A method and system for predicting the life of an electrical connector

Abstract

The application relates to the technical field of electric signal processing, in particular to a method and system for predicting the service life of an electric connector. The method comprises the following steps: continuously monitoring the electrical performance of the contact piece of the electric connector, recording an abnormal initial site when a change in the contact resistance value is detected; collecting a surface image of the electric connector according to the abnormal initial site; detecting the wear and scratch of the contact surface of the surface image of the electric connector, identifying the connector defects of the contact surface, and marking the connector defects as a connector structure defect area; detecting the overall physical hardness of the connector structure defect area to obtain a connector overall hardness value; identifying the hardness mutation site of the connector overall hardness value to record the connector hardness abnormal area. The application realizes the comprehensive evaluation of the performance of the electric connector through the electric signal processing technology and the image recognition technology, thereby improving the accuracy of the service life prediction of the electric connector.

Description

TECHNICAL FIELD

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

[0002] An electrical connector is an electronic component used to achieve electrical connection and is widely used in electronic devices, communication systems, automobiles, aerospace, etc. The contact of an electrical connector is a core component of the electrical connector and is used to achieve electrical connection. The shell of the electrical connector is used to protect the internal contact and insulator, and provides mechanical protection and environmental sealing. The service life prediction of the electrical connector usually ignores the change of material performance. On the one hand, the decrease of material hardness will lead to the decrease of mechanical performance of the contact, thereby affecting the reliability of the electrical connector. However, there is a lack of real-time monitoring and evaluation means for material hardness in the prior art, and it is impossible to accurately determine whether the material performance is abnormal. On the other hand, the service life prediction of the electrical connector usually ignores the influence of the sealing property of the shell structure on the service life. Insufficient sealing property of the shell will lead to the entry of external environmental factors (such as moisture and dust) into the electrical connector, thereby accelerating the aging and failure of the electrical connector. However, there is a lack of detection and evaluation means for the sealing property of the shell in the prior art, and it is impossible to comprehensively evaluate the health status of the electrical connector. SUMMARY

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

[0004] To achieve the above-mentioned purpose, a method for predicting the service life of an electrical connector is provided, and the method comprises the following steps:

[0005] Step S1: continuously monitoring the electrical performance of the contact of the electrical connector, and recording an abnormal initial site when detecting a change in the contact resistance value;

[0006] Step S2: collecting a surface image of the electrical connector according to the abnormal initial site; detecting the contact surface wear and scratches of the surface image of the electrical connector, identifying the connector defects of the contact surface, and marking as a connector structure defect area;

[0007] Step S3: detecting the overall physical hardness of the connector structure defect area to obtain a connector overall hardness value; identifying the hardness mutation site of the connector overall hardness value to record a connector hardness abnormal area; detecting the material deformation of the connector hardness abnormal area to generate a connector material deformation degree value;

[0008] Step S4: determining the corresponding electrical connector shell according to the connector structure defect area; detecting the sealing property of the shell structure of the electrical connector to generate a shell structure sealing degree value;

[0009] Step S5: Perform electrical connector performance evaluation based on the connector material deformation degree value and the shell structure sealing degree value to obtain 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.

[0010] The application continuously monitors the electrical performance of the electrical connector contact, and once the contact resistance value changes, it is recorded as an abnormal initial point. This real-time monitoring and accurate recording ensures timely capture of changes in electrical connector performance, avoids missing critical abnormal information due to monitoring delays, lays a solid foundation for subsequent detection and evaluation, effectively improves the accuracy and reliability of electrical connector performance monitoring, and enables subsequent detection and evaluation based on accurate initial data. According to the abnormal initial point, the surface image of the electrical connector is collected, and the contact surface wear and scratches in the image are detected to identify the connector defects of the contact surface and mark them as connector structure defect areas. This step realizes comprehensive detection and accurate identification of surface defects of the electrical connector through image acquisition and analysis technology, which not only can find the tiny defects that are difficult to be detected by naked eye, but also can accurately locate and mark the defects, providing clear area guidance for subsequent targeted detection and evaluation, greatly improving the efficiency and accuracy of electrical connector defect detection, and helping to discover potential performance risks in time. The connector structure defect area is detected for physical hardness, the hardness of the connector is obtained, and compared with the preset hardness to determine the hardness abnormal area of the connector; then the hardness abnormal area is detected for electrical connector material deformation to generate the material deformation degree value of the connector. This deep detection process analyzes the structural performance of the electrical connector from two key dimensions of physical hardness and material deformation, accurately identifies the performance weak links caused by insufficient hardness or material deformation through comparison with the standard hardness and quantitative evaluation of the deformation degree, provides more comprehensive and accurate quantitative data for subsequent performance evaluation, significantly enhances the accuracy and reliability of electrical connector performance evaluation, and makes the evaluation results more scientific and convincing. According to the connector structure defect area, the corresponding electrical connector shell is determined, and the shell structure sealing detection is performed on the shell to generate the shell structure sealing degree value. This step includes the sealing performance of the electrical connector shell in the evaluation category, and quantifies the shell structure sealing degree through scientific detection means, further improving the electrical connector performance evaluation system. The shell sealing performance is an important factor affecting the performance and service life of the electrical connector, and its detection result can provide key basis for evaluating the reliability of the electrical connector in 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 application. Based on the connector material deformation degree value and the shell structure sealing degree value, the performance of the electrical connector is evaluated to obtain the performance data of the electrical connector, and the service life of the electrical connector is predicted to generate the service life prediction report of the electrical connector. This step comprehensively uses the key data obtained in the previous steps to realize the comprehensive evaluation of the performance of the electrical connector and the accurate prediction of the service life. The generated service life prediction report can provide accurate and reliable data support for the use, maintenance and replacement of the electrical connector, help users to develop reasonable maintenance plan and replacement strategy in advance, and reduce the risk of equipment downtime caused by electrical connector failure.

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

[0012] Step S11: monitoring partitioning the electrical connector contact, from the starting end of the electrical connector contact, the length is 1 / 3 of the total length of the contact, marked as the front-end monitoring area; from 1 / 3 to 2 / 3 of the total length of the contact, marked as the middle-end monitoring area; from 2 / 3 of the total length of the contact to the end, marked as the rear-end monitoring area;

[0013] Step S12: collecting contact resistance values in the front-end monitoring area, the middle-end monitoring area and the rear-end monitoring area in turn according to the set time interval; wherein 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 each pause time increases by 1 minute than the previous one;

[0014] Step S13: processing the collected contact resistance values, calculating the average value of each monitoring area in the continuous three times of collection to obtain the average value change trend of the area resistance;

[0015] Step S14: determining the resistance change trend slope according to the average value change trend of the area resistance, if the resistance change trend slope is greater than the preset resistance change trend slope, it is judged that the contact resistance value is suddenly changed;

[0016] Step S15: when the contact resistance value is suddenly changed, the monitoring area of the electrical connector contact is mapped out, and the monitoring area is recorded as the abnormal initial site.

[0017] The present application divides the electrical connector contact into three monitoring areas of front end, middle end and rear end, and collects the contact resistance values in turn according to a specific time interval, calculates the average value change trend of the resistance of each area and the resistance change trend slope, which can accurately locate the area of sudden change of contact resistance value and record it as the abnormal initial site. This way of partition monitoring and dynamic time interval collection realizes the fine monitoring of the resistance change of different parts of the electrical connector contact, can timely and accurately capture the resistance sudden change, 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 life prediction of the electrical connector, ensures the performance stability and reliability of the electrical connector in actual application, reduces the risk of failure 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, step S2 comprises collecting the surface image of the electrical connector according to the abnormal initial site comprises:

[0019] According to the abnormal initial site, image acquisition is performed on the surface of the electrical connector using a high-resolution industrial camera, and the resolution of the camera is not less than 1024*768 pixels;

[0020] The electrical connector is placed on a fixed support, 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;

[0021] The collected surface image is subjected to grayscale processing, and the color image is converted into a grayscale image; the grayscale image is subjected to median filtering processing, and the window size is 3*3 pixels; the filtered image is subjected to edge enhancement processing to obtain the surface image of the electrical connector.

[0022] In the electrical connector life prediction method, 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 on the surface of the electrical connector, so as to ensure the definition and detail presentation of the images. The electrical connector is placed on a fixed support, 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 accurate acquisition setting can ensure that the collected images have uniform and high-quality imaging effects, providing a reliable basis for subsequent image processing. The collected surface image is subjected to grayscale processing, and the color image is converted into a grayscale image, which simplifies the image data and reduces the calculation amount of subsequent processing. The grayscale image is subjected to median filtering processing, and the window size is 3*3 pixels, which effectively removes noise interference in the image while retaining the edge information of the image. The filtered image is subjected to edge enhancement processing, which further highlights the detailed features of the surface of the electrical connector, so that the defects such as wear and scratches on the surface of the electrical connector can be more clearly presented, providing high-quality image basis for subsequent defect recognition and structure defect area marking, thereby improving the accuracy and reliability of the electrical connector surface defect detection, providing more accurate structure defect data support for the life prediction of the electrical connector, and helping to realize the fine evaluation of the performance of the electrical connector and the accurate prediction of the life.

