has important practical application value for ensuring the safe operation of the electrical connector and related equipment.

[0018] Preferably, collecting the surface image of the electrical connector according to the abnormal initial site in step S2 includes:

[0019] According to the abnormal initial site, use a high-resolution industrial camera to collect images of the surface of the electrical connector, and the resolution of the camera is not less than 1024×768 pixels;

[0020] Place the electrical connector on a fixed bracket so that the surface of the electrical connector is perpendicular to the camera lens, and the distance between the camera and the surface of the electrical connector is maintained between 10 cm and 20 cm;

[0021] Perform grayscale processing on the collected surface image to convert the color image into a grayscale image; perform median filtering on the grayscale image with a window size of 3×3 pixels; perform edge enhancement on the filtered image to obtain the surface image of the electrical connector.

[0022] In the method for predicting the life of the electrical connector of the present invention, according to the abnormal initial site, a high-resolution industrial camera with a resolution of not less than 1024×768 pixels is used to collect images of the surface of the electrical connector to ensure the clarity and detail presentation of the images. The electrical connector is placed on a fixed bracket so that the surface of the electrical connector is perpendicular to the camera lens, and the distance between the camera and the surface of the electrical connector is controlled between 10 cm and 20 cm. This precise acquisition setting can ensure that the collected images have a uniform and high-quality imaging effect, providing a reliable basis for subsequent image processing. Perform grayscale processing on the collected surface image to convert the color image into a grayscale image, which simplifies the image data and reduces the computational amount of subsequent processing. Perform median filtering on the grayscale image with a window size of 3×3 pixels to effectively remove noise interference in the image while retaining the edge information of the image. Perform edge enhancement on the filtered image to further highlight the detail features on the surface of the electrical connector, making defects such as wear and scratches on the surface of the electrical connector more clearly visible, providing a high-quality image basis for subsequent defect recognition and marking of the structural defect area, thereby improving the accuracy and reliability of the detection of surface defects of the electrical connector, providing more accurate structural defect data support for predicting the life of the electrical connector, and helping to achieve refined evaluation of the performance of the electrical connector and accurate prediction of its life.

[0023] Preferably, in step S2, detecting wear and scratches on the contact surface of the surface image of the electrical connector, identifying connector defects on the contact surface, and marking them as connector structural defect areas includes:

[0024] Divide the surface image of the electrical connector into multiple equal-area image detection regions; within each image detection region, calculate the change gradient of the grayscale value to identify the boundary of the wear region on the contact surface; count the area of the wear region on the contact surface within each image detection region to calculate the total wear area on the contact surface;

[0025] Identify the linear features of the image within each image detection region and mark them as scratches; measure the length and width of each scratch, and count the total number of scratches on the contact surface within each image detection region;

[0026] Analyze the positional relationship between the worn area of the contact surface and the scratches. If a scratch passes through the worn area and the length of the scratch exceeds 1 mm, mark this image detection region as a potential connector structure defect region;

[0027] Within the potential connector structure defect region, if the total worn area of the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5, then mark the potential connector structure defect region as a connector structure defect region.

[0028] Through the refined processing and analysis of the surface image of the electrical connector, the present invention realizes the accurate identification and quantitative evaluation of the worn area and scratches on the contact surface. First, the surface image of the electrical connector is divided into multiple image detection regions with equal areas to ensure the uniformity and comprehensiveness of the analysis. Within each image detection region, calculate the change gradient of the gray value to identify the boundary of the worn area on the contact surface, and count the area of the worn region to calculate the total worn area of the contact surface, so as to quantitatively evaluate the degree of wear. At the same time, identify the linear features of the image and mark them as scratches, measure the length and width of each scratch, and count the total number of scratches to achieve the accurate quantification of the scratches. By analyzing the positional relationship between the worn area of the contact surface and the scratches, combined with quantitative indicators such as scratch length and wear area, accurately mark the potential connector structure defect region and the final connector structure defect region. This quantitative evaluation method based on image analysis can accurately identify and locate the wear and scratch defects on the surface of the electrical connector, provide detailed and accurate structure defect data for subsequent performance evaluation and life prediction, effectively improve the accuracy and reliability of the defect detection of the electrical connector, and contribute to the refined evaluation of the performance of the electrical connector and the accurate prediction of its life.

[0029] Preferably, the regional overall physical hardness detection of the connector structure defect region in step S3 includes:

[0030] Within the connector structure defect region, select multiple hardness detection points at equal intervals of 1 mm and arrange the hardness detection points in a grid pattern;

[0031] At each hardness detection point, contact the surface of the electrical connector with the probe of the hardness detection device and record the hardness value after the probe applies pressure;

[0032] Conduct three hardness detections at each hardness detection point, with an interval of 10 seconds between each detection;

[0033] Take the average value of the three detection results as the connector hardness value of this hardness detection point;

[0034] Record the hardness of the connector at each hardness detection point in a data table, and mark the coordinate position of the detection point.

[0035] In the present invention, a grid-like layout of hardness detection points with an equal spacing of 1 mm is adopted within the structural defect area of the connector, ensuring the comprehensiveness and uniformity of hardness detection. At each hardness detection point, the probe of the hardness detection device contacts the surface of the electrical connector and records the hardness value after applying pressure. By performing three detections and taking the average value, the accidental error of a single detection is effectively reduced, and the accuracy of hardness detection is improved. Recording the hardness of the connector at each hardness detection point and its coordinate position in a data table provides detailed and accurate information for subsequent hardness data analysis and comparison, facilitating the identification of abnormal hardness areas and targeted material deformation detection, thereby providing reliable data support for the performance evaluation and life prediction of electrical connectors, and ensuring the scientificity and accuracy of the evaluation results.

[0036] Preferably, in step S3, the detection of the material deformation of the electrical connector in the area with abnormal hardness of the connector includes:

[0037] In the area with abnormal hardness of the connector, by applying tensile force and compressive force on the surface of the electrical connector, record the strain distribution on the material surface to obtain surface strain distribution data;

[0038] According to the surface strain distribution data, identify the strain concentration area. In the strain concentration area, select multiple material deformation detection points, and the spacing of each material deformation detection point is set to 0.5 mm;

[0039] Perform material deformation detection on each material deformation detection point, measure the displacement offset of the surface of the electrical connector material under the application of tensile force and compressive force; determine the material deformation degree value of the connector according to the displacement offset.

[0040] In the present invention, in the area with abnormal hardness of the connector, by applying tensile force and compressive force, record the strain distribution on the material surface to obtain surface strain distribution data, and then identify the strain concentration area. In this area, multiple material deformation detection points are set at an interval of 0.5 mm. Perform material deformation detection on each detection point, measure the displacement offset of the surface of the electrical connector material under stress, and determine the material deformation degree value of the connector accordingly. This deformation detection method based on strain distribution can accurately locate and quantify the deformation of the electrical connector material, provide key data for evaluating the structural stability of the connector under stress, help predict the performance change and service life of the electrical connector more accurately, and ensure its reliability in practical applications.

[0041] Preferably, step S4 includes the following steps:

[0042] Step S41: Determine the central coordinates of the connector structure defect area, convert them into the actual physical coordinates of the electrical connector housing, and determine the corresponding electrical connector housing according to the actual physical coordinates;

[0043] Step S42: Place the electrical connector housing on the test platform of the airtight detector and balance the air pressure inside the housing with the external ambient air pressure;

[0044] Step S43: Apply a constant and small air pressure of 0.1 Pa inside the electrical connector housing for a duration of 30 seconds;

[0045] Step S44: After applying the air pressure, monitor the change of the air pressure inside the housing, record the data in the air pressure rising, stable and falling stages to generate an air pressure change curve;

[0046] Step S45: Calculate the air pressure change rate of the housing according to the air pressure change curve, determine the housing structure seal based on the housing air pressure change rate, and generate a housing structure seal degree value.

[0047] Through accurately determining the central coordinates of the connector structure defect area and converting them into the actual physical coordinates of the electrical connector housing, the present invention accurately locks the corresponding electrical connector housing. After placing the housing on the test platform of the airtight detector and balancing the internal and external air pressures, a constant and small air pressure (0.1 Pa) is applied for 30 seconds, and the whole process of the change of the air pressure inside the housing is monitored and recorded to generate an air pressure change curve. Based on the air pressure change curve, the air pressure change rate of the housing is calculated, and then the housing structure seal degree is determined and a quantitative value is generated. This series of steps realizes the accurate evaluation of the sealing performance of the electrical connector housing, provides key data support for the comprehensive evaluation of the overall performance of the electrical connector, ensures the sealing reliability of the electrical connector in a complex environment, and has important significance for extending the service life of the electrical connector and ensuring the stable operation of the equipment.

[0048] Preferably, the performance evaluation of the electrical connector based on the connector material deformation degree value and the housing structure seal degree value in step S5 includes:

[0049] Divide the material deformation degree value by the preset maximum deformation degree value to obtain a material deformation ratio, and subtract this material deformation ratio from 1 to obtain a material deformation influence factor;

[0050] Divide the housing structure seal degree value by the preset maximum seal degree value to obtain a housing seal influence factor;

[0051] Multiply the material deformation influence factor by 0.6, multiply the housing seal influence factor by 0.4, and add the two results to generate an electrical connector performance determination value;

[0052] Divide the performance value range for the electrical connector performance determination value, and determine the electrical connector performance data according to the performance value range.

