Waterproof performance detection method and system for Type-C interface

Abstract

The invention discloses a waterproof performance detection method and system for a Type-C interface, and relates to the technical field of interface adapters, and the method comprises the steps: obtaining a waterproof performance detection device; constructing an interface attribute classifier, and obtaining a to-be-detected interface attribute parameter set; interface detection dual channels are obtained according to the control processor; performing matching analysis on the to-be-detected interface attribute parameter set; the Type-C interface to be detected is built in an air tightness test cavity, air tightness detection control is carried out according to the waterproof performance detection parameter curve, and a pressure change test data flow is obtained; and migrating to obtain a Type-C interface waterproof performance evaluator, and performing waterproof performance evaluation on the pressure change test data flow to obtain a waterproof performance detection result. The technical problems of low waterproof performance detection precision and poor efficiency caused by difficult efficient and accurate matching of detection parameters in the prior art are solved, and the technical effects of improving the waterproof performance detection efficiency and precision of the interface and the reliability of the detection result are achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to interface adapters, and specifically to a method and system for detecting the waterproof performance of a Type-C interface. Background Art

[0002] With the popularization of smart devices and the continuous development of electronic products towards miniaturization and high performance, the design and protection performance of the connection port are becoming increasingly important. As a new type of connection port with high transmission rate and high current carrying capacity, the Type-C interface has been widely used in various electronic devices such as smartphones, laptops, chargers, headphones, etc. However, with the increasing complexity of the use environment, how to ensure the reliability of the Type-C interface in harsh environments such as humidity and rain has become a top priority. The waterproof performance of the Type-C interface is directly related to the reliability and service life of the device. It not only depends on the design of the interface itself, but also is closely related to the overall sealing performance of the device. The current interface waterproof performance detection methods, such as immersion-based testing and water spraying testing, are usually difficult to simulate the complex water environment in actual use scenarios, and cannot perform refined testing of the sealing of the interface. In addition, there is a lack of efficient and accurate automated control methods, resulting in a complex detection process, poor detection efficiency, and easy to be affected by human factors, making the anti-water performance test results not accurate, and unable to guarantee the reliability of the Type-C interface.

[0003] Therefore, in the current relevant technologies, there is a technical problem that it is difficult to efficiently and accurately match the detection parameters, resulting in low accuracy and poor efficiency in waterproof performance detection. Summary of the invention

[0004] The present application solves the technical problem in the prior art that it is difficult to efficiently and accurately match detection parameters, resulting in low accuracy and poor efficiency in waterproof performance detection, by providing a method and system for detecting the waterproof performance of the Type-C interface. This achieves the technical effect of improving the efficiency, accuracy and reliability of the detection results of the waterproof performance of the interface.

[0005] The present application provides a method for detecting waterproof performance of a Type-C interface, the method comprising: obtaining a waterproof performance detection device, the waterproof performance detection device comprising an airtightness test chamber, a Hall pressure sensor, a control processor and an automatic fixture; constructing an interface attribute classifier, classifying attribute information of a Type-C interface to be detected based on the interface attribute classifier, and obtaining an interface attribute parameter set to be detected; obtaining an interface detection dual channel according to the control processor, the interface detection dual channel comprising a conventional detection channel and a special detection channel; matching and parsing the interface attribute parameter set to be detected based on the interface detection dual channel, and obtaining a waterproof performance detection parameter curve; placing the Type-C interface to be detected in the airtightness test chamber, fixing the Type-C interface to be detected by the automatic fixture, performing airtightness detection control on the Type-C interface to be detected according to the waterproof performance detection parameter curve, and simultaneously monitoring and obtaining a pressure change test data stream through the Hall pressure sensor; migrating to obtain a Type-C interface waterproof performance evaluator, performing waterproof performance evaluation on the pressure change test data stream based on the Type-C interface waterproof performance evaluator, and obtaining a Type-C interface waterproof performance detection result.