[0023] Preferably, the step S2 of detecting the contact surface wear and scratches of the electrical connector surface image, identifying the connector defects of the contact surface, and marking the connector structure defect area comprises:

[0024] The electrical connector surface image is divided into a plurality of equal-area image detection regions; in each image detection region, the change gradient of the grayscale value is calculated to identify the boundary of the contact surface wear area; the area of the contact surface wear area in each image detection region is counted to calculate the total area of the contact surface wear area;

[0025] Identify the image linear features in each image detection area, marked as scratches; measure the length and width of each scratch, and count the total number of scratches in each image detection area;

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

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

[0028] The present application realizes accurate identification and quantitative evaluation of contact surface wear area and scratches by fine processing and analysis of the surface image of the electrical connector. First, the surface image of the electrical connector is divided into multiple equal-area image detection areas to ensure uniformity and comprehensiveness of the analysis. In each image detection area, the change gradient of the gray value is calculated to identify the boundary of the contact surface wear area, and the wear area is counted to calculate the total area of the contact surface wear, thereby quantitatively evaluating the wear degree. At the same time, the image linear features are identified and marked as scratches, the length and width of each scratch are measured, and the total number of scratches is counted to realize accurate quantification of the scratches. By analyzing the positional relationship between the contact surface wear area and the scratches, combined with the quantitative indicators such as the length of the scratches and the wear area, the potential connector structure defect area and the final connector structure defect area are accurately marked. 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, providing detailed and accurate structural defect data for subsequent performance evaluation and life prediction, effectively improving the accuracy and reliability of the electrical connector defect detection, and helping to realize fine evaluation of the performance of the electrical connector and accurate prediction of the life.

[0029] Preferably, the step S3 of detecting the hardness of the connector structure defect area as a whole includes:

[0030] In the connector structure defect area, a plurality of hardness detection points are selected at an interval of 1 mm, and the hardness detection points are arranged in a grid shape;

[0031] 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;

[0032] Each hardness detection is performed three times, and the interval time between each detection is 10 seconds;

[0033] The average value of the three detection results is taken as the hardness value of the connector at the hardness detection point;

[0034] The connector hardness value of each hardness detection point and the coordinate position of the detection point are recorded in a data table.

[0035] The present application adopts a 1mm equidistant grid hardness detection point layout in the connector structure defect area, ensuring the comprehensiveness and uniformity of hardness detection. At each hardness detection point, the hardness detection equipment probe contacts the surface of the electrical connector and records the hardness value after applying pressure, effectively reducing the accidental error of single detection by taking the average value of three detections, and improving the accuracy of hardness detection. The connector hardness value of each hardness detection point and the coordinate position of the detection point are recorded in a data table, providing detailed and accurate information for subsequent hardness data analysis and comparison, facilitating the identification of hardness abnormal areas and targeted material deformation detection, thereby providing reliable data support for electrical connector performance evaluation and life prediction, ensuring the scientificity and accuracy of the evaluation results.

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

[0037] In the connector hardness abnormal area, the strain distribution of the material surface is recorded by applying tensile force and compressive force on the surface of the electrical connector, and the surface strain distribution data is obtained;

[0038] According to the surface strain distribution data, the strain concentration area is identified, and a plurality of material deformation detection points are selected in the strain concentration area, and the spacing of each material deformation detection point is set to 0.5mm;

[0039] The material deformation of each material deformation detection point is detected, the displacement deviation of the material surface of the electrical connector under the action of tensile force and compressive force is measured, and the material deformation degree value of the connector is determined according to the displacement deviation.

[0040] In the connector hardness abnormal area, the strain distribution of the material surface is recorded by applying tensile force and compressive force, and the surface strain distribution data is obtained, and then the strain concentration area is identified. In this area, a plurality of material deformation detection points are set at a spacing of 0.5mm, the material deformation of each detection point is detected, the displacement deviation of the material surface of the electrical connector under the action of force is measured, and the material deformation degree value of the connector is determined accordingly. This deformation detection method based on strain distribution can accurately locate and quantify the deformation of the electrical connector material, providing key data for evaluating the structural stability of the connector under stress conditions, and helping to more accurately predict the performance change and service life of the electrical connector, ensuring its reliability in actual application.

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

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

[0043] Step S42: place the electrical connector shell on the sealing detector test platform and balance the internal and external air pressures of the shell;

[0044] Step S43: apply a constant small air pressure to the inside of the electrical connector shell, with an air pressure value of 0.1 Pa and a duration of 30 seconds;

[0045] Step S44: after applying air pressure, monitor the change of the internal air pressure of the shell, record the data of the rising, stable and falling stages of the air pressure, and generate an air pressure change curve;

[0046] Step S45: calculate the shell air pressure change rate according to the air pressure change curve, determine the shell structure sealing based on the shell air pressure change rate, and generate a shell structure sealing degree value.

[0047] The present application accurately determines the center coordinates of the connector structure defect area and converts them into actual physical coordinates of the electrical connector shell, accurately locking the corresponding electrical connector shell. After placing the shell on the sealing detector test platform and balancing the internal and external air pressures, a constant small air pressure (0.1 Pa) is applied for 30 seconds, and the whole process of the change of the internal air pressure of the shell is monitored and recorded to generate an air pressure change curve. Based on the air pressure change curve, the shell air pressure change rate is calculated, and the shell structure sealing 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 shell, provides key data support for the overall evaluation of the performance of the electrical connector, ensures the sealing reliability of the electrical connector in complex environments, and has important significance for prolonging the service life of the electrical connector and ensuring the stable operation of the equipment.

[0048] Preferably, the electrical connector performance evaluation based on the connector material deformation degree value and the shell structure sealing degree value in step S5 comprises:

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

[0050] Divide the shell structure sealing degree value by the preset maximum sealing degree value to obtain a material deformation influence factor;

[0051] 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 an electrical connector performance determination value;

[0052] The performance value range of the performance determination value of the electric connector is divided, and the performance data of the electric connector is determined according to the performance value range.

[0053] The material deformation ratio is obtained by comparing the material deformation degree value with the preset maximum deformation degree value, and the material deformation influence factor is further obtained. Meanwhile, the shell structure sealing degree value is compared with the preset maximum sealing degree value to obtain the shell sealing influence factor. The two influence factors are weighted and summed according to the set weight (the material deformation influence factor weight is 0.6, and the shell sealing influence factor weight is 0.4) to generate the performance determination value of the electric connector. The performance data of the electric connector is determined according to the performance determination value of the electric connector by dividing the performance value range. This process realizes the quantitative evaluation of the performance of the electric connector, comprehensively considers the two key factors of material deformation and shell sealing, and obtains the determination value that can accurately reflect the overall performance of the electric connector through scientific weight distribution and quantitative calculation. The performance evaluation and life prediction of the electric connector are provided with accurate and objective data basis, and the scientificity and reliability of the evaluation result are ensured.

[0054] Preferably, the step S5 of predicting the life of the electric connector according to the performance data of the electric connector comprises:

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

[0056] For the high performance interval, the remaining percentage of the life of the electric connector in this region is predicted to be 80%; for the medium performance interval, the remaining percentage of the life of the electric connector in this region is predicted to be 50%; and for the low performance interval, the remaining percentage of the life of the electric connector in this region is predicted to be 20%.

[0057] The electric connector life prediction distribution diagram is drawn in the corresponding region of the electric connector, and the electric connector life prediction report is output.

[0058] The present application divides performance intervals according to electrical connector performance data, and clearly defines the corresponding electrical connector life remaining percentage in different performance intervals: the high performance interval (performance data >= 0.8) corresponds to a life remaining percentage of 80%, the medium performance interval (performance data between 0.5 and 0.8) corresponds to a life remaining percentage of 50%, and the low performance interval (performance data < 0.5) corresponds to a life remaining percentage of 20%. Through this quantitative division and corresponding relationship, the life of the electrical connector can be quickly and accurately predicted. 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 visual distribution maps and detailed reports, makes the life evaluation of the electrical connector more scientific, accurate and easy to understand, helping users to timely grasp the performance status of the electrical connector and reasonably arrange maintenance and replacement plans, thereby improving the use efficiency and reliability of the electrical connector and reducing the risk and cost caused by electrical connector failure.

[0059] The present specification also provides an electrical connector life prediction system for performing the electrical connector life prediction method as described above, which comprises:

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

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

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

[0063] A shell structure sealing detection module for determining the corresponding electrical connector shell according to the connector structure defect area; and performing shell structure sealing detection on the electrical connector shell to generate a shell structure sealing 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 shell structure sealing degree value to obtain electrical connector performance data; and predicting the life of the electrical connector through the electrical connector performance data to generate an electrical connector life prediction report.