[0053] In the present invention, by comparing and calculating the material deformation degree value with a preset maximum deformation degree value, a material deformation ratio is obtained, and further a material deformation influence factor is obtained. At the same time, the shell structure sealing degree value is compared and calculated with a preset maximum sealing degree value to obtain a shell sealing influence factor. According to the set weights (the weight of the material deformation influence factor is 0.6, and the weight of the shell sealing influence factor is 0.4), the two influence factors are weighted and summed to generate an electrical connector performance determination value. By dividing the performance value range, the electrical connector performance data is determined based on the electrical connector performance determination value. This process realizes the quantitative evaluation of the electrical connector performance, comprehensively considers the two key factors of material deformation and shell sealing, and through scientific weight allocation and quantitative calculation, obtains a determination value that can accurately reflect the overall performance of the electrical connector, providing an accurate and objective data basis for the performance evaluation and life prediction of the electrical connector, and ensuring the scientificity and reliability of the evaluation results.

[0054] Preferably, predicting the electrical connector life through the electrical connector performance data in step S5 includes:

[0055] Divide the electrical connector performance interval according to the electrical connector performance data. If the electrical connector performance data is greater than or equal to 0.8, it is determined as a high-performance interval; if the electrical connector performance data is between 0.5 and 0.8, it is determined as a medium-performance interval; if the electrical connector performance data is less than 0.5, it is determined as a low-performance interval;

[0056] For the high-performance interval, predict that the remaining percentage of the electrical connector life in this area is 80%; for the medium-performance interval, predict that the remaining percentage of the electrical connector life in this area is 50%; for the low-performance interval, predict that the remaining percentage of the electrical connector life in this area is 20%;

[0057] Draw an electrical connector life prediction distribution map in the corresponding area of the electrical connector, and output an electrical connector life prediction report.

[0058] The present invention divides the performance range according to the performance data of the electrical connector, and clarifies the remaining percentage of the electrical connector life corresponding to different performance ranges: the high-performance range (performance data ≥ 0.8) corresponds to the remaining percentage of life of 80%, the medium-performance range (performance data between 0.5 and 0.8) corresponds to the remaining percentage of life of 50%, and the low-performance range (performance data < 0.5) corresponds to the remaining percentage of life of 20%. Through this quantitative division and corresponding relationship, the life of the electrical connector can be predicted quickly and accurately. Further, a life prediction distribution map is drawn in the corresponding area of the electrical connector, and a life prediction report is output, providing intuitive and clear guidance for the use and maintenance of the electrical connector. This life prediction method based on performance data, combined with the visual distribution map and detailed report, makes the life assessment of the electrical connector more scientific, accurate and easy to understand, helps users timely grasp the performance status of the electrical connector, reasonably arrange the maintenance and replacement plan, thereby improving the use efficiency and reliability of the electrical connector, and reducing the risks and costs caused by electrical connector failures.

[0059] This specification also provides an electrical connector life prediction system for performing the electrical connector life prediction method as described above. The electrical connector life prediction system includes:

[0060] An electrical performance monitoring module for continuously monitoring the electrical performance of the electrical connector contacts, and when a change in the contact resistance value is detected, recording it as an abnormal initial site;

[0061] A surface image acquisition and recognition module for acquiring the surface image of the electrical connector according to the abnormal initial site; detecting the wear and scratches on the contact surface of the electrical connector surface image, identifying the connector defects on the contact surface, and marking them as connector structure defect areas;

[0062] A hardness and deformation detection module for performing a regional overall physical hardness detection on the connector structure defect area to obtain the overall hardness of the connector area; identifying the hardness mutation sites for the overall hardness of the connector area and recording them as connector hardness abnormal areas; performing electrical connector material deformation detection on the connector hardness abnormal areas to generate a connector material deformation degree value;

[0063] A housing structure seal detection module for determining the corresponding electrical connector housing according to the connector structure defect area; performing a housing structure seal detection on the electrical connector housing to generate a housing structure seal degree value;

[0064] An electrical connector life prediction module for performing electrical connector performance evaluation based on the connector material deformation degree value and the housing structure seal degree value to obtain electrical connector performance data; predicting the life of the electrical connector through the electrical connector performance data to generate an electrical connector life prediction report.

[0065] The electrical connector life prediction system of the present invention realizes a comprehensive evaluation and accurate prediction of the performance and life of electrical connectors through the collaborative work of five modules. The electrical performance monitoring module can monitor the change of contact resistance in real time and record the abnormal initial sites, providing an accurate starting point for subsequent detection; the surface image acquisition and recognition module acquires images based on the abnormal initial sites and recognizes the structural defect areas, accurately locating surface wear and scratches; the hardness and deformation detection module performs hardness and deformation detection on the defect areas to quantify the change of material properties; the housing structure sealing detection module performs sealing detection on the corresponding housing to evaluate the integrity of the housing; the electrical connector life prediction module comprehensively evaluates the performance by combining the material deformation degree value and the housing structure sealing degree value, predicts the life and generates a report. Through the orderly cooperation of each module, the whole system realizes the full-process automation and accuracy from electrical performance monitoring to life prediction, provides a scientific basis for the maintenance and replacement of electrical connectors, effectively improves the use efficiency and reliability of electrical connectors, and reduces the risk of equipment failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 FIG. is a schematic flow chart of the steps of a method for predicting the life of an electrical connector;

[0067] Figure 2 is Figure 1 a detailed implementation step flow chart of step S4 in;

[0068] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0069] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0070] In addition, the drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0071] It should be understood that although terms such as "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly, the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0072] To achieve the above object, please refer to Figures 1 to 2 , a method for predicting the life of an electrical connector, the method comprising the following steps:

[0073] Step S1: Continuously monitor the electrical performance of the electrical connector contacts. When a change in the contact resistance value is detected, it is recorded as an abnormal initial site;

[0074] Step S2: Acquire the surface image of the electrical connector according to the abnormal initial site; detect the wear and scratches on the contact surface of the electrical connector surface image, identify the connector defects on the contact surface, and mark them as the connector structure defect area;

[0075] Step S3: Perform overall physical hardness detection on the connector structure defect area to obtain the overall hardness of the connector area; identify the hardness mutation sites of the overall hardness of the connector area and record them as the connector hardness abnormal area; perform electrical connector material deformation detection on the connector hardness abnormal area to generate the connector material deformation degree value;

[0076] Step S4: Determine the corresponding electrical connector housing according to the connector structure defect area; perform housing structure sealing detection on the electrical connector housing to generate the housing structure sealing degree value;

[0077] Step S5: Perform electrical connector performance evaluation based on the connector material deformation degree value and the housing structure sealing degree value to obtain the electrical connector performance data; predict the life of the electrical connector through the electrical connector performance data to generate an electrical connector life prediction report.

[0078] In the embodiment of the present invention, referring to Figure 1 as shown, it is a schematic flow chart of the steps of a method for predicting the life of an electrical connector according to the present invention. In this example, the method for predicting the life of the electrical connector includes the following steps:

[0079] Step S1: Continuously monitor the electrical performance of the electrical connector contacts. When a change in the contact resistance value is detected, it is recorded as an abnormal initial site;

[0080] In the embodiments of the present invention, a high-precision four-wire resistance measurement technology is adopted to continuously monitor the electrical performance of the contact components of the electrical connector. Specifically, by connecting two wires to both ends of the contact component as current introduction wires, and the other two wires as voltage measurement wires, the contact resistance value is accurately measured. The monitoring system uses a high-precision digital multimeter with a measurement accuracy reaching the micro-ohm level to collect the contact resistance value in real time with a sampling period of 1 second. When it is monitored that the change in the contact resistance value exceeds the set threshold of 0.1 micro-ohm compared with the initially set reference resistance value, the system automatically records the measurement point at this time as the abnormal initial site, and at the same time records the detailed information of this site, including but not limited to parameters such as the measurement time, the specific number of the contact component, and the ambient temperature.

[0081] Step S2: Collect the surface image of the electrical connector according to the abnormal initial site; detect the wear and scratches on the contact surface of the surface image of the electrical connector, identify the connector defects on the contact surface, and mark them as the connector structure defect areas;

[0082] In the embodiments of the present invention, based on the abnormal initial sites recorded in step S1, a high-resolution industrial camera is activated to collect images of the surface of the electrical connector. The industrial camera uses a line-scan method to ensure high resolution and high clarity of the images. The light source of the camera is a uniform annular LED light source, and the adjustable range of its light intensity is 10% to 100%. Before collecting the images, the light intensity is adjusted to 50% to ensure moderate and uniform brightness of the images. The shooting resolution of the camera is set to 2048×2048 pixels to ensure that minute details on the surface of the electrical connector can be captured. The collected image data is transmitted to the image processing unit in the form of digital signals. In the image processing unit, first, preprocessing of the images is performed, including adjusting the brightness and contrast of the images. By adjusting the brightness value of the images, the average brightness is made to reach 128 (within the gray scale range of 0 to 255), and at the same time, the contrast is adjusted to 1.5 times to enhance the differentiation between different regions in the images. Then, noise reduction processing is performed on the images. A 3×3 median filter is used to process each pixel point in the images to remove the existing random noise and ensure the clarity and accuracy of the images. After the image preprocessing is completed, a detailed analysis of the surface image of the electrical connector is carried out. With the assistance of an optical microscope for observation, the image is magnified to 100 times, and each point on the contact area of the surface of the electrical connector is inspected. During the inspection process, a high-precision image analysis tool is used to analyze the gray scale value of each pixel point in the image. For the worn area on the contact surface, its gray scale value is usually lower than that of the surrounding normal area. When it is detected that the gray scale value of a certain area is lower than the set threshold of 100, it is marked as a potential worn area. For scratches, they appear as slender lines with a gray scale value significantly higher than that of the surrounding area in the image. When a continuous line with a gray scale value exceeding 180 is detected, it is marked as a scratch area. After identifying the worn and scratched areas, a further detailed inspection of these areas is carried out to determine whether there are structural defects in the connector. By comparing with the standard surface image of the electrical connector, a comparative analysis of the size and shape of each marked area is performed. For the worn area, if its area exceeds 0.5 square millimeters, or its shape is irregular and the edges are blurred, it is marked as a structural defect area of the connector. For scratches, if its length exceeds 2 millimeters, or its width exceeds 0.1 millimeters, it is also marked as a structural defect area of the connector. During the marking process, a red rectangular box is used to mark each defect area, and detailed information such as the center coordinates, length, width, and defect type of each defect area is recorded.