[0006] In a possible implementation, the waterproof performance detection method of the Type-C interface also performs the following processing: obtaining interface attribute factor information, the interface attribute factor information including size specifications, number of pins, functional attributes, application attributes and waterproof level requirements; mining and obtaining a Type-C interface product database, and extracting attribute features of the Type-C interface product database based on the interface attribute factor information to obtain an interface product attribute feature data set; using a decision tree to perform feature segmentation and recursive construction on the interface product attribute feature data set to obtain an initial interface attribute classification tree; performing classification prediction verification and parameter strategy tuning on the initial interface attribute classification tree to construct the interface attribute classifier.

[0007] In a possible implementation, the waterproof performance detection method of the Type-C interface also performs the following processing: classify and identify the Type-C interface product database according to the Type-C interface production standard to obtain a conventional Type-C interface product data set and a special Type-C interface product data set; crawl airtightness detection data based on the conventional Type-C interface product data set and the special Type-C interface product data set to obtain a conventional interface airtightness detection data set and a special interface airtightness detection data set; perform airtightness detection analysis based on the conventional interface airtightness detection data set and the special interface airtightness detection data set to obtain a conventional detection channel and a special detection channel; connect the conventional detection channel and the special detection channel in parallel to obtain an interface detection dual channel and store it in the control processor.

[0008] In a possible implementation, the waterproof performance detection method of the Type-C interface also performs the following processing: preferentially extracting detection parameters of the conventional interface airtightness detection data set to obtain an available interface airtightness detection data set; correlating and analyzing the interface attribute data and the airtightness detection parameters in the available interface airtightness detection data set to generate an interface attribute-airtightness detection parameter correlation model; configuring a conventional interface detection channel based on the interface attribute-airtightness detection parameter correlation model to obtain the conventional detection channel; performing airtightness detection analysis based on the special interface airtightness detection data set and the interface attribute-airtightness detection parameter correlation model to obtain the special detection channel.

[0009] In a possible implementation, the waterproof performance detection method of the Type-C interface also performs the following processing: extracting special attribute data and associated detection parameters of the special interface airtightness detection data set to obtain special interface detection feature data; using the interface attribute-airtightness detection parameter association model as the basic model framework, performing training loss analysis on the special interface detection feature data to obtain detection analysis loss data; performing incremental training update on the interface attribute-airtightness detection parameter association model based on the detection analysis loss data to obtain a special interface attribute-airtightness detection associated update model; configuring a special interface detection channel based on the special interface attribute-airtightness detection associated update model to obtain the special detection channel.

[0010] In a possible implementation, the waterproof performance detection method of the Type-C interface also performs the following processing: selecting a source domain interface waterproof performance evaluation data set, the source domain interface waterproof performance evaluation data set includes waterproof performance evaluation data sets of different types of interfaces; respectively evaluating and training the waterproof performance evaluation data sets of different types of interfaces to obtain a source domain interface waterproof performance evaluation model set; obtaining a Type-C interface waterproof performance evaluation target domain, and determining a transfer learning strategy based on the source domain interface waterproof performance evaluation model set and the Type-C interface waterproof performance evaluation target domain; performing transfer training and tuning on the Type-C interface waterproof performance evaluation data set and the source domain interface waterproof performance evaluation model set based on the transfer learning strategy to obtain the Type-C interface waterproof performance evaluator.

[0011] In a possible implementation, the waterproof performance detection method of the Type-C interface further performs the following processing: extracting the model parameters of the source domain interface waterproof performance evaluation model set respectively to obtain the source domain model parameter set; performing selective migration and fine-tuning on the source domain model parameter set based on the transfer learning strategy to obtain basic evaluation model structure parameters; using the basic evaluation model structure parameters to perform performance evaluation and model tuning on the Type-C interface waterproof performance evaluation data set to obtain the Type-C interface waterproof performance evaluator.