[0065] The electric connector life prediction system of the present application realizes comprehensive evaluation and accurate prediction of the performance and life of the electric connector through the cooperative work of the five modules. The electrical performance monitoring module can monitor the change of contact resistance in real time and record the abnormal initial site, providing an accurate starting point for subsequent detection; the surface image acquisition and identification module acquires images and identifies structural defect areas based on the abnormal initial site, accurately positioning surface wear and scratches; the hardness and deformation detection module detects the hardness and deformation of the defect area, quantifying the change in material performance; the shell structure sealing detection module detects the sealing of the corresponding shell, evaluating the integrity of the shell; the electric connector life prediction module evaluates the performance by comprehensively considering the material deformation degree value and the shell 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 precision from electrical performance monitoring to life prediction, provides a scientific basis for the maintenance and replacement of the electric connector, effectively improves the use efficiency and reliability of the electric connector, and reduces the risk of equipment failure. BRIEF DESCRIPTION OF DRAWINGS

[0066] Figure 1 It is a step flowchart of the electric connector life prediction method.

[0067] Figure 2 It is a detailed implementation step flowchart of step S4 in the method. Figure 1

[0068] The implementation of the present application, functional features and advantages will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0069] The technical method of the present application will be described clearly and completely below in combination with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

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

[0071] ​It should be understood that, although the terms "first", "second" or the like can be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of the example embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

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

[0073] Step S1: continuously monitor the electrical performance of the electrical connector contact, and when a change in contact resistance value is detected, record it as an abnormal initial site;

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

[0075] Step S3: perform area-wide physical hardness detection on the connector structure defect areas to obtain connector area-wide hardness values; perform hardness mutation site identification on the connector area-wide hardness values to record them as connector hardness abnormal areas; perform electrical connector material deformation detection on the connector hardness abnormal areas to generate connector material deformation degree values;

[0076] 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 a housing structure sealing degree value;

[0077] Step S5: perform electrical connector performance evaluation based on the connector material deformation degree values and the housing structure sealing degree value to obtain 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.

[0078] In the embodiments of the present application, reference Figure 1 is made to the schematic diagram of the step flow of a method for predicting the service life of an electrical connector, in the present example, the method for predicting the service life of an electrical connector comprises the following steps:

[0079] Step S1: continuously monitor the electrical performance of the electrical connector contact, and when a change in contact resistance value is detected, record it as an abnormal initial site;

[0080] In the embodiment of the present application, high-precision four-wire resistance measurement technology is used to continuously monitor the electrical performance of the contact of the electrical connector. Specifically, two wires are connected to the two ends of the contact as current introduction lines, and the other two wires are used as voltage measurement lines to accurately measure the contact resistance value. The monitoring system uses 1 second as a sampling period, and uses a high-precision digital multimeter with a measurement accuracy of micro-ohm level to collect the contact resistance value in real time. When the contact resistance value changes by more than 0.1 micro-ohm compared with the initial set reference resistance value, the system automatically records the measurement point at this time as an abnormal initial point, and records the detailed information of the point, including but not limited to the measurement time, the specific number of the contact, and the environmental temperature and other parameters.

[0081] Step S2: collecting an image of the surface of the electrical connector according to the abnormal initial point; detecting the contact surface wear and scratches of the surface image of the electrical connector, identifying the connector defects of the contact surface, and marking as a connector structure defect area;

[0082] In the embodiment of the present application, according to the abnormal initial site recorded in step S1, a high-resolution industrial camera is started to collect images of the surface of the electrical connector. The industrial camera adopts a line array scanning mode to ensure high resolution and high definition of the images. The light source of the camera adopts a uniform ring-shaped LED light source, and the light intensity can be adjusted in the range of 10% to 100%. Before collecting the images, the light intensity is adjusted to 50% to ensure that the brightness of the images is moderate and uniform. The shooting resolution of the camera is set to 2048x2048 pixels to ensure that the micro details of 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, the image is first preprocessed, including adjusting the brightness and contrast of the image. By adjusting the brightness value of the image, the average brightness reaches 128 (in the gray scale range of 0 to 255), and at the same time, the contrast is adjusted to 1.5 times to enhance the distinction between different regions in the image. Then, the image is denoised by using a 3x3 median filter to process each pixel point in the image to remove random noise and ensure the clarity and accuracy of the image. After the image preprocessing is completed, the surface image of the electrical connector is analyzed in detail. With the aid of an optical microscope, the image is magnified to 100 times, and the contact area of the surface of the electrical connector is checked point by point. During the checking process, a high-precision image analysis tool is used to analyze the gray value of each pixel point in the image. For the wear area of the contact surface, the gray value is usually lower than that of the surrounding normal area. When the gray value of a certain area is detected to be lower than the set threshold value 100, it is marked as a potential wear area. For a scratch, it appears as an elongated line in the image with a gray value obviously higher than that of the surrounding area. When a continuous line with a gray value exceeding 180 is detected, it is marked as a scratch area. After identifying the wear and scratch areas, further detailed checking is performed on these areas to determine whether there is a connector structure defect. By comparing the standard electrical connector surface image, the size and shape of each marked area are compared and analyzed. For the wear area, if its area exceeds 0.5 square millimeters or its shape is irregular and the edge is blurred, it is marked as a connector structure defect area. For the scratch, if its length exceeds 2 millimeters or its width exceeds 0.1 millimeter, it is also marked as a connector structure defect area. During the marking process, a red rectangular frame 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: detecting the overall hardness of the connector structure defect area, obtaining the overall hardness of the connector area, identifying the hardness mutation site of the overall hardness of the connector area, and recording it as the hardness abnormal area of the connector; detecting the material deformation of the hardness abnormal area of the connector, and generating the material deformation degree value of the connector.

[0084] In the embodiment of the present application, in the process of implementing step S3, first, the area overall physical hardness of the defect area of the electrical connector structure is detected. A high-precision hardness detection device is used, which is equipped with a probe with adjustable pressure and can accurately measure the hardness value of the surface of the electrical connector. The electrical connector is placed on a fixed support to ensure that its surface is flat and stable. The probe of the hardness detection device is in contact with 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 defect area of the connector structure, a plurality of hardness detection points are selected at equal intervals of 1 mm, and the hardness detection points are arranged in a grid shape to ensure that the entire defect area is covered. At each hardness detection point, the probe of the hardness detection device is in contact with 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, with an interval of 10 seconds between each detection. The average value of the three detection results is taken as the hardness value of the connector at the hardness detection point, and the hardness value of each hardness detection point is recorded in the data table, with the coordinate position of the detection point marked. Subsequently, the overall hardness of the connector region is identified. By analyzing the recorded hardness data, the hardness difference between adjacent hardness detection points is calculated. A hardness difference threshold of 1.0 HV (Vickers hardness unit) is set, and when the hardness difference between adjacent detection points exceeds 1.0 HV, it is determined that there is a hardness mutation in the region. The coordinate range of the hardness mutation site is recorded and marked as the hardness abnormal area of the connector. Finally, the material deformation of the electrical connector in the hardness abnormal area is detected. In the hardness abnormal area, the strain distribution of the material surface is recorded by applying tensile force and compressive force on the surface of the electrical connector to obtain the surface strain distribution data. 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, and a plurality of material deformation detection points are selected in the strain concentration area, with a spacing of 0.5 mm between each material deformation detection point. The material deformation of each material deformation detection point is detected, and a high-precision displacement sensor is used to measure the displacement of the electrical connector material surface under the applied tensile force and compressive force. The material deformation degree value of the connector is determined according to the displacement, and the value is recorded in the data table, with the coordinate position of the detection point marked.

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

[0086] In the embodiment of the present application, in the defect area of the connector structure, the specific position and number of the electrical connector shell corresponding to the defect area are accurately determined through the structural drawing and assembly relationship of the electrical connector. The positioning of the electrical connector shell is completed by a three-dimensional coordinate measuring system, which adopts laser tracking technology and has a measurement accuracy of 0.01 mm. During the positioning process, the electrical connector is placed on the measuring platform, and a laser beam is emitted from the laser emitter to the surface of the shell. After the laser is reflected back to the receiver, the system calculates the three-dimensional coordinate position of the shell according to the reflected signal. After the electrical connector shell is determined, the shell structure sealing detection is performed. The helium mass spectrometry leak detection technology is used for sealing detection. This technology uses helium as a tracer gas, which has the characteristics of small molecular diameter and high sensitivity, and can effectively detect small leaks. During the detection process, the electrical connector shell is first placed in the sealing detection cavity, and the cavity is pumped to a vacuum degree of 1.0×10-3 Pa by a vacuum pump. Then, the shell is filled with helium, and the filling pressure is set to 0.1 MPa. After the helium is filled, the filling valve is closed, and the helium mass spectrometry leak detector is started, and the detection sensitivity is set to 1.0×10-3 Pa·L / s. The helium mass spectrometry leak detector evaluates the sealing performance of the shell by detecting the leakage amount of helium 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 sealing standard, when the leakage rate exceeds 1.0×10-3 Pa·L / s, it is determined that the shell sealing performance is unqualified. After the detection is completed, the system automatically generates the shell structure sealing degree value, which is expressed in the form of leakage rate, and the unit is Pa·L / s. -8 -6

[0087] Step S5: based on the connector material deformation degree value and the shell structure sealing degree value, the performance of the electrical connector is evaluated to obtain electrical connector performance data; the service life of the electrical connector is predicted through the electrical connector performance data to generate an electrical connector service life prediction report.