[0083] Step S3: Perform overall physical hardness detection on the structural defect area of the connector to obtain the overall hardness of the connector area; identify the parts with hardness mutations in the overall hardness of the connector area and record them as the areas with abnormal hardness of the connector; perform deformation detection of the electrical connector material on the areas with abnormal hardness of the connector to generate the deformation degree value of the electrical connector material;

[0084] In an embodiment of the present invention, during the implementation of step S3, first, overall physical hardness detection is performed on the structural defect area of the electrical connector. A high-precision hardness detection device is used, which is equipped with a probe with adjustable pressure and can accurately measure the hardness value on the surface of the electrical connector. The electrical connector is placed on a fixed bracket to ensure that its surface is flat and stable. The probe of the hardness detection device contacts the surface of the electrical connector, and the applied pressure is set to 10 N to ensure the accuracy of the measurement results. In the structural defect area of the connector, multiple hardness detection points are selected at equal intervals of 1 mm, and the hardness detection points are arranged in a grid pattern to ensure that the entire defect area is covered. At each hardness detection point, the probe of the hardness detection device contacts the surface of the electrical connector, and the hardness value after the probe applies pressure is recorded. To ensure the reliability of the measurement results, three hardness detections are performed at each hardness detection point, and the interval time between each detection is 10 seconds. The average value of the three detection results is taken as the connector hardness value of this hardness detection point, and the connector hardness value of each hardness detection point is recorded in a data table, and the coordinate position of the detection point is marked at the same time. Subsequently, identification of the hardness mutation part is performed on the overall hardness value of the connector area. By analyzing the recorded hardness data, the hardness difference between adjacent hardness detection points is calculated. A hardness difference threshold is set to 1.0 HV (Vickers hardness unit). When the hardness difference between adjacent detection points exceeds 1.0 HV, it is determined that there is a hardness mutation in this area. The coordinate range of the hardness mutation part is recorded and marked as the connector hardness abnormal area. Finally, material deformation detection of the electrical connector is performed on the connector hardness abnormal area. In the hardness abnormal area, by applying tensile force and compressive force on the surface of the electrical connector, the strain distribution on the material surface is recorded to obtain the surface strain distribution data. The magnitudes of the applied tensile force and compressive force are 100 N and -100 N respectively, and the duration is 5 seconds. According to the surface strain distribution data, the strain concentration area is identified. In the strain concentration area, multiple material deformation detection points are selected, and the distance between each material deformation detection point is set to 0.5 mm. Material deformation detection is performed on each material deformation detection point, and a high-precision displacement sensor is used to measure the displacement offset of the surface of the electrical connector material under the applied tensile force and compressive force. The connector material deformation degree value is determined according to the displacement offset and recorded in the data table, and the coordinate position of the detection point is marked at the same time..

[0085] Step S4: Determine the corresponding electrical connector housing according to the structural defect area of the connector; perform housing structure seal detection on the electrical connector housing to generate a housing structure seal degree value;

[0086] In the embodiments of the present invention, in the defective area of the connector structure, the specific position and number of the electrical connector housing corresponding to the defective area are accurately determined through the structure drawing and assembly relationship of the electrical connector. The positioning of the electrical connector housing is completed by a three-dimensional coordinate measurement system, which adopts laser tracking technology with a measurement accuracy of 0.01 mm. During the positioning process, the electrical connector is placed on the measurement platform, and a laser beam is emitted from the laser emitter to the surface of the housing. After the laser is reflected back to the receiver, the system calculates the three-dimensional coordinate position of the housing according to the reflected signal. After determining the electrical connector housing, a shell structure seal detection is carried out on it. The helium mass spectrometry leak detection technology is used for the seal detection. This technology uses helium as a tracer gas. Due to its small molecular diameter and high sensitivity, it can effectively detect minute leaks. During the detection process, first, the electrical connector housing is placed in a sealed detection cavity, and the cavity is evacuated to a vacuum degree of 1.0×10-3 Pascal by a vacuum pump. Subsequently, helium is filled into the housing, and the inflation pressure is set to 0.1 MPa. After the helium is filled, the inflation valve is closed, and the helium mass spectrometry leak detector is started, and its detection sensitivity is set to 1.0×10 -8 Pa·m3 / s. The helium mass spectrometry leak detector evaluates the seal of the housing by detecting the helium leakage amount in the cavity. During the detection process, the leak detector monitors the helium concentration in the cavity in real time, and records the leakage rate when helium leakage is detected. According to the preset seal standard, when the leakage rate exceeds 1.0×10 -6 Pa·m3 / s, it is determined that the seal of the housing is unqualified. After the detection is completed, the system automatically generates a shell structure seal degree value, which is expressed in the form of a leakage rate, and the unit is Pa·m3 / s.

[0087] Step S5: Perform electrical connector performance evaluation based on the connector material deformation degree value and the shell structure seal degree value to obtain electrical connector performance data; predict the electrical connector life through the electrical connector performance data to generate an electrical connector life prediction report.

[0088] In the embodiments of the present invention, first, the connector material deformation degree value measured in step S3 and the shell structure seal degree value measured in step S4 are obtained. The connector material deformation degree value is expressed in percentage. For example, 12% means that the material deformation degree in this area exceeds 12% of the normal range; the shell structure seal degree value is expressed in the form of a leakage rate. For example, 1.5×10 -6 Pa·m3 / s means that the leakage rate of the housing exceeds the standard value.

[0089] Next, a comprehensive evaluation of these two parameters is carried out. For the deformation degree value of the connector material, it is compared with the standard value of 10%. If the actually measured deformation degree value is greater than 10%, it is considered that the material deformation has a negative impact on the performance of the electrical connector. For the sealing degree value of the housing structure, it is compared with the standard value of 1.0×10 -6 Pa·m³ / s. If the actually measured leakage rate is greater than 1.0×10 -6 Pa·m³ / s, it is considered that the housing seal has a negative impact on the performance of the electrical connector. According to the above comparison results, the performance status of the electrical connector is determined. If both the material deformation degree value and the housing structure sealing degree value are within the standard range, it is considered that the performance of the electrical connector is good; if one or both of the parameters exceed the standard range, the performance of the electrical connector is evaluated accordingly according to the degree of exceeding. After completing the performance evaluation, the life of the electrical connector is predicted according to the evaluation results. If the performance of the electrical connector is good, the predicted life value is close to the service life of the electrical connector under ideal conditions, that is, 10 years. If there are defects in the performance of the electrical connector, the predicted life value is adjusted accordingly according to the severity of the defects. For example, if the material deformation degree value exceeds the standard range by 2%, the predicted life value is reduced by 2%; if the housing structure sealing degree value exceeds the standard range by 0.5×10 -6 Pa·m³ / s, the predicted life value is further reduced by 0.5%. In this way, considering the influence of material deformation and housing seal on the life of the electrical connector, the final predicted life value of the electrical connector is obtained. Finally, the performance evaluation results and life prediction values of the electrical connector are compiled into a report. The report details information such as the serial number of the electrical connector, the detection date, the material deformation degree value, the housing structure sealing degree value, the performance evaluation result, and the life prediction value, etc., so as to accurately evaluate and manage the service life of the electrical connector.

[0090] Preferably, step S1 includes the following steps:

[0091] Step S11: Monitor and partition the contacts of the electrical connector. Starting from the starting end of the contacts of the electrical connector, the first 1 / 3 part of the total length of the contacts is marked as the front-end monitoring area; the part from 1 / 3 to 2 / 3 of the total length of the contacts is marked as the middle-end monitoring area; the part from 2 / 3 to the end of the total length of the contacts is marked as the back-end monitoring area;

[0092] Step S12: In the front-end monitoring area, middle-end monitoring area, and back-end monitoring area, collect the contact resistance values in sequence at set time intervals; among them, the set time interval is set to pause for 1 minute after the first collection, pause for 2 minutes after the second collection, pause for 3 minutes after the third collection, and the pause time for each time increases by 1 minute compared with the previous time;

[0093] Step S13: Process the collected contact resistance values, calculate the average value of each monitoring area in three consecutive acquisitions, and obtain the changing trend of the average area resistance;

[0094] Step S14: Determine the slope of the resistance change trend according to the changing trend of the average area resistance. If the slope of the resistance change trend is greater than the preset slope of the resistance change trend, it is determined that the contact resistance value has mutated;

[0095] Step S15: When the contact resistance value mutates, map the monitoring area of the electrical connector contact and record this monitoring area as the abnormal initial site.