[0012] The present application also provides a waterproof performance detection system for a Type-C interface, including: a waterproof performance detection device acquisition module, used to acquire a waterproof performance detection device, the waterproof performance detection device including an airtightness test chamber, a Hall pressure sensor, a control processor and an automatic fixture; an interface attribute classifier construction module, used to construct an interface attribute classifier, based on which the attribute information of the Type-C interface to be detected is classified to obtain an interface attribute parameter set to be detected; an interface detection dual-channel acquisition module, used to obtain an interface detection dual-channel according to the control processor, the interface detection dual-channel including a conventional detection channel and a special detection channel; a parameter matching analysis module, used to classify the attribute information of the Type-C interface to be detected based on the interface attribute classifier, and obtain an interface attribute parameter set to be detected; The detection interface attribute parameter set is matched and parsed to obtain a waterproof performance detection parameter curve; an airtightness detection control module is used to place the Type-C interface to be detected in the airtightness test cavity, and fix the Type-C interface to be detected by the automatic fixture, and perform airtightness detection control on the Type-C interface to be detected according to the waterproof performance detection parameter curve, and at the same time monitor and obtain the pressure change test data stream through the Hall pressure sensor; a waterproof performance evaluation module is used to migrate and obtain a Type-C interface waterproof performance evaluator, and perform waterproof performance evaluation on the pressure change test data stream based on the Type-C interface waterproof performance evaluator to obtain a Type-C interface waterproof performance test result.

[0013] It is intended to obtain a waterproof performance detection device through the waterproof performance detection method and system of the Type-C interface proposed in this application; construct an interface attribute classifier to obtain the interface attribute parameter set to be detected; obtain the interface detection dual channel according to the control processor; match and parse the interface attribute parameter set to be detected; place the Type-C interface to be detected in the airtightness test chamber, perform airtightness detection control according to the waterproof performance detection parameter curve, and obtain the pressure change test data stream; migrate to obtain the Type-C interface waterproof performance evaluator, perform waterproof performance evaluation on the pressure change test data stream, and obtain the waterproof performance test result. It solves the technical problem that it is difficult to efficiently and accurately match the detection parameters in the prior art, resulting in low precision and poor efficiency of waterproof performance detection, and achieves the technical effect of improving the efficiency, accuracy and reliability of interface waterproof performance detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of a method for detecting the waterproof performance of a Type-C interface provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a Type-C interface waterproof performance detection system provided in an embodiment of the present application.

[0016] Explanation of the reference numerals: waterproof performance detection device acquisition module 10, interface attribute classifier construction module 20, interface detection dual-channel acquisition module 30, parameter matching analysis module 40, airtightness detection control module 50, waterproof performance evaluation module 60. DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides a method for detecting the waterproof performance of a Type-C interface, such as Figure 1 As shown, the method includes: Step S100, obtaining a waterproof performance testing device, wherein the waterproof performance testing device includes an airtightness test chamber, a Hall pressure sensor, a control processor and an automatic fixture.

[0021] Preferably, a waterproof performance detection device is obtained, wherein the waterproof performance detection device is a comprehensive test equipment for detecting the waterproof performance of the Type-C interface, including an airtightness test chamber, a Hall pressure sensor, a control processor and an automatic fixture. Specifically, the airtightness test chamber is a closed test area for performing airtightness detection on the Type-C interface. The gas flow in the test chamber can be controlled to simulate the penetration situation, so as to detect whether the interface can effectively prevent the entry of water and gas, and provide a closed and controlled environment for the test to ensure that the waterproof performance of the interface can be accurately tested; the Hall pressure sensor is a pressure sensor based on the Hall effect principle, which detects gas by The pressure change caused by the body or liquid in the airtightness test chamber is used to obtain the data of the interface's waterproof performance. It can accurately measure the air pressure change caused by the interface's sealing problem, thereby helping to determine the interface's waterproof ability; the control processor is the brain of the waterproof performance testing device, responsible for coordinating the work of various parts, collecting and processing test data, and controlling the test process according to the preset test standards to ensure the automation of the test process and generate corresponding test results; the automatic fixture is used to fix the Type-C interface to be tested during the test process to ensure the stability of the interface position, avoid human interference, ensure the consistency of the interface position during each test, and avoid test errors caused by changes in the interface position. Through the collaborative work of these components, the waterproof performance of the Type-C interface can be accurately and automatically tested in a controlled environment, providing reliable test data.