[0088] In the embodiment of the present application, the connector material deformation degree value measured in step S3 and the shell structure sealing degree value measured in step S4 are first obtained. The connector material deformation degree value is expressed in percentage, for example, 12%, which means that the material deformation degree of this area exceeds 12% of the normal range; the shell structure sealing degree value is expressed in the form of leakage rate, for example, 1.5×10-3 Pa·L / s, which means that the leakage rate of the shell exceeds the standard value. -6

[0089] ​​​Next, these two parameters are comprehensively evaluated. For the connector material deformation value, it is compared with the standard value of 10%. If the actual measured deformation value is greater than 10%, the material deformation is considered to have a negative impact on the electrical connector performance. For the housing structure sealing value, it is compared with the standard value of 1.0 × 10⁻⁶. -6 Compare with Pa·m³ / s. If the actual measured leakage rate is greater than 1.0 × 10⁻⁶, the leakage rate will be lower. -6 If the pressure is measured in Pa·m³ / s, the housing seal is considered to have a negative impact on the electrical connector performance. Based on the above comparison results, the performance status of the electrical connector is determined. If both the material deformation value and the housing seal value are within the standard range, the electrical connector is considered to have good performance; if one or both parameters exceed the standard range, the electrical connector performance is evaluated accordingly based on the degree of exceedance. After completing the performance evaluation, the lifespan of the electrical connector is predicted based on the evaluation results. If the electrical connector performs well, its predicted lifespan is close to the ideal lifespan of the electrical connector, i.e., 10 years. If the electrical connector performance has defects, the predicted lifespan is adjusted accordingly based on the severity of the defects. For example, if the material deformation value exceeds the standard range by 2%, the predicted lifespan is reduced by 2%; if the housing seal value exceeds the standard range by 0.5 × 10⁻⁶, the predicted lifespan is reduced by 2%. -6 If the pressure is increased to Pa·m³ / s, the predicted lifespan is further reduced by 0.5%. This method comprehensively considers the impact of material deformation and housing sealing on the electrical connector's lifespan, resulting in the final predicted lifespan. Finally, the performance evaluation results and predicted lifespan of the electrical connector are compiled into a report. The report details the connector's serial number, testing date, material deformation level, housing sealing level, performance evaluation results, and predicted lifespan to ensure accurate assessment and management of the connector's lifespan.

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

[0091] Step S11: Divide the electrical connector contacts into monitoring zones. Starting from the beginning of the electrical connector contact, the first 1 / 3 of the contact's total length is marked as the front monitoring zone; the portion from 1 / 3 to 2 / 3 of the contact's total length is marked as the middle monitoring zone; and the portion from 2 / 3 of the contact's total length to the end is marked as the rear monitoring zone.

[0092] Step S12: Collect contact resistance values ​​sequentially in the front-end monitoring area, the middle monitoring area, and the back-end monitoring area according to the set time intervals; wherein, the set time intervals are set to pause for 1 minute after the first collection, pause for 2 minutes after the second collection, and pause for 3 minutes after the third collection, and each pause time is increased by 1 minute compared to the previous one;

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

[0094] Step S14: Determine the slope of the resistance change trend based on the trend of the average resistance of the area. If the slope of the resistance change trend is greater than the preset slope of the resistance change trend, it is judged as a sudden change in the contact resistance value.

[0095] Step S15: When the contact resistance value changes abruptly, the monitoring area of ​​the electrical connector contact is mapped out, and this monitoring area is recorded as the initial location of the abnormality.

[0096] In this embodiment of the invention, the electrical connector contacts are first divided into monitoring zones. A high-precision measuring tool, such as a laser rangefinder, is used to accurately measure the total length of the electrical connector contacts. Assuming the total length of the contacts is 300 mm, starting from the beginning of the contacts, a 100 mm section is marked as the front monitoring area; the section from 100 mm to 200 mm is marked as the middle monitoring area; and the section from 200 mm to the end is marked as the rear monitoring area. The boundary of each area is marked using a laser marker to ensure the accuracy of subsequent monitoring. Contact resistance values ​​are collected sequentially at set time intervals in the front, middle, and rear monitoring areas. A high-precision four-wire resistance meter is used, with a measurement accuracy reaching the micro-ohm level. The meter's two current input lines and two voltage measurement lines are connected to both ends of each monitoring area to ensure measurement accuracy. The data acquisition process is as follows:

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

[0098] Pause for 1 minute: After the data acquisition is completed, the measuring instrument will automatically enter a pause state and wait for 1 minute before conducting the second data acquisition.

[0099] Second data acquisition: A second contact resistance value acquisition was conducted in each monitoring area, and the measured value was recorded.

[0100] Pause for 2 minutes: After the data acquisition is completed, the measuring instrument will pause again and wait for 2 minutes before the third data acquisition.

[0101] Third data acquisition: A third contact resistance value acquisition is performed in each monitoring area, and the measured value is recorded.

[0102] Pause for 3 minutes: After data acquisition is complete, the measuring instrument enters a pause state and waits for 3 minutes. Each pause time is increased by 1 minute compared to the previous one to ensure the stability and reliability of the measurement data.

[0103] The collected contact resistance values ​​are processed. The contact resistance values ​​for each monitoring area are recorded in three consecutive acquisitions. For example, the three acquisition values ​​for the front-end monitoring area are 0.5 μΩ, 0.6 μΩ, and 0.7 μΩ, respectively. The average value for each monitoring area is calculated, i.e., the trend of the average resistance value change. For the front-end monitoring area, the average value is (0.5 + 0.6 + 0.7) / 3 = 0.6 μΩ. The average values ​​for the middle and rear monitoring areas are calculated using the same method. The slope of the resistance change trend is determined based on the trend of the average resistance value change. The slope of the resistance change trend is obtained by calculating the difference between two adjacent acquisitions of resistance value and dividing by the time interval. For example, the slope of the resistance change trend for the front-end monitoring area is (0.6 - 0.5) / 1 + (0.7 - 0.6) / 2 = 0.1 + 0.05 = 0.15 μΩ / min. The preset slope of the resistance change trend is 0.1 μΩ / min. The calculated slope of the resistance change trend is compared with the preset value. If the slope of the resistance change trend is greater than the preset slope, for example, 0.15 microohms / minute in the front-end monitoring area is greater than the preset 0.1 microohms / minute, it is judged as a sudden change in contact resistance value. When the contact resistance value changes abruptly, the monitoring area of ​​the electrical connector contact is mapped through the marking information of the monitoring area, and this monitoring area is recorded as the initial point of the anomaly. The recorded content includes the location of the monitoring area (front end, middle end, or rear end), the slope of the resistance change trend, and the specific resistance value change, for subsequent further analysis and processing.

[0104] Preferably, step S2, which involves acquiring an image of the electrical connector surface based on the abnormal initial location, includes:

[0105] Based on the initial location of the anomaly, images of the electrical connector surface are acquired using a high-resolution industrial camera with a resolution of no less than 1024×768 pixels.

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

[0107] The acquired surface image is converted to grayscale; the grayscale image is then subjected to median filtering with a window size of 3×3 pixels; and the filtered image is then subjected to edge enhancement processing to obtain the surface image of the electrical connector.

[0108] In this embodiment of the invention, based on the abnormal initial location, the electrical connector is placed on a dedicated fixed bracket, ensuring that the surface of the electrical connector is perpendicular to the camera lens. A high-resolution industrial camera with a resolution of 1024×768 pixels is used to acquire images of the electrical connector surface, ensuring that the acquired images have sufficient detail. The distance between the camera and the electrical connector surface is adjusted to be between 10 cm and 20 cm, with the specific distance optimized according to the size of the electrical connector and the focal length of the camera to ensure image clarity and coverage. Before acquiring images, the camera parameters are set. The camera aperture is adjusted to F8 to obtain a larger depth of field, ensuring that all parts of the electrical connector surface are clearly imaged. At the same time, the camera's ISO value is set to 100 to reduce image noise and improve image quality. A uniform ring LED light source is used to illuminate the electrical connector surface, and the brightness of the light source is adjusted to 70% to ensure that the image brightness is moderate and uniform. After completing the above settings, the camera is started to acquire images. The acquired color image is first transmitted to the image processing unit for grayscale processing. Grayscale conversion transforms the RGB values ​​of each pixel in a color image into grayscale values ​​using the formula: Grayscale value = 0.299 × R + 0.587 × G + 0.114 × B. This weighted averaging method converts the color image to grayscale, reducing data volume and simplifying subsequent processing. Next, median filtering is applied to the grayscale image to remove random noise. Median filtering uses a 3×3 pixel window, sorting the grayscale values ​​of each pixel and its eight surrounding pixels, and taking the median value as the new grayscale value for that pixel. This non-linear filtering method effectively removes salt-and-pepper noise while preserving edge information. Finally, edge enhancement is performed on the filtered image. Edge enhancement highlights edge information by calculating the gradient magnitude of each pixel. Specifically, for each pixel, the grayscale difference between it and its surrounding pixels is calculated. If the difference exceeds a set threshold of 10, the grayscale value of that pixel is enhanced to be closer to 255 (white), thus highlighting the edge. This process yields a clear image of the electrical connector surface, providing a high-quality image foundation for subsequent defect detection and analysis.