[0096] In the embodiment of the present invention, the monitoring areas of the electrical connector contacts are first divided. A high-precision measuring tool, such as a laser rangefinder, is used to accurately measure the total length of the electrical connector contacts. Assuming that the total length of the contact is 300 millimeters, starting from the starting end of the contact, the part with a length of 100 millimeters is marked as the front-end monitoring area; the part from 100 millimeters to 200 millimeters is marked as the middle-end monitoring area; the part from 200 millimeters to the end is marked as the back-end monitoring area. The boundary positions of each area are marked by a laser marker to ensure the accuracy of subsequent monitoring. In the front-end monitoring area, the middle-end monitoring area, and the back-end monitoring area, the contact resistance values are collected in sequence at the set time intervals. A high-precision four-wire resistance measuring instrument is used, and its measurement accuracy reaches the micro-ohm level. The two current introduction wires and the two voltage measurement wires of the measuring instrument are respectively connected to both ends of each monitoring area to ensure the accuracy of the measurement. The acquisition process is as follows:

[0097] The first acquisition: The first contact resistance value is collected in each monitoring area, and the measured value is recorded.

[0098] Pause for 1 minute: After the acquisition is completed, the measuring instrument automatically enters the pause state and waits for 1 minute before the second acquisition.

[0099] The second acquisition: The second contact resistance value is collected in each monitoring area, and the measured value is recorded.

[0100] Pause for 2 minutes: After the acquisition is completed, the measuring instrument enters the pause state again and waits for 2 minutes before the third acquisition.

[0101] The third acquisition: The third contact resistance value is collected in each monitoring area, and the measured value is recorded.

[0102] Pause for 3 minutes: After the acquisition is completed, the measuring instrument enters the pause state and waits for 3 minutes. The pause time increases by 1 minute each time to ensure the stability and reliability of the measurement data.

[0103] Process the collected contact resistance values. Record the contact resistance values in each monitoring area for three consecutive collections respectively. For example, the three collection values in the front-end monitoring area are 0.5 micro-ohm, 0.6 micro-ohm, and 0.7 micro-ohm respectively. Calculate the average value of each monitoring area, that is, the change trend of the average regional resistance. For the front-end monitoring area, the average value is (0.5 + 0.6 + 0.7) / 3 = 0.6 micro-ohm. Calculate the average values of the middle-end monitoring area and the rear-end monitoring area in the same way. Determine the slope of the resistance change trend according to the change trend of the average regional resistance. By calculating the difference between the resistance values of two adjacent collections and then dividing by the time interval, the slope of the resistance change trend is obtained. For example, the slope of the resistance change trend in the front-end monitoring area is (0.6 - 0.5) / 1 + (0.7 - 0.6) / 2 = 0.1 + 0.05 = 0.15 micro-ohm / minute. The preset slope of the resistance change trend is 0.1 micro-ohm / minute. Compare the calculated slope of the resistance change trend with the preset value. If the slope of the resistance change trend is greater than the preset slope of the resistance change trend, for example, 0.15 micro-ohm / minute in the front-end monitoring area is greater than the preset 0.1 micro-ohm / minute, it is determined that the contact resistance value has mutated. When the contact resistance value mutates, through the marking information of the monitoring area, map out the monitoring area of the electrical connector contact and record this monitoring area as the abnormal initial site. The recorded content includes the position of the monitoring area (front-end, middle-end, or rear-end), the slope of the resistance change trend, and the specific resistance value change situation for subsequent further analysis and processing.

[0104] Preferably, in step S2, collecting the surface image of the electrical connector according to the abnormal initial site includes:

[0105] According to the abnormal initial site, use a high-resolution industrial camera to collect the surface image of the electrical connector, and the resolution of the camera is not less than 1024×768 pixels;

[0106] Place the electrical connector on a fixed bracket so that the surface of the electrical connector is perpendicular to the camera lens, and the distance between the camera and the surface of the electrical connector is kept between 10 cm and 20 cm;

[0107] Perform grayscale processing on the collected surface image to convert the color image into a grayscale image; perform median filtering on the grayscale image with a window size of 3×3 pixels; perform edge enhancement processing on the filtered image to obtain the surface image of the electrical connector.

[0108] In the embodiment of the present invention, according to the abnormal initial site, the electrical connector is placed on a dedicated fixing bracket to ensure that the surface of the electrical connector is perpendicular to the camera lens. An industrial camera with high resolution is used to collect images of the surface of the electrical connector. The resolution of this camera is 1024×768 pixels to ensure that the collected images have sufficient details. Adjust the distance between the camera and the surface of the electrical connector to keep it between 10 cm and 20 cm. The specific distance is optimized according to the size of the electrical connector and the focal length of the camera to ensure the clarity and coverage of the image. Before collecting the image, set the parameters of the camera. Adjust the aperture of the camera to F8 to obtain a larger depth of field and ensure that all parts of the surface of the electrical connector can be clearly imaged. At the same time, set the ISO value of the camera to 100 to reduce image noise and improve image quality. Use a uniform ring-shaped LED light source to provide illumination for the surface of the electrical connector, and adjust the brightness of the light source to 70% to ensure that the brightness of the image is moderate and uniform. After the above settings are completed, start the camera to collect images. The collected color images are first transmitted to the image processing unit for grayscale processing. The grayscale processing converts the RGB values of each pixel point of the color image into grayscale values. The conversion formula is: grayscale value = 0.299×R + 0.587×G + 0.114×B. Through this weighted average method, the color image is converted into a grayscale image, reducing the data volume and simplifying the subsequent processing process. Next, perform median filtering on the grayscale image to remove random noise in the image. The median filtering process uses a 3×3 pixel window to sort the grayscale values of each pixel point in the image and its surrounding 8 pixel points, and takes the median value as the new grayscale value of this pixel point. This non-linear filtering method can effectively remove salt-and-pepper noise while retaining the edge information of the image. Finally, perform edge enhancement processing on the filtered image. The edge enhancement processing highlights the edge information by calculating the gradient magnitude of each pixel point in the image. The specific operation is: for each pixel point, calculate the grayscale difference between it and the surrounding pixel points. If the difference exceeds the set threshold of 10, then enhance the grayscale value of this pixel point to make it closer to 255 (white), thereby highlighting the edge. Through this processing, a clear image of the surface of the electrical connector is obtained, providing a high-quality image basis for subsequent defect detection and analysis.

[0109] Preferably, in step S2, when detecting the wear and scratches on the contact surface of the electrical connector surface image, identifying the connector defects on the contact surface, and marking the connector structure defect area includes:

[0110] Divide the electrical connector surface image into multiple image detection areas with equal areas; in each image detection area, calculate the change gradient of the grayscale value to identify the boundary of the wear area on the contact surface; count the area of the wear area on the contact surface in each image detection area to calculate the total wear area of the contact surface;

[0111] Identify the linear features of the image within each image detection area and label them as scratches; measure the length and width of each scratch, and count the total number of scratches on the contact surface within each image detection area;

[0112] Analyze the positional relationship between the worn area and the scratches on the contact surface. If a scratch passes through the worn area and the scratch length exceeds 1 mm, mark the image detection area as a potential connector structure defect area;

[0113] Within the potential connector structure defect area, if the total worn area of the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5, then mark the potential connector structure defect area as a connector structure defect area.

[0114] In the embodiments of the present invention, the surface image of the electrical connector is divided into multiple image detection regions with equal areas. Assuming the resolution of the image is 1024×768 pixels, the image is divided into 16×12 detection regions, and the size of each detection region is 64×64 pixels. Using image segmentation technology, the image is evenly segmented through coordinate positioning to ensure that the area of each detection region is equal. Within each image detection region, the change gradient of the gray value is calculated. By calculating the gray difference between adjacent pixel points, the boundary of the worn area on the contact surface is identified. The specific operation is as follows: for each pixel point within each detection region, calculate the gray difference between it and the surrounding 8 pixel points. If the difference exceeds the set threshold of 10, then it is considered that this pixel point is located on the boundary of the worn area. In this way, the boundary of the worn area within each detection region is identified. The area of the worn area on the contact surface within each image detection region is statistically calculated to calculate the total worn area of the contact surface. Count the pixel points within the boundary of the worn area within each detection region, and multiply the counting result by the area of each pixel point (assuming the area of each pixel point is 0.01 square millimeters) to obtain the worn area within each detection region. Add up the worn areas within all detection regions to obtain the total worn area of the surface of the electrical connector. The linear features of the image are identified within each image detection region and marked as scratches. By calculating the gradient direction and amplitude of each pixel point, the linear features are identified. If the gradient direction of a certain pixel point changes continuously and the gradient amplitude exceeds the set threshold of 20, then it is considered that this pixel point belongs to a scratch. Each scratch is tracked until it ends, so as to identify the complete scratch. Measure the length and width of each scratch. The length of the scratch is obtained by calculating the Euclidean distance between the two end points of the scratch, and the width of the scratch is obtained by calculating the number of pixel points at the widest part of the scratch multiplied by the width of each pixel point. The total number of scratches on the contact surface within each image detection region is statistically calculated. Analyze the positional relationship between the worn area on the contact surface and the scratches. If a scratch passes through the worn area and the length of the scratch exceeds 1 millimeter, then this image detection region is marked as a potential connector structure defect region. The specific operation is as follows: for each scratch within each detection region, check whether it intersects with the boundary of the worn area. If it intersects and the length of the scratch exceeds 1 millimeter, then this detection region is marked as a potential connector structure defect region. Within the potential connector structure defect region, if the total worn area of the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5, then the potential connector structure defect region is marked as a connector structure defect region. The specific operation is as follows: for each potential connector structure defect region, check whether its total worn area exceeds 10 square millimeters and whether the total number of scratches exceeds 5. If both conditions are met, then this region is marked as a connector structure defect region, and its position and relevant information are recorded.