[0109] Preferably, step S2, which involves detecting contact surface wear and scratches in the electrical connector surface image, identifying connector defects on the contact surface, and marking them as connector structural defect areas, includes:

[0110] The surface image of the electrical connector is divided into multiple image detection regions of equal area; within each image detection region, the gradient of grayscale value change is calculated to identify the boundary of the wear area on the contact surface; the area of ​​the wear area on the contact surface within each image detection region is counted to calculate the total wear area on the contact surface.

[0111] Linear features of the image are identified within each image detection area and marked as scratches; the length and width of each scratch are measured, and the total number of scratches on the contact surface within each image detection area is counted.

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

[0113] If the total wear area of ​​the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5 within the potential connector structural defect area, then the potential connector structural defect area is marked as a connector structural defect area.

[0114] In this embodiment of the invention, the surface image of the electrical connector is divided into multiple image detection regions of equal area. Assuming the image resolution is 1024×768 pixels, the image is divided into 16×12 detection regions, each with a size of 64×64 pixels. Image segmentation technology is used to uniformly segment the image through coordinate positioning, ensuring that the area of ​​each detection region is equal. Within each image detection region, the gradient of grayscale value change is calculated. By calculating the grayscale difference between adjacent pixels, the boundary of the wear area on the contact surface is identified. Specifically, for each pixel within each detection region, the grayscale difference between it and its 8 surrounding pixels is calculated. If the difference exceeds a set threshold of 10, the pixel is considered to be located at the boundary of the wear area. In this way, the boundary of the wear area within each detection region is identified. The area of ​​the wear area on the contact surface within each image detection region is counted to calculate the total wear area of ​​the contact surface. Pixels within the boundary of the wear area in each detection region are counted, and the count result is multiplied by the area of ​​each pixel (assuming the area of ​​each pixel is 0.01 square millimeters) to obtain the area of ​​the wear area within each detection region. The total wear area of ​​the electrical connector surface is obtained by summing the areas of the wear regions within all detection areas. Linear features in each image detection area are identified and marked as scratches. Linear features are identified by calculating the gradient direction and magnitude of each pixel. If the gradient direction of a pixel changes continuously and the gradient magnitude exceeds a set threshold of 20, the pixel is considered a scratch. Each scratch is tracked until its end to identify complete scratches. The length and width of each scratch are measured. The length of the scratch is obtained by calculating the Euclidean distance between its two endpoints, and the width is obtained by multiplying the number of pixels at the widest point of the scratch by the width of each pixel. The total number of scratches on the contact surface within each image detection area is counted. The positional relationship between the wear area and the scratches on the contact surface is analyzed. If a scratch crosses a wear area and its length exceeds 1 mm, the image detection area is marked as a potential connector structural defect area. The specific operation is as follows: For each scratch within each inspection area, check whether it intersects with the boundary of the wear area. If they intersect and the scratch length exceeds 1 mm, then the inspection area is marked as a potential connector structural defect area. Within a potential connector structural defect area, if the total wear area of ​​the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5, then the potential connector structural defect area is marked as a connector structural defect area. Specifically, for each potential connector structural defect area, check whether its total wear area exceeds 10 square millimeters and whether the total number of scratches exceeds 5. If both conditions are met simultaneously, then the area is marked as a connector structural defect area, and its location and related information are recorded.

[0115] Preferably, step S3, which involves performing an overall physical hardness test on the defective area of ​​the connector structure, includes:

[0116] Within the defective area of ​​the connector structure, multiple hardness testing points are selected at equal intervals of 1 mm, and the hardness testing points are set in a grid pattern.

[0117] At each hardness testing point, the probe of the hardness testing device is brought into contact with the surface of the electrical connector, and the hardness value after the probe applies pressure is recorded.

[0118] Three hardness tests were performed at each hardness test point, with a 10-second interval between each test.

[0119] The average value of the three test results is taken as the connector hardness at that hardness test point.

[0120] Record the connector hardness at each hardness test point in a data table and mark the coordinates of the test points.

[0121] In this embodiment of the invention, within the defect area of ​​the connector structure, a high-precision positioning device, such as a laser positioning instrument, is used to select multiple hardness testing points at equal intervals of 1 mm, and these points are arranged in a grid pattern. Assuming the defect area is a rectangular region, 10 mm long and 5 mm wide, 10 × 5 = 50 hardness testing points are set within this area, forming a grid-like array of testing points. At each hardness testing point, the probe of the hardness testing device is precisely aligned with the surface of the electrical connector. The hardness testing device uses a Vickers hardness tester, whose probe is a diamond pyramid shape. The probe is gently brought into contact with the surface of the electrical connector, ensuring good contact and no external interference. The load of the hardness tester is set to 10 grams of force, and the loading time is 10 seconds. After the probe applies pressure, the hardness tester automatically records the hardness value, in Vickers hardness (HV). Three hardness tests are performed at each hardness testing point. After the first test, the hardness tester automatically records the first hardness value; then, after waiting 10 seconds, a second test is performed, and the second hardness value is recorded; after waiting another 10 seconds, a third test is performed, and the third hardness value is recorded. Ensure a 10-second interval between each test to guarantee the stability and accuracy of the results. Take the average of the three test results as the connector hardness value for that test point. Specifically, add the hardness values ​​from the first, second, and third tests, then divide by 3 to obtain the average hardness value for that test point. For example, if the three test values ​​for a certain test point are 250HV, 252HV, and 248HV respectively, then the connector hardness value for that test point is (250+252+248) / 3 = 250HV. Record the connector hardness value for each hardness test point in a data table, marking the coordinates of the test point. The data table includes the test point number, coordinates (X and Y coordinates, in millimeters), and the corresponding connector hardness value. For example, test point number 1, coordinates (1 mm, 1 mm), connector hardness value 250HV. In this way, all hardness test point data are completely recorded for subsequent analysis and processing.

[0122] Preferably, step S3, which involves detecting the deformation of the electrical connector material in areas of abnormal connector hardness, includes:

[0123] In areas of abnormal connector hardness, tensile and compressive forces are applied to the surface of the electrical connector, and the strain distribution on the material surface is recorded to obtain surface strain distribution data.

[0124] Based on the surface strain distribution data, strain concentration areas are identified. Within these strain concentration areas, multiple material deformation detection points are selected, with the spacing between each detection point set to 0.5 mm.

[0125] Material deformation is detected at each material deformation detection point, and the displacement deviation of the electrical connector material surface under applied tensile and compressive forces is measured; the degree of connector material deformation is determined based on the displacement deviation.

[0126] In this embodiment of the invention, in areas of abnormal connector hardness, tensile and compressive forces are first applied to the surface of the electrical connector using a high-precision mechanical testing device. This testing device can precisely control the magnitude and direction of the applied forces, ensuring the stability and repeatability of the experimental conditions. The tensile and compressive forces are set to 100 Newtons and -100 Newtons, respectively, and the application speed is set to 1 mm / min. During the application of forces, a strain measurement system is used to record the strain distribution on the material surface. This system employs high-precision strain gauges with measurement accuracy reaching the micro-strain level. The strain measurement system acquires strain data by attaching strain gauges to the surface of the electrical connector. The strain gauges are arranged in a grid pattern, with a spacing of 1 mm between each gauge, ensuring complete coverage of the abnormal hardness area. During the application of tensile and compressive forces, the strain measurement system records the strain value of each strain gauge in real time, obtaining surface strain distribution data. This data is stored in the form of digital signals in a data acquisition system for subsequent analysis. Based on the surface strain distribution data, strain concentration areas are identified. By analyzing the strain data, areas where the strain value exceeds a preset threshold (e.g., 100 micro-strain) are identified and marked as strain concentration areas. Within the strain concentration area, multiple material deformation detection points are selected, with a spacing of 0.5 mm between each point. High-precision displacement measurement equipment, such as a laser displacement sensor, is used to detect material deformation at each point. Before measuring each point, the laser displacement sensor probe is aligned with the point, ensuring a distance of 10 mm between the probe and the point. During the application of tensile and compressive forces, the laser displacement sensor measures the displacement deviation of the connector material surface under the applied forces in real time. The measurement accuracy of the displacement deviation reaches the micrometer level, ensuring data accuracy. After each measurement, the displacement deviation data is recorded in a data table, which includes the detection point number, coordinate position (X and Y coordinates, in millimeters), and the corresponding displacement deviation. The degree of connector material deformation is determined based on the displacement deviation. Specifically, the displacement deviation at each detection point is compared with the magnitude of the applied force. For example, assuming an applied tensile force of 100 Newtons corresponds to a displacement deviation of 0.1 mm, the deformation degree at that detection point is 0.1 mm / 100 Newtons. In this way, the deformation degree value of each detection point is calculated and the results are recorded in a data table for further analysis and processing.