[0115] Preferably, the overall physical hardness detection of the connector structure defect region in step S3 includes:

[0116] Within the defective area of the connector structure, select multiple hardness detection points at equal intervals of 1 mm, and arrange the hardness detection points in a grid pattern;

[0117] At each hardness detection point, bring the probe of the hardness detection device into contact with the surface of the electrical connector, and record the hardness value after the probe applies pressure;

[0118] Conduct three hardness detections at each hardness detection point, with an interval of 10 seconds between each detection;

[0119] Take the average of the three detection results as the hardness of the connector at this hardness detection point;

[0120] Record the hardness of the connector at each hardness detection point in a data table, and mark the coordinate position of the detection point.

[0121] In the embodiments of the present invention, within the defective area of the connector structure, a high-precision positioning device, such as a laser locator, is used to select multiple hardness detection points at equal intervals of 1 mm and arrange the hardness detection points in a grid pattern. Assuming the defective area is a rectangular area with a length of 10 mm and a width of 5 mm, 10×5 = 50 hardness detection points are set in this area to form a grid-like detection point array. At each hardness detection point, the probe of the hardness detection device is accurately aligned with the surface of the electrical connector. The hardness detection device uses a Vickers hardness tester, and its probe is in the shape of a diamond pyramid. The probe is gently brought into contact with the surface of the electrical connector to ensure good contact and no external interference. The load of the hardness tester is set to 10 gf, and the loading time is 10 s. After the pressure is applied by the probe, the hardness tester automatically records the hardness value in units of Vickers hardness (HV). Three hardness detections are performed at each hardness detection point. After the first detection is completed, the hardness tester automatically records the first hardness value; then wait for 10 s for the second detection and record the second hardness value; wait for another 10 s for the third detection and record the third hardness value. Ensure that the interval time between each detection is 10 s to ensure the stability and accuracy of the detection results. Take the average value of the three detection results as the connector hardness of this hardness detection point. The specific operation is as follows: add the hardness values obtained from the first, second, and third detections, and then divide by 3 to obtain the average hardness value of this detection point. For example, if the three detection values of a certain detection point are 250 HV, 252 HV, and 248 HV respectively, the connector hardness of this detection point is (250 + 252 + 248) / 3 = 250 HV. Record the connector hardness of each hardness detection point in a data table and mark the coordinate position of the detection point. The data table includes the detection point number, coordinate position (X coordinate and Y coordinate, in units of mm), and the corresponding connector hardness. For example, the detection point number is 1, the coordinate position is (1 mm, 1 mm), and the connector hardness is 250 HV. In this way, the data of all hardness detection points are completely recorded for subsequent analysis and processing.

[0122] Preferably, in step S3, the detection of the deformation of the electrical connector material in the area with abnormal connector hardness includes:

[0123] In the area with abnormal connector hardness, by applying tensile force and compressive force to the surface of the electrical connector, record the strain distribution on the material surface to obtain surface strain distribution data;

[0124] According to the surface strain distribution data, identify the strain concentration area. In the strain concentration area, select multiple material deformation detection points, and the spacing of each material deformation detection point is set to 0.5 mm;

[0125] Perform material deformation detection on each material deformation detection point, and measure the displacement offset of the surface of the electrical connector material under the application of tensile force and compressive force; determine the deformation degree value of the connector material according to the displacement offset.

[0126] In the embodiment of the present invention, in the abnormal hardness area of the connector, first use a high-precision mechanical test equipment to apply tensile force and compressive force to the surface of the electrical connector. This test equipment can accurately control the magnitude and direction of the applied force, ensuring the stability and repeatability of the experimental conditions. The magnitudes of the tensile force and the compressive force are respectively set to 100 Newtons and -100 Newtons, and the application speed of the force is set to 1 millimeter per minute. During the application of the force, use a strain measurement system to record the strain distribution on the material surface. This system uses high-precision strain gauges with a measurement accuracy reaching the microstrain level. The strain measurement system obtains strain data by pasting strain gauges on the surface of the electrical connector. The arrangement of the strain gauges is in a grid pattern, with a spacing of 1 millimeter between each strain gauge, ensuring that the abnormal hardness area can be fully covered. During the application of the tensile force and the compressive force, the strain measurement system records the strain values of each strain gauge in real time to obtain the surface strain distribution data. These data are stored in the data acquisition system in the form of digital signals for subsequent analysis. According to the surface strain distribution data, identify the strain concentration area. By analyzing the strain data, find the area where the strain value exceeds the preset threshold (for example, 100 microstrains), and mark it as the strain concentration area. In the strain concentration area, select multiple material deformation detection points, and the spacing of each detection point is set to 0.5 millimeters. Use a high-precision displacement measurement device, such as a laser displacement sensor, to perform material deformation detection on each material deformation detection point. When measuring each material deformation detection point, first align the probe of the laser displacement sensor with the detection point to ensure that the distance between the probe and the detection point remains at 10 millimeters. During the application of the tensile force and the compressive force, the laser displacement sensor measures the displacement offset of the surface of the electrical connector material under the applied force in real time. The measurement accuracy of the displacement offset reaches the micron level, ensuring the accuracy of the data. After each measurement is completed, record the displacement offset data in a data table, which includes the detection point number, coordinate positions (X coordinate and Y coordinate, in millimeters), and the corresponding displacement offset. Determine the deformation degree value of the connector material according to the displacement offset. The specific operation is as follows: Compare and analyze the displacement offset of each detection point with the magnitude of the applied force. Suppose the applied tensile force is 100 Newtons and the corresponding displacement offset is 0.1 millimeter, then the deformation degree value of this detection point is 0.1 millimeter / 100 Newtons. In this way, calculate the deformation degree value of each detection point and record the results in the data table for subsequent further analysis and processing.

[0127] Especially importantly, performing material deformation detection on each material deformation detection point and measuring the displacement offset of the surface of the electrical connector material under the application of tensile force and compressive force includes:

[0128] Apply a tensile force of 10 Newtons to each material deformation detection point for a duration of 10 seconds;

[0129] While applying the tensile force, measure the displacement offset of each material deformation detection point through a displacement sensor;

[0130] Apply the tensile force and measure the displacement three times for each material deformation detection point, and take the average of the three measurement results as the displacement offset of the material deformation detection point under the tensile force;

[0131] Apply a compressive force of 20 Newtons to each detection point for a duration of 20 seconds;

[0132] While applying the compressive force, measure the displacement offset of each material deformation detection point through a displacement sensor;

[0133] Apply the tensile force and measure the displacement three times for each material deformation detection point, and take the average of the three measurement results as the displacement offset of the material deformation detection point under the compressive force.

[0134] In the embodiments of the present invention, when performing material deformation detection, first, a high-precision mechanical testing device is used to apply a tensile force to each material deformation detection point. This device can precisely control the magnitude and duration of the applied force. For the tensile force test, the force value is set to 10 Newtons, and the duration is 10 seconds. While applying the tensile force, the displacement deviation of each material deformation detection point is measured by a high-precision laser displacement sensor. The measurement accuracy of the laser displacement sensor reaches the micron level, ensuring the accuracy of the data. The distance between the probe of the displacement sensor and the detection point is maintained at 10 millimeters to ensure the stability and accuracy of the measurement. The tensile force application and displacement measurement are performed three times for each material deformation detection point. After the first application of the tensile force, the displacement deviation measured by the displacement sensor is recorded; then wait for 10 seconds, apply the tensile force for the second time, and record the displacement deviation again; wait for another 10 seconds, apply the tensile force for the third time, and record the displacement deviation of the third time. Ensure that the interval time between each application of the tensile force is 10 seconds to ensure the stability and repeatability of the measurement results. Take the average value of the three measurement results as the displacement deviation of this material deformation detection point under the tensile force. For example, if the three displacement deviations of a certain detection point are 0.05 millimeters, 0.06 millimeters, and 0.04 millimeters respectively, then the displacement deviation of this detection point under the tensile force is (0.05 + 0.06 + 0.04) / 3 = 0.05 millimeters. Next, a compressive force is applied to each material deformation detection point. The force value is set to 20 Newtons, and the duration is 20 seconds. While applying the compressive force, the displacement deviation of each material deformation detection point is measured by the laser displacement sensor. Similarly, the compressive force application and displacement measurement are performed three times for each detection point. After the first application of the compressive force, the displacement deviation measured by the displacement sensor is recorded; then wait for 20 seconds, apply the compressive force for the second time, and record the displacement deviation again; wait for another 20 seconds, apply the compressive force for the third time, and record the displacement deviation of the third time. Ensure that the interval time between each application of the compressive force is 20 seconds to ensure the stability and repeatability of the measurement results. Take the average value of the three measurement results as the displacement deviation of this material deformation detection point under the compressive force. For example, if the three displacement deviations of a certain detection point are -0.1 millimeters, -0.12 millimeters, and -0.08 millimeters respectively, then the displacement deviation of this detection point under the compressive force is (-0.1 + -0.12 + -0.08) / 3 = -0.1 millimeters. Through the above steps, the displacement deviations of each material deformation detection point under the tensile force and the compressive force are obtained.

[0135] As an example of the present invention, refer to Figure 2 As shown, in this example, step S4 includes:

[0136] Step S41: Determine the center coordinates of the connector structure defect area, and convert them into the actual physical coordinates of the electrical connector housing. Determine the corresponding electrical connector housing according to the actual physical coordinates;

[0137] Step S42: Place the electrical connector housing on the test platform of the airtight detector and balance the air pressure inside the housing with the external ambient air pressure;

[0138] Step S43: Apply a constant and small air pressure of 0.1 Pa inside the electrical connector housing for a duration of 30 seconds;

[0139] Step S44: After applying the air pressure, monitor the change of the air pressure inside the housing, record the data in the air pressure rising, stable and falling stages to generate an air pressure change curve;

[0140] Step S45: Calculate the air pressure change rate of the housing according to the air pressure change curve, determine the structural seal of the housing based on the air pressure change rate of the housing, and generate a value of the structural seal degree of the housing.

[0141] In an embodiment of the present invention, a high-precision image processing system is used to determine the central coordinates of the structural defect area of the connector. Through image analysis software, the surface image of the electrical connector is processed to identify the boundary of the structural defect area and calculate its central coordinates. Assuming the image resolution is 1024×768 pixels, the position of the central coordinates of the defect area in the image is (512, 384) pixels. Convert this image coordinate to the actual physical coordinate of the electrical connector housing. Assuming that each pixel in the image corresponds to an actual physical size of 0.1 mm, the central coordinates are converted to (51.2 mm, 38.4 mm). According to the actual physical coordinates, determine the specific position of the electrical connector housing corresponding to the defect area. Place the electrical connector housing on the test platform of the hermeticity detector. Use a high-precision positioning device to ensure that the center of the housing is aligned with the center of the test platform. Before placing the housing, use a pneumatic balance device to adjust the air pressure inside the housing to be consistent with the external ambient air pressure. By connecting the air pressure sensor inside the housing and the air pressure sensor of the external environment, monitor and adjust the air pressure inside the housing until the internal and external air pressure difference is less than 0.01 Pascal (Pa) to ensure pneumatic balance. After the air pressure inside the housing is balanced with the external ambient air pressure, apply a constant and small air pressure to the inside of the housing using the hermeticity detector. Through a high-precision air pressure controller, raise the air pressure inside the housing to 0.1 Pascal (Pa) and maintain this air pressure value for 30 seconds. The precision of the air pressure controller is 0.001 Pascal to ensure that the applied air pressure value is accurate and stable. After applying the air pressure, use a high-precision air pressure sensor to monitor the change of the air pressure inside the housing. The sampling frequency of the air pressure sensor is set to 10 times per second to ensure that the real-time change of the air pressure can be accurately recorded. Record the data in the air pressure rising, stable, and falling stages to generate an air pressure change curve. The air pressure change curve includes three stages: Air pressure rising stage: Record the rising process from the initial air pressure to 0.1 Pascal. Air pressure stable stage: Record the data during the 30 seconds when the air pressure remains at 0.1 Pascal. Air pressure falling stage: Record the process of the air pressure falling from 0.1 Pascal to the initial air pressure. According to the air pressure change curve, calculate the air pressure change rate of the housing. The air pressure change rate is determined by calculating the falling rate of the air pressure during the stable stage. The specific operation is as follows: During the air pressure stable stage, record the time required for the air pressure to drop from 0.1 Pascal to 0.09 Pascal. Assuming this time is 10 seconds, the air pressure change rate is (0.1 - 0.09) / 10 = 0.001 Pascal / second. Based on the air pressure change rate of the housing, determine the structural seal degree of the housing. The preset air pressure change rate threshold is 0.0005 Pascal / second. If the calculated air pressure change rate exceeds this threshold, it is determined that the housing seal is unqualified; if the air pressure change rate is lower than or equal to this threshold, it is determined that the housing seal is qualified. Record the air pressure change rate as the value of the structural seal degree of the housing, with the unit of Pascal / second.For example, if the air pressure change rate is 0.001 Pascal / second, the shell structure sealing degree value is 0.001 Pascal / second, indicating that the shell sealing is unqualified.

[0142] Particularly importantly, step S45 includes the following steps:

[0143] Step S451: Select two adjacent time points on the air pressure change curve and calculate the air pressure difference between these two time points;

[0144] Step S452: Divide the air pressure difference by the time interval to obtain the air pressure change rate within this time period;

[0145] Step S453: Repeat the above steps S451 to step S452 to calculate the air pressure change rate within the entire monitoring time period and record the air pressure change rate at each time point;

[0146] Step S454: Classify the air pressure change rate at each time point and record the corresponding sealing degree level;

[0147] Step S455: Conduct a statistical analysis on the air pressure change rates at all time points and calculate the average air pressure change rate;

[0148] Step S456: Determine the overall sealing degree value of the shell structure based on the average air pressure change rate; if the average air pressure change rate is less than 0.05 Pa / s, the shell structure sealing degree value is 100%; if the average air pressure change rate is between 0.05 Pa / s and 0.1 Pa / s, the shell structure sealing degree value is 50%; if the average air pressure change rate is greater than 0.1 Pa / s, the shell structure sealing degree value is 0%.

[0149] In an embodiment of the present invention, first, two adjacent time points are selected from the air pressure change curve, such as time points t1 and t2, where t1 is 1 second and t2 is 2 seconds. Record the air pressure values corresponding to these two time points. Assume that the air pressure at time t1 is 0.105 Pascal (Pa), and the air pressure at time t2 is 0.103 Pascal (Pa). Calculate the air pressure difference between these two time points, that is, the air pressure difference ΔP = P(t2) - P(t1) = 0.103 - 0.105 = -0.002 Pascal (Pa). In step S452, divide the air pressure difference by the time interval to obtain the air pressure change rate during this time period. The time interval Δt = t2 - t1 = 2 - 1 = 1 second. Therefore, the air pressure change rate ΔP / Δt = -0.002 Pa / 1 s = -0.002 Pascal per second (Pa / s). Record this air pressure change rate in the data table, and the corresponding time point is t1. In step S453, repeat the above steps S451 to S452 to calculate the air pressure change rate during the entire monitoring time period. Assume that the monitoring time period is 30 seconds, with a 1-second time interval. Select adjacent time points in sequence, calculate the air pressure change rate for each time period, and record the air pressure change rate for each time point. For example, for time points t2 and t3 (t3 is 3 seconds), assume the air pressures are 0.103 Pa and 0.101 Pa respectively, then the air pressure difference is -0.002 Pa, and the air pressure change rate is -0.002 Pa / s, which is recorded in the data table corresponding to time point t2. Continue this process until the air pressure change rates for all time points are calculated. In step S454, classify the air pressure change rate for each time point and record the corresponding sealing degree level. According to the preset classification criteria, the air pressure change rate is divided into three levels: if the air pressure change rate is less than 0.05 Pa / s, the sealing degree level is A; if the air pressure change rate is between 0.05 Pa / s and 0.1 Pa / s, the sealing degree level is B; if the air pressure change rate is greater than 0.1 Pa / s, the sealing degree level is C. For example, for the air pressure change rate of -0.002 Pa / s at time point t1, it belongs to level A; for the air pressure change rate of -0.002 Pa / s at time point t2, it also belongs to level A. Record the air pressure change rate for each time point and its corresponding sealing degree level in the data table. In step S455, perform statistical analysis on the air pressure change rates for all time points and calculate the average air pressure change rate. Add up the air pressure change rates for all time points and then divide by the total number of time points. Assume that a total of 30 air pressure change rates are calculated within 30 seconds, and their sum is -0.06 Pa / s, then the average air pressure change rate is -0.06 Pa / s ÷ 30 = -0.002 Pa / s. In step S456, determine the overall sealing degree value of the housing structure based on the average air pressure change rate.According to the preset criteria: if the average air pressure change rate is less than 0.05 Pa / s, the shell structure sealing degree value is 100%; if the average air pressure change rate is between 0.05 Pa / s and 0.1 Pa / s, the shell structure sealing degree value is 50%; if the average air pressure change rate is greater than 0.1 Pa / s, the shell structure sealing degree value is 0%.

[0150] Preferably, the electrical connector performance evaluation based on the connector material deformation degree value and the shell structure sealing degree value in step S5 includes:

[0151] Divide the material deformation degree value by the preset maximum deformation degree value to obtain the material deformation ratio, and subtract this material deformation ratio from 1 to obtain the material deformation influence factor;

[0152] Divide the shell structure sealing degree value by the preset maximum sealing degree value to obtain the shell sealing influence factor;

[0153] Multiply the material deformation influence factor by 0.6, multiply the shell sealing influence factor by 0.4, and add the two results to generate the electrical connector performance determination value;

[0154] Divide the electrical connector performance determination value into performance value ranges, and determine the electrical connector performance data according to the performance value ranges.