[0127] Of particular importance is the measurement of material deformation at each material deformation detection point, including the displacement of the electrical connector material surface under applied tensile and compressive forces.

[0128] A tensile force of 10 Newtons was applied to each material deformation detection point for 10 seconds.

[0129] While applying tensile force, the displacement deviation at each material deformation detection point is measured using a displacement sensor;

[0130] For each material deformation detection point, three tensile forces were applied and displacement measurements were taken. The average value of the three measurements was taken as the displacement deviation of the material deformation detection point under tensile force.

[0131] A compressive force of 20 Newtons is applied to each detection point for 20 seconds;

[0132] While applying compressive force, the displacement deviation at each material deformation detection point is measured using a displacement sensor;

[0133] For each material deformation detection point, tensile force was applied and displacement was measured three times. The average value of the three measurements was taken as the displacement deviation of the material deformation detection point under compressive force.

[0134] In this embodiment of the invention, when performing material deformation detection, a high-precision mechanical testing device is first 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. Simultaneously with the application of the tensile force, a high-precision laser displacement sensor measures the displacement deviation at each material deformation detection point. The laser displacement sensor has a measurement accuracy at the micrometer level, ensuring data accuracy. The distance between the displacement sensor probe and the detection point is maintained at 10 millimeters to ensure measurement stability and accuracy. Tensile force is applied and displacement is measured three times for each material deformation detection point. After the first application of tensile force, the displacement deviation measured by the displacement sensor is recorded; then, after a 10-second wait, the tensile force is applied a second time, and the displacement deviation is recorded again; after another 10 seconds, the tensile force is applied a third time, and the displacement deviation is recorded the third time. The interval between each application of tensile force is ensured to be 10 seconds to guarantee the stability and repeatability of the measurement results. The average of the three measurement results is taken as the displacement deviation of the material deformation detection point under tensile force. For example, if the three displacement deviations at a certain detection point are 0.05 mm, 0.06 mm, and 0.04 mm, respectively, then the displacement deviation of that detection point under tensile force is (0.05 + 0.06 + 0.04) / 3 = 0.05 mm. 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 using a laser displacement sensor. Similarly, three compression force applications and displacement measurements are performed for each detection point. After the first application of the compressive force, the displacement deviation measured by the displacement sensor is recorded; then, after waiting 20 seconds, the second application of the compressive force is performed, and the displacement deviation is recorded again; after waiting another 20 seconds, the third application of the compressive force is performed, and the third displacement deviation is recorded. The interval between each application of the compressive force is ensured to be 20 seconds to guarantee the stability and repeatability of the measurement results. The average of the three measurement results is taken as the displacement deviation of the material deformation detection point under compressive force. For example, if the three displacement deviations of a certain detection point are -0.1 mm, -0.12 mm and -0.08 mm respectively, then the displacement deviation of the detection point under compressive force is (-0.1 + -0.12 + -0.08) / 3 = -0.1 mm. Through the above steps, the displacement deviation of each material deformation detection point under tensile and compressive forces can be obtained.

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

[0136] Step S41: Determine the center coordinates of the defective area in the connector structure and convert them into the actual physical coordinates of the electrical connector housing. Determine the corresponding electrical connector housing based on the actual physical coordinates.

[0137] Step S42: Place the electrical connector housing on the test platform of the sealing tester and balance the internal air pressure of the housing with the external ambient air pressure;

[0138] Step S43: Apply a constant, minute air pressure of 0.1 Pa to the inside of the electrical connector housing for 30 seconds;

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

[0140] Step S45: Calculate the shell pressure change rate based on the pressure change curve, determine the shell structure sealing based on the shell pressure change rate, and generate the shell structure sealing degree value.

[0141] In this embodiment of the invention, a high-precision image processing system is used to determine the center coordinates of the connector structural defect area. Image analysis software is used to process the surface image of the electrical connector, identify the boundary of the structural defect area, and calculate its center coordinates. Assuming the image resolution is 1024×768 pixels, the center coordinates of the defect area in the image are (512, 384) pixels. These image coordinates are then converted to the actual physical coordinates of the electrical connector housing. Assuming each pixel in the image corresponds to an actual physical size of 0.1 mm, the center coordinates are converted to (51.2 mm, 38.4 mm). Based on the actual physical coordinates, the specific location of the electrical connector housing corresponding to the defect area is determined. The electrical connector housing is placed on the test platform of the sealing tester. A high-precision positioning device is used to ensure that the center of the housing is aligned with the center of the test platform. Before placing the housing, a pressure balancing device is used to adjust the internal air pressure of the housing to match the external ambient air pressure. By connecting the internal air pressure sensor and the external ambient air pressure sensor, the internal air pressure of the housing is monitored and adjusted until the pressure difference between the inside and outside is less than 0.01 Pa, ensuring pressure balance. After the internal air pressure of the casing is balanced with the external ambient air pressure, a constant, minute air pressure is applied to the inside of the casing using a sealing detector. A high-precision air pressure controller is used to raise the internal air pressure to 0.1 Pa and maintain this pressure value for 30 seconds. The air pressure controller has an accuracy of 0.001 Pa to ensure the applied air pressure is accurate and stable. After the air pressure is applied, a high-precision air pressure sensor is used to monitor changes in the internal air pressure. The air pressure sensor's sampling frequency is set to 10 times / second to ensure accurate recording of real-time air pressure changes. Data from the air pressure rise, stabilization, and fall phases are recorded to generate an air pressure change curve. The air pressure change curve includes three phases: Air pressure rise phase: recording the rise from the initial air pressure to 0.1 Pa; Air pressure stabilization phase: recording data during the 30 seconds the air pressure remains at 0.1 Pa; Air pressure fall phase: recording the fall from 0.1 Pa back to the initial air pressure. Based on the air pressure change curve, the air pressure change rate of the casing is calculated. The rate of change of air pressure is determined by calculating the rate of decrease in air pressure during the steady-state phase. Specifically, during the steady-state phase, the time required for the air pressure to decrease from 0.1 Pascals to 0.09 Pascals is recorded. Assuming this time is 10 seconds, the rate of change is (0.1 - 0.09) / 10 = 0.001 Pascals / second. Based on the rate of change of air pressure in the casing, the sealing degree of the casing structure is determined. The preset threshold for the rate of change of air pressure is 0.0005 Pascals / second. If the calculated rate of change of air pressure exceeds this threshold, the casing sealing performance is deemed unqualified; if the rate of change of air pressure is lower than or equal to this threshold, the casing sealing performance is deemed qualified. The rate of change of air pressure is recorded as the sealing degree value of the casing structure, in Pascals / second.For example, if the rate of change of air pressure is 0.001 Pascals per second, then the sealing degree of the shell structure is 0.001 Pascals per second, indicating that the shell sealing performance is unqualified.

[0142] Of particular importance, step S45 includes the following steps:

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

[0144] Step S452: Divide the pressure difference by the time interval to obtain the pressure change rate during that time period;

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

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

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

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

[0149] In this embodiment of the invention, two adjacent time points, such as t1 and t2, are first selected from the pressure change curve, where t1 is 1 second and t2 is 2 seconds. The corresponding pressure values ​​at these two time points are recorded. It is assumed that the pressure at time t1 is 0.105 Pascals (Pa) and the pressure at time t2 is 0.103 Pascals (Pa). The pressure difference between these two time points is calculated as ΔP = P(t2) - P(t1) = 0.103 - 0.105 = -0.002 Pascals (Pa). In step S452, the pressure difference is divided by the time interval to obtain the pressure change rate within that time interval. The time interval Δt = t2 - t1 = 2 - 1 = 1 second. Therefore, the pressure change rate ΔP / Δt = -0.002 Pa / 1s = -0.002 Pascals / second (Pa / s). This pressure change rate is recorded in a data table, with the corresponding time point being t1. In step S453, steps S451 to S452 are repeated to calculate the air pressure change rate over the entire monitoring period. Assuming the monitoring period is 30 seconds, adjacent time points are selected sequentially at 1-second intervals to calculate the air pressure change rate for each time period and record the rate at each time point. For example, for time points t2 and t3 (t3 being 3 seconds), assuming the air pressures are 0.103 Pa and 0.101 Pa respectively, the pressure difference is -0.002 Pa, and the air pressure change rate is -0.002 Pa / s. The corresponding time point recorded in the data table is t2. This process continues until the air pressure change rate for all time points has been calculated. In step S454, the air pressure change rate for each time point is categorized, and its corresponding sealing level is recorded. 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 level is A; if the air pressure change rate is between 0.05 Pa / s and 0.1 Pa / s, the sealing level is B; and if the air pressure change rate is greater than 0.1 Pa / s, the sealing level is C. For example, the air pressure change rate at time point t1 is -0.002 Pa / s, which belongs to level A; the air pressure change rate at time point t2 is also -0.002 Pa / s, which also belongs to level A. The air pressure change rate and its corresponding sealing level at each time point are recorded in a data table. In step S455, the air pressure change rate at all time points is statistically analyzed to calculate the average air pressure change rate. The air pressure change rates at all time points are added together and then divided by the total number of time points. Assuming that 30 pressure change rates are calculated within 30 seconds, and their sum is -0.06 Pa / s, then the average pressure change rate is -0.06 Pa / s ÷ 30 = -0.002 Pa / s. In step S456, the overall sealing degree of the shell structure is determined based on the average pressure change rate.According to the preset standards: if the average pressure change rate is less than 0.05 Pa / s, the sealing degree of the shell structure is 100%; if the average pressure change rate is between 0.05 Pa / s and 0.1 Pa / s, the sealing degree of the shell structure is 50%; if the average pressure change rate is greater than 0.1 Pa / s, the sealing degree of the shell structure is 0%.