[0155] In an embodiment of the present invention, when evaluating the performance of an electrical connector, the material deformation degree value is first processed. Assume that the measured material deformation degree value is 0.08 mm, and the preset maximum deformation degree value is 0.1 mm. Divide the material deformation degree value of 0.08 mm by the preset maximum deformation degree value of 0.1 mm to obtain a material deformation ratio of 0.8. Then subtract this material deformation ratio of 0.8 from 1 to obtain a material deformation influence factor of 0.2. Next, the shell structure sealing degree value is processed. Assume that the measured shell structure sealing degree value is 0.003 Pa / s, and the preset maximum sealing degree value is 0.1 Pa / s. Divide the shell structure sealing degree value of 0.003 Pa / s by the preset maximum sealing degree value of 0.1 Pa / s to obtain a shell sealing influence factor of 0.03. Then, weight allocation and comprehensive calculation are performed. Multiply the material deformation influence factor of 0.2 by the weight coefficient of 0.6 to obtain 0.12. Multiply the shell sealing influence factor of 0.03 by the weight coefficient of 0.4 to obtain 0.012. Add these two results, that is, 0.12 plus 0.012, to obtain an electrical connector performance determination value of 0.132. Finally, the performance value range of the electrical connector performance determination value is divided. The preset performance value range division standard is: when the performance determination value is greater than or equal to 0.9, the electrical connector performance data is "excellent"; when the performance determination value is between 0.5 and 0.9, the electrical connector performance data is "good"; when the performance determination value is less than 0.5, the electrical connector performance data is "poor". According to the above standard, the electrical connector performance determination value of 0.132 falls within the "poor" performance value range, so it is determined that the electrical connector performance data is "poor".

[0156] Preferably, predicting the electrical connector life through the electrical connector performance data in step S5 includes:

[0157] Divide the electrical connector performance interval according to the electrical connector performance data. If the electrical connector performance data is greater than or equal to 0.8, it is determined as a high-performance interval; if the electrical connector performance data is between 0.5 and 0.8, it is determined as a medium-performance interval; if the electrical connector performance data is less than 0.5, it is determined as a low-performance interval;

[0158] For the high-performance interval, predict that the remaining percentage of the electrical connector life in this area is 80%; for the medium-performance interval, predict that the remaining percentage of the electrical connector life in this area is 50%; for the low-performance interval, predict that the remaining percentage of the electrical connector life in this area is 20%;

[0159] Draw an electrical connector life prediction distribution map in the corresponding area of the electrical connector and output an electrical connector life prediction report.

[0160] In an embodiment of the present invention, after analyzing the performance data of the electrical connector, the performance data of the electrical connector is classified according to a preset performance interval division standard. Assume that the performance data of the electrical connector is 0.75. According to the division standard, if the performance data of the electrical connector is greater than or equal to 0.8, it is determined to be in the high-performance interval; if the performance data of the electrical connector is between 0.5 and 0.8, it is determined to be in the medium-performance interval; if the performance data of the electrical connector is less than 0.5, it is determined to be in the low-performance interval. Since 0.75 is between 0.5 and 0.8, the performance data of this electrical connector is determined to be in the medium-performance interval. For the medium-performance interval, according to the preset life prediction standard, the remaining life percentage of the electrical connectors in this area is predicted to be 50%. Using high-precision drawing software, a life prediction distribution map of the electrical connector is drawn in the corresponding area of the electrical connector. During the drawing process, according to the structure and size of the electrical connector, the position of each area is accurately marked, and different colors or patterns are used for distinction according to its performance interval. For example, green is used to represent the high-performance interval, yellow is used to represent the medium-performance interval, and red is used to represent the low-performance interval. In the area corresponding to the medium-performance interval, the remaining life percentage of 50% is marked. After the drawing is completed, a life prediction report of the electrical connector is generated. The report details the serial number, detection date, performance data of the electrical connector, and the corresponding performance interval. At the same time, the life prediction distribution map of the electrical connector is attached to clearly show the performance status and life prediction results of different areas. In the report, for the electrical connectors in the medium-performance interval, it is clearly pointed out that the remaining life percentage is 50%, and corresponding maintenance suggestions are provided, such as regular inspections and timely replacements, etc., to ensure the reliability and safety of the electrical connector.

[0161] The mapping relationship between the performance data of the electrical connector and the remaining life percentage is illustrated by the following experimental data:

[0162] Experimental sample preparation: Randomly select 150 samples from electrical connectors of the same batch, same specification model. These samples have passed strict quality inspections at the time of factory, have consistent performance, and have the same initial life expectancy. These samples are divided into three groups, with 50 samples in each group, and are used for accelerated life tests under different usage environments respectively to simulate the performance attenuation and life consumption process of electrical connectors under actual working conditions.

[0163] Accelerated Life Test Design: The first group of samples is placed in a high-temperature and high-humidity environment with the temperature set at 75°C and the humidity at 95% RH. This environment will accelerate the aging of the insulating material and the oxidation of the contact parts of the electrical connector. The second group of samples is placed in a mechanical vibration environment with a vibration frequency of 55 Hz and an acceleration of 15 g to simulate the mechanical shock during the transportation or operation of the electrical connector. The third group of samples is placed in a high-frequency electromagnetic interference environment with an electromagnetic interference intensity of 15 V / m and a frequency range of 200 MHz to 3.5 GHz to simulate the performance changes of the electrical connector in a complex electromagnetic environment. Each group of samples is respectively subjected to accelerated life tests for 1000 hours, 2000 hours, and 3000 hours in their respective environments, totaling 9 working condition combinations, and each working condition combination corresponds to 17 samples (some samples are for backup).

[0164] Performance Data Acquisition and Processing:

[0165] Under each accelerated life test condition, key performance parameters such as the contact resistance and insulation resistance of the electrical connector are collected every 100 hours using a high-precision electrical parameter tester. The specific measurement methods are as follows:

[0166] Contact Resistance: Measured by the four-terminal method to avoid the influence of lead resistance on the measurement results.

[0167] Insulation Resistance: Measure the resistance value of the insulated part of the electrical connector under the rated voltage through a high-resistance meter.

[0168] The collected original performance parameters are normalized through a data processing algorithm and converted into performance data between 0 and 1. The normalization formula is:

[0169]

[0170] For example, for the contact resistance, the initial value is 0.015 Ω and the failure threshold is 1.5 Ω. If the measured value at a certain moment is 0.75 Ω, then its performance data is:

[0171]

[0172] Calculation of Remaining Life Percentage and Verification of Mapping Relationship: After the accelerated life test is completed, the life of each sample is evaluated. According to the theoretical formula of the accelerated life test, calculate the equivalent life consumption percentage of each sample under the actual working conditions. The equivalent life calculation formula of the accelerated life test is:

[0173]

[0174] Among them, t is the accelerated life test time, τ is the acceleration factor, which is calculated according to the Arrhenius equation. For the high-temperature and high-humidity environment, the relationship between the acceleration factor τ and temperature and humidity is:

[0175]

[0176] Among them, E a is the activation energy, k is the Boltzmann constant, T0 and H0 are the reference temperature and humidity respectively, and T and H are the test temperature and humidity. For the mechanical vibration and electromagnetic interference environments, the calculation formulas of the acceleration factors are similar, and factors such as vibration frequency, acceleration, and electromagnetic interference intensity are considered respectively. Through the above calculations, the remaining life percentage of each sample is obtained. The performance data of the samples are compared and analyzed with the remaining life percentage to verify the mapping relationship between the performance data and the remaining life percentage. The following is a summary of some experimental data:

[0177]

[0178] Verification of the mapping relationship:

[0179] It can be seen from the experimental data that when the performance data is greater than or equal to 0.8, the remaining life percentage is mostly between 80% and 84%, which is close to the predicted value of 80%.

[0180] When the performance data is between 0.5 and 0.8, the remaining life percentage is mostly between 48% and 55%, which is close to the predicted value of 50%.

[0181] When the performance data is less than 0.5, the remaining life percentage is mostly between 22% and 24%, which is close to the predicted value of 20%.

[0182] Through statistical analysis, the errors between the experimental values and the predicted values are all within the allowable range, verifying the rationality of the mapping relationship between the performance data of the electrical connector and the remaining life percentage.

[0183] This specification also provides an electrical connector life prediction system for performing the electrical connector life prediction method as described above. The electrical connector life prediction system includes:

[0184] An electrical performance monitoring module for continuously monitoring the electrical performance of the electrical connector contacts. When a change in the contact resistance value is detected, it is recorded as an abnormal initial site;

[0185] A surface image acquisition and recognition module for acquiring the surface image of the electrical connector according to the abnormal initial site; detecting the wear and scratches on the contact surface of the electrical connector surface image, identifying the connector defects on the contact surface, and marking them as the connector structure defect areas;

[0186] The hardness deformation detection module is used to perform physical hardness detection on the structural defect area of the connector to obtain the connector hardness value; compare the connector hardness value with the preset hardness value, and if the connector hardness value is lower than the preset hardness value, it is determined as the connector hardness abnormal area; perform electrical connector material deformation detection on the connector hardness abnormal area to generate the connector material deformation degree value;

[0187] The housing structure seal detection module is used to determine the corresponding electrical connector housing according to the structural defect area of the connector; perform housing structure seal detection on the electrical connector housing to generate the housing structure seal degree value;

[0188] The electrical connector life prediction module is used to evaluate the performance of the electrical connector based on the connector material deformation degree value and the housing structure seal degree value to obtain the electrical connector performance data; predict the electrical connector life through the electrical connector performance data to generate an electrical connector life prediction report.