[0150] Preferably, step S5, which evaluates the performance of the electrical connector based on the deformation value of the connector material and the sealing value of the housing structure, includes:

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

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

[0154] The performance judgment values ​​of electrical connectors are divided into performance value ranges, and the performance data of electrical connectors are determined based on the performance value ranges.

[0155] In this embodiment of the invention, when evaluating the performance of the electrical connector, the material deformation value is processed first. Assuming the measured material deformation value is 0.08 mm and the preset maximum deformation value is 0.1 mm, the material deformation value of 0.08 mm is divided by the preset maximum deformation value of 0.1 mm to obtain a material deformation ratio of 0.8. Then, 1 is subtracted from this material deformation ratio of 0.8 to obtain a material deformation influence factor of 0.2. Next, the housing structure sealing value is processed. Assuming the measured housing structure sealing value is 0.003 Pascals / second and the preset maximum sealing value is 0.1 Pascals / second, the housing structure sealing value of 0.003 Pascals / second is divided by the preset maximum sealing value of 0.1 Pascals / second to obtain a housing sealing influence factor of 0.03. Then, weight allocation and comprehensive calculation are performed. The material deformation influence factor of 0.2 is multiplied by a weighting coefficient of 0.6 to obtain 0.12. The housing sealing influence factor of 0.03 is multiplied by a weighting coefficient of 0.4 to obtain 0.012. Adding these two results together, 0.12 plus 0.012, yields the electrical connector performance assessment value of 0.132. Finally, the performance assessment value is divided into performance ranges. The preset performance range division standard is: when the performance assessment value is greater than or equal to 0.9, the electrical connector performance data is "Excellent"; when the performance assessment value is between 0.5 and 0.9, the electrical connector performance data is "Good"; when the performance assessment value is less than 0.5, the electrical connector performance data is "Poor". According to the above standard, the electrical connector performance assessment value of 0.132 falls within the "Poor" performance range, therefore the electrical connector performance data is determined to be "Poor".

[0156] Preferably, the step S5 of predicting the lifespan of the electrical connector using electrical connector performance data includes:

[0157] The performance range of electrical connectors is determined based on their performance data. If the performance data is greater than or equal to 0.8, it is identified as a high-performance range; if the performance data is between 0.5 and 0.8, it is identified as a medium-performance range; and if the performance data is less than 0.5, it is identified as a low-performance range.

[0158] For the high-performance range, the predicted remaining percentage of electrical connector life is 80%; for the medium-performance range, the predicted remaining percentage is 50%; and for the low-performance range, the predicted remaining percentage is 20%.

[0159] Draw a distribution map of the predicted lifespan of the electrical connector in the corresponding area and output a report on the predicted lifespan of the electrical connector.

[0160] In this embodiment of the invention, after analyzing the performance data of the electrical connector, the performance data is classified according to a preset performance range classification standard. Assuming the electrical connector performance data is 0.75, according to the classification standard, if the electrical connector performance data is greater than or equal to 0.8, it is determined to be in the high-performance range; if the electrical connector performance data is between 0.5 and 0.8, it is determined to be in the medium-performance range; and if the electrical connector performance data is less than 0.5, it is determined to be in the low-performance range. Since 0.75 falls between 0.5 and 0.8, this electrical connector performance data is determined to be in the medium-performance range. For the medium-performance range, according to a preset lifespan prediction standard, the remaining percentage of electrical connector lifespan in this area is predicted to be 50%. Using high-precision drawing software, a distribution map of the electrical connector lifespan prediction is drawn in the corresponding area of ​​the electrical connector. During the drawing process, the location of each area is accurately marked according to the structure and size of the electrical connector, and different colors or patterns are used to distinguish them according to their performance range. For example, green is used to represent the high-performance range, yellow to represent the medium-performance range, and red to represent the low-performance range. In the area corresponding to the medium-performance range, the remaining lifespan percentage of 50% is marked. After completing the drawing, an electrical connector lifespan prediction report is generated. The report details the connector's serial number, testing date, performance data, and corresponding performance range. It also includes a lifespan prediction distribution map, clearly showing the performance status and lifespan prediction results for different regions. For connectors in the mid-performance range, the report explicitly states their remaining lifespan percentage is 50% and provides corresponding maintenance recommendations, such as regular inspections and timely replacement, to ensure the reliability and safety of the connectors.

[0161] The following experimental data illustrates the mapping relationship between electrical connector performance data and remaining lifespan percentage:

[0162] Experimental Sample Preparation: 150 samples were randomly selected from electrical connectors of the same batch and specifications. These samples underwent rigorous quality testing at the factory, exhibiting consistent performance and the same initial lifespan expectation. These samples were divided into three groups of 50 each, and used for accelerated life testing under different operating environments to simulate the performance degradation and lifespan depletion process of electrical connectors under actual working conditions.

[0163] Accelerated life test design: The first group of samples was placed in a high-temperature and high-humidity environment, with a temperature set at 75℃ and humidity at 95% RH. This environment accelerates the aging of the insulation material and oxidation of the contacts in the electrical connector. The second group of samples was placed in a mechanical vibration environment with a vibration frequency of 55Hz and an acceleration of 15g, simulating the mechanical shock of the electrical connector during transportation or equipment operation. The third group of samples was placed in a high-frequency electromagnetic interference environment with an electromagnetic interference intensity of 15V / m and a frequency range of 200MHz to 3.5GHz, simulating the performance changes of the electrical connector under complex electromagnetic environments. Each group of samples underwent accelerated life tests for 1000 hours, 2000 hours, and 3000 hours in their respective environments, for a total of 9 operating condition combinations. Each operating condition combination corresponded to 17 samples (some samples were used as backups).

[0164] Performance data acquisition and processing:

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

[0166] Contact resistance: The four-terminal method is used for measurement to avoid the influence of lead resistance on the measurement results.

[0167] Insulation resistance: The resistance of the insulating part of the electrical connector at the rated voltage is measured by a high resistance meter.

[0168] The collected raw performance parameters are normalized using a data processing algorithm, converting them into performance data between 0 and 1. The normalization formula is:

[0169]

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

[0171]

[0172] Calculation and Mapping Relationship Verification of Remaining Life Percentage: After the accelerated life test, a life assessment is performed on each sample. Based on the theoretical formula for accelerated life testing, the equivalent life consumption percentage of each sample under actual operating conditions is calculated. The formula for calculating the equivalent life under accelerated life testing is:

[0173]

[0174] Where t is the accelerated life test time, and τ is the acceleration factor, calculated according to the Arrhenius equation. For high temperature and high humidity environments, the relationship between the acceleration factor τ and temperature and humidity is as follows:

[0175]

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

[0177]

[0178] Mapping relationship verification:

[0179] The experimental data shows that when the performance data is greater than or equal to 0.8, the remaining lifespan percentage is mostly between 80% and 84%, which is close to the predicted value of 80%.

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

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

[0182] Statistical analysis showed that the errors between the experimental and predicted values ​​were within the allowable range, verifying the rationality of the mapping relationship between the electrical connector performance data and the remaining lifespan percentage.

[0183] This specification also provides an electrical connector life prediction system for performing the electrical connector life prediction method described above, the electrical connector life prediction system comprising:

[0184] The electrical performance monitoring module is used to continuously monitor the electrical performance of the electrical connector contacts. When a change in the contact resistance value is detected, it is recorded as the initial point of abnormality.

[0185] The surface image acquisition and recognition module is used to acquire surface images of electrical connectors based on abnormal initial sites; detect wear and scratches on the contact surface of the electrical connector surface images, identify connector defects on the contact surface, and mark them as connector structural defect areas;

[0186] The hardness deformation detection module is used to perform physical hardness detection on the defective areas of the connector structure 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 judged as an abnormal area of ​​connector hardness; perform electrical connector material deformation detection on the abnormal area of ​​connector hardness to generate a connector material deformation degree value.