[0189] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to cover all changes that fall within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0190] The above are only the specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather will conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for predicting the service life of an electrical connector, characterized in that Including the following steps: Step S1: Continuously monitor the electrical performance of the electrical connector contacts. When a change in the contact resistance value is detected, record it as the abnormal initial site; Step S2: Collect the surface image of the electrical connector according to the abnormal initial site; Detect the wear and scratches on the contact surface of the surface image of the electrical connector, identify the connector defects on the contact surface, and mark them as the connector structure defect areas; Step S3: Conduct a regional overall physical hardness test on the connector structure defect areas to obtain the overall hardness of the connector area; Identify the parts with sudden hardness changes in the overall hardness of the connector area and record them as the connector hardness abnormal areas; Conduct a deformation detection of the electrical connector material on the connector hardness abnormal areas to generate the deformation degree value of the connector material; Step S4: Determine the corresponding electrical connector housing according to the connector structure defect areas; Conduct a housing structure sealing test on the electrical connector housing to generate the housing structure sealing degree value; Step S5: Based on the connector material deformation degree value and the housing structure sealing degree value, conduct a performance evaluation of the electrical connector to obtain the electrical connector performance data; Predict the service life of the electrical connector through the electrical connector performance data to generate an electrical connector service life prediction report.

2. The method for predicting the service life of an electrical connector according to claim 1, wherein Step S1 includes the following steps: Step S11: Divide the monitoring areas of the electrical connector contacts. Starting from the starting end of the electrical connector contacts, the first 1 / 3 part of the total length of the contacts is marked as the front-end monitoring area; the part from 1 / 3 to 2 / 3 of the total length of the contacts is marked as the middle-end monitoring area; the part from 2 / 3 to the end of the total length of the contacts is marked as the back-end monitoring area; Step S12: In the front-end monitoring area, middle-end monitoring area, and back-end monitoring area, collect the contact resistance values in sequence at the set time intervals. Among them, the set time intervals are set to pause for 1 minute after the first collection, pause for 2 minutes after the second collection, pause for 3 minutes after the third collection, and the pause time increases by 1 minute each time compared with the previous one; Step S13: Process the collected contact resistance values, calculate the average value of each monitoring area in three consecutive collections to obtain the change trend of the regional resistance average value; Step S14: Determine the resistance change trend slope according to the change trend of the regional resistance average value. If the resistance change trend slope is greater than the preset resistance change trend slope, it is judged that the contact resistance value has mutated; Step S15: When the contact resistance value mutates, map the monitoring area of the electrical connector contacts and record this monitoring area as the abnormal initial site.

3. The method for predicting the service life of an electrical connector according to claim 1, characterized in that, The collection of the surface image of the electrical connector according to the abnormal initial site in Step S2 includes: According to the abnormal initial site, use a high-resolution industrial camera to collect the image of the electrical connector surface. The resolution of the camera is not less than 1024×768 pixels; Place the electrical connector on a fixed bracket so that the surface of the electrical connector is perpendicular to the camera lens, and the distance between the camera and the surface of the electrical connector is kept between 10 cm and 20 cm; Perform grayscale processing on the collected surface image to convert the color image into a grayscale image; perform median filtering on the grayscale image with a window size of 3×3 pixels; perform edge enhancement on the filtered image to obtain the surface image of the electrical connector.

4. The method for predicting the service life of an electrical connector according to claim 1, characterized in that, In step S2, detect the wear and scratches on the contact surface of the surface image of the electrical connector, identify the connector defects on the contact surface, and mark the connector structure defect areas including: Divide the surface image of the electrical connector into multiple image detection areas with equal areas; within each image detection area, calculate the change gradient of the grayscale value to identify the boundary of the wear area on the contact surface; count the area of the wear area on the contact surface within each image detection area to calculate the total wear area of the contact surface. Identify the linear features of the image within each image detection area and mark them as scratches; measure the length and width of each scratch, and count the total number of scratches on the contact surface within each image detection area. Analyze the positional relationship between the wear area on the contact surface and the scratches. If a scratch passes through the wear area and the length of the scratch exceeds 1 mm, mark this image detection area as a potential connector structure defect area. Within the potential connector structure defect area, if the total wear area of the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5, then mark the potential connector structure defect area as a connector structure defect area.

5. The method for predicting the service life of an electrical connector according to claim 1, wherein In step S3, the regional overall physical hardness detection of the connector structure defect area includes: Within the connector structure defect area, select multiple hardness detection points at equal intervals of 1 mm and set the hardness detection points in a grid pattern. At each hardness detection point, contact the probe of the hardness detection device with the surface of the electrical connector and record the hardness value after the probe applies pressure. Perform hardness detection three times at each hardness detection point, with a time interval of 10 seconds between each detection. Take the average value of the three detection results as the connector hardness value of this hardness detection point. Record the connector hardness value of each hardness detection point in a data table and mark the coordinate position of the detection point.

6. The method for predicting the service life of an electrical connector according to claim 1, wherein In step S3, the electrical connector material deformation detection of the connector hardness abnormal area includes: In the connector hardness abnormal area, by applying tensile force and compressive force on the surface of the electrical connector, record the strain distribution on the material surface to obtain the surface strain distribution data. Identify the strain concentration area according to the surface strain distribution data. Within the strain concentration area, select multiple material deformation detection points, and the distance between each material deformation detection point is set to 0.5 mm. Perform material deformation detection on each material deformation detection point, measure the displacement offset of the surface of the electrical connector material under the applied tensile force and compressive force; determine the connector material deformation degree value according to the displacement offset.

7. The method for predicting the service life of an electrical connector according to claim 1, wherein, Step S4 includes the following steps: Step S41: Determine the center coordinates of the connector structure defect area and convert them into the actual physical coordinates of the electrical connector housing. Determine the corresponding electrical connector housing according to the actual physical coordinates. Step S42: Place the electrical connector housing on the test platform of the seal detector and make the air pressure inside the housing balance with the external ambient air pressure. Step S43: Apply a constant and tiny air pressure of 0.1 Pa inside the electrical connector housing for 30 seconds; Step S44: After applying the air pressure, monitor the change of the air pressure inside the housing, record the data of the air pressure rising, stabilizing and falling stages to generate an air pressure change curve; Step S45: Calculate the air pressure change rate of the housing according to the air pressure change curve, and determine the housing structure seal based on the air pressure change rate of the housing to generate a housing structure seal degree value.

8. The method for predicting the service life of an electrical connector according to claim 7, wherein, The electrical connector performance evaluation based on the connector material deformation degree value and the housing structure seal degree value in Step S5 includes: Divide the material deformation degree value by the preset maximum deformation degree value to obtain a material deformation ratio, and subtract this material deformation ratio from 1 to obtain a material deformation influence factor; Divide the housing structure seal degree value by the preset maximum seal degree value to obtain a housing seal influence factor; Multiply the material deformation influence factor by 0.6, multiply the housing seal influence factor by 0.4, and add the two results to generate an electrical connector performance determination value; Divide the performance value range of the electrical connector performance determination value, and determine the electrical connector performance data according to the performance value range.

9. The method for predicting the service life of an electrical connector according to claim 7, characterized in that, The prediction of the electrical connector life through the electrical connector performance data in Step S5 includes: Divide the electrical connector performance interval according to the electrical connector performance data. If the electrical connector performance data is greater than or equal to 0.8, it is determined as a high-performance interval; if the electrical connector performance data is between 0.5 and 0.8, it is determined as a medium-performance interval; if the electrical connector performance data is less than 0.5, it is determined as a low-performance interval; For the high-performance interval, predict that the remaining percentage of the electrical connector life in this area is 80%; for the medium-performance interval, predict that the remaining percentage of the electrical connector life in this area is 50%; for the low-performance interval, predict that the remaining percentage of the electrical connector life in this area is 20%; Draw an electrical connector life prediction distribution map in the corresponding area of the electrical connector and output an electrical connector life prediction report.

10. An electrical connector life prediction system, characterized in that, For implementing the electrical connector life prediction method as described in Claim 1, the electrical connector life prediction system includes: An electrical performance monitoring module for continuously monitoring the electrical performance of the electrical connector contacts, and recording it as an abnormal initial site when the detected contact resistance value changes; A surface image acquisition and recognition module for acquiring the surface image of the electrical connector according to the abnormal initial site; detecting the contact surface wear and scratches of the electrical connector surface image, identifying the connector defects on the contact surface, and marking them as connector structure defect areas; A hardness deformation detection module for performing a regional overall physical hardness detection on the connector structure defect area to obtain the overall hardness of the connector area; identifying the hardness mutation parts of the overall hardness of the connector area and recording them as connector hardness abnormal areas; performing electrical connector material deformation detection on the connector hardness abnormal areas to generate a connector material deformation degree value; A housing structure seal detection module for determining the corresponding electrical connector housing according to the connector structure defect area; performing a housing structure seal detection on the electrical connector housing to generate a housing structure seal degree value; An electrical connector life prediction module is used to evaluate the performance of an electrical connector based on the deformation degree value of the connector material and the sealing degree value of the housing structure, so as to obtain the electrical connector performance data; predict the life of the electrical connector through the electrical connector performance data to generate an electrical connector life prediction report.

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