[0187] The housing structure sealing detection module is used to determine the corresponding electrical connector housing based on the defect area of ​​the connector structure; to perform housing structure sealing detection on the electrical connector housing, and to generate a housing structure sealing degree value;

[0188] The electrical connector life prediction module is used to evaluate the performance of electrical connectors based on the deformation value of connector materials and the sealing value of the housing structure, and obtain electrical connector performance data; the electrical connector life is predicted based on the electrical connector performance data to generate an electrical connector life prediction report.

[0189] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0190] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for predicting the lifespan of an electrical connector, characterized in that, Includes the following steps: Step S1: Continuously monitor the electrical performance of the electrical connector contacts. When a change in contact resistance is detected, record it as the initial point of abnormality. Step S2: Acquire surface images of the electrical connector based on the abnormal initial location; Detect contact surface wear and scratches in electrical connector surface images, identify connector defects on the contact surface, and mark them as connector structural defect areas; Step S3: Perform overall physical hardness testing on the defective area of ​​the connector structure to obtain the overall hardness of the connector area; Identify and record areas of abrupt hardness changes in the overall hardness of the connector area as areas of abnormal connector hardness. The deformation of the connector material in areas of abnormal connector hardness is detected, and the degree of connector material deformation is generated. Step S4: Determine the corresponding electrical connector housing based on the defective area of ​​the connector structure; Perform a housing structure sealing test on the electrical connector housing and generate a housing structure sealing degree value; Step S5: Evaluate the performance of the electrical connector based on the deformation value of the connector material and the sealing value of the housing structure to obtain the performance data of the electrical connector; Predict the lifespan of electrical connectors using their performance data to generate an electrical connector lifespan prediction report.

2. The method for predicting the lifespan of an electrical connector according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Divide the electrical connector contacts into monitoring zones. Starting from the beginning of the electrical connector contact, the first 1 / 3 of the contact's total length is marked as the front monitoring zone; the portion from 1 / 3 to 2 / 3 of the contact's total length is marked as the middle monitoring zone; and the portion from 2 / 3 of the contact's total length to the end is marked as the rear monitoring zone. Step S12: Collect contact resistance values ​​sequentially in the front-end monitoring area, the middle monitoring area, and the back-end monitoring area according to the set time intervals; wherein, the set time intervals are set to pause for 1 minute after the first collection, pause for 2 minutes after the second collection, and pause for 3 minutes after the third collection, and each pause time is increased by 1 minute compared to the previous one; Step S13: Process the collected contact resistance values, calculate the average value of each monitoring area in three consecutive collections, and obtain the trend of the average resistance value of the area. Step S14: Determine the slope of the resistance change trend based on the trend of the average resistance of the area. If the slope of the resistance change trend is greater than the preset slope of the resistance change trend, it is judged as a sudden change in the contact resistance value. Step S15: When the contact resistance value changes abruptly, the monitoring area of ​​the electrical connector contact is mapped out, and this monitoring area is recorded as the initial location of the abnormality.

3. The method for predicting the lifespan of an electrical connector according to claim 1, characterized in that, Step S2, which involves acquiring surface images of the electrical connector based on abnormal initial sites, includes: Based on the initial location of the anomaly, images of the electrical connector surface are acquired using a high-resolution industrial camera with a resolution of no less than 1024×768 pixels. Place the electrical connector on the fixed bracket, keeping the surface of the electrical connector perpendicular to the camera lens, and maintaining a distance of 10 cm to 20 cm between the camera and the surface of the electrical connector; The acquired surface image is converted to grayscale; the grayscale image is then subjected to median filtering with a window size of 3×3 pixels; and the filtered image is then subjected to edge enhancement processing to obtain the surface image of the electrical connector.

4. The method for predicting the lifespan of an electrical connector according to claim 1, characterized in that, Step S2 involves detecting wear and scratches on the contact surface of the electrical connector in the surface image, identifying connector defects on the contact surface, and marking these as areas of connector structural defect, including: The surface image of the electrical connector is divided into multiple image detection regions of equal area; within each image detection region, the gradient of grayscale value change is calculated to identify the boundary of the wear area on the contact surface; the area of ​​the wear area on the contact surface within each image detection region is counted to calculate the total wear area on the contact surface. Linear features of the image are identified within each image detection area and marked as scratches; the length and width of each scratch are measured, and the total number of scratches on the contact surface within each image detection area is counted. Analyze the positional relationship between the wear area and the scratch on the contact surface. If the scratch passes through the wear area and the scratch length exceeds 1 mm, mark the image detection area as a potential connector structural defect area. If the total wear area of ​​the contact surface exceeds 10 square millimeters and the total number of scratches exceeds 5 within the potential connector structural defect area, then the potential connector structural defect area is marked as a connector structural defect area.

5. The method for predicting the lifespan of an electrical connector according to claim 1, characterized in that, Step S3, which involves performing an overall physical hardness test on the defective area of ​​the connector structure, includes: Within the defective area of ​​the connector structure, multiple hardness testing points are selected at equal intervals of 1 mm, and the hardness testing points are set in a grid pattern. At each hardness testing point, the probe of the hardness testing device is brought into contact with the surface of the electrical connector, and the hardness value after the probe applies pressure is recorded. Three hardness tests were performed at each hardness test point, with a 10-second interval between each test. The average value of the three test results is taken as the connector hardness at that hardness test point. Record the connector hardness at each hardness test point in a data table and mark the coordinates of the test points.

6. The method for predicting the lifespan of an electrical connector according to claim 1, characterized in that, Step S3, which involves detecting the deformation of the connector material in areas of abnormal connector hardness, includes: In areas of abnormal connector hardness, tensile and compressive forces are applied to the surface of the electrical connector, and the strain distribution on the material surface is recorded to obtain surface strain distribution data. Based on the surface strain distribution data, strain concentration areas are identified. Within these strain concentration areas, multiple material deformation detection points are selected, with the spacing between each detection point set to 0.5 mm. Material deformation is detected at each material deformation detection point, and the displacement deviation of the electrical connector material surface under applied tensile and compressive forces is measured; the degree of connector material deformation is determined based on the displacement deviation.

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

8. The method for predicting the lifespan of an electrical connector according to claim 7, characterized in that, Step S5, which evaluates the performance of the electrical connector based on the deformation value of the connector material and the sealing value of the housing structure, includes: Divide the material deformation degree value by the preset maximum deformation degree value to obtain the material deformation ratio value, and subtract the material deformation ratio value from 1 to obtain the material deformation influence factor; Divide the shell structure sealing degree value by the preset maximum sealing degree value to obtain the material deformation influence factor; Multiply the material deformation influence factor by 0.6, multiply the housing sealing influence factor by 0.4, and add the two results to generate the electrical connector performance judgment value; The performance judgment values ​​of electrical connectors are divided into performance value ranges, and the performance data of electrical connectors are determined based on the performance value ranges.

9. The method for predicting the lifespan of an electrical connector according to claim 7, characterized in that, Step S5, which predicts the lifespan of an electrical connector using its performance data, includes: The performance range of electrical connectors is determined based on their performance data. If the performance data is greater than or equal to 0.8, it is identified as a high-performance range; if the performance data is between 0.5 and 0.8, it is identified as a medium-performance range; and if the performance data is less than 0.5, it is identified as a low-performance range. For the high-performance range, the predicted remaining percentage of electrical connector life is 80%; for the medium-performance range, the predicted remaining percentage is 50%; and for the low-performance range, the predicted remaining percentage is 20%. Draw a distribution map of the predicted lifespan of the electrical connector in the corresponding area and output a report on the predicted lifespan of the electrical connector.

10. A system for predicting the lifespan of an electrical connector, characterized in that, For performing the electrical connector life prediction method as described in claim 1, the electrical connector life prediction system includes: The electrical performance monitoring module is used to continuously monitor the electrical performance of the electrical connector contacts. When a change in the contact resistance value is detected, it is recorded as the initial point of abnormality. The surface image acquisition and recognition module is used to acquire surface images of electrical connectors based on abnormal initial sites; detect wear and scratches on the contact surface of the electrical connector surface images, identify connector defects on the contact surface, and mark them as connector structural defect areas; The hardness deformation detection module is used to perform overall physical hardness detection on the structural defect area of ​​the connector to obtain the overall hardness of the connector area; identify the hardness abrupt change locations of the overall hardness of the connector area and record them as abnormal hardness areas of the connector; and perform electrical connector material deformation detection on the abnormal hardness areas of the connector to generate the deformation degree value of the connector material. The housing structure sealing detection module is used to determine the corresponding electrical connector housing based on the defect area of ​​the connector structure; to perform housing structure sealing detection on the electrical connector housing, and to generate a housing structure sealing degree value; The electrical connector life prediction module is used to evaluate the performance of electrical connectors based on the deformation value of connector materials and the sealing value of the housing structure, and obtain electrical connector performance data; the electrical connector life is predicted based on the electrical connector performance data to generate an electrical connector life prediction report.

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