[0022] Step S200: construct an interface attribute classifier, classify attribute information of the Type-C interface to be detected based on the interface attribute classifier, and obtain an interface attribute parameter set to be detected.

[0023] Preferably, an interface attribute classifier is constructed based on a decision tree to analyze and classify the attribute information of the Type-C interface to be detected. Specifically, the interface attribute classifier classifies the Type-C interface to be detected according to different attributes of the interface (such as size, number of pins, function, application requirements and waterproof level, etc.), and then obtains a parameter set of interface attributes to be detected, wherein the interface attribute information includes the size specifications, number of pins, functional attributes, application attributes and waterproof level requirements of the Type-C interface. After classification by the interface attribute classifier, each interface to be detected will have a set of specific parameter data. The interface attribute parameter set to be detected may include the physical characteristics, electrical characteristics, functional requirements and environmental adaptability of the interface, etc., to ensure that the corresponding detection standards and processes are selected according to the characteristics of different interfaces, thereby improving the pertinence and accuracy of the detection.

[0024] Furthermore, step S200 also includes step S210, obtaining interface attribute factor information, wherein the interface attribute factor information includes size specifications, number of pins, functional attributes, application attributes, and waterproof level requirements; step S220, mining and obtaining a Type-C interface product database, performing attribute feature extraction on the Type-C interface product database based on the interface attribute factor information, and obtaining an interface product attribute feature data set; step S230, using a decision tree to perform feature segmentation and recursive construction on the interface product attribute feature data set to obtain an initial interface attribute classification tree; step S240, performing classification prediction verification and parameter strategy tuning on the initial interface attribute classification tree to construct the interface attribute classifier.

[0025] Preferably, the interface attribute factor information includes size specifications (physical dimensions of the Type-C interface, such as length, width and height, etc.), number of pins (number of pins available on the Type-C interface, used for different functions such as electrical connection, data transmission, power supply, etc.), functional attributes (functional characteristics of the interface, such as whether it supports high-speed data transmission, fast charging, video output, etc.), application attributes (specific device types and scenarios in which the interface is applied, such as mobile phones, laptops, chargers, audio equipment, etc.) and waterproof level requirements (specific requirements for the interface in terms of waterproofing, for example, whether the interface needs to reach a certain waterproof level, such as IP67 or IP68 level), wherein a large amount of Type-C interface product information is obtained through data mining technology to form a Type-C interface product database, which includes different attributes, technical parameters, functional requirements and other information of each Type-C interface, and then attribute feature extraction is performed on the Type-C interface product database according to the interface attribute factor information, that is, attribute features of Type-C interface products are extracted from the Type-C interface product database as an interface product attribute feature set, which includes various attribute features of different Type-C interface products, rows represent different interface products, and columns represent different attribute features.

[0026] Preferably, the interface product attribute feature data set is feature segmented and recursively constructed according to the decision tree. Specifically, an optimal segmentation feature (such as size, number of pins, waterproof level, etc.) is selected for each segmentation, so that the segmented sub-dataset is purer in terms of the feature (for example, similar data sets have similar waterproof level requirements). For example, information gain, gain ratio, etc. are calculated to determine the best segmentation feature. Recursive construction means starting from the root node, segmenting the data layer by layer, and each segmentation point forms a tree node. The segmented sub-dataset will be further recursively divided until the conditions are met, the data set contains only data of the same category, or effective segmentation can no longer be performed, or the data segmentation has reached the set purity threshold, thereby obtaining an initial interface attribute classification tree, and then performing classification prediction verification and parameter strategy optimization on the initial interface attribute classification tree. Specifically, classification prediction verification It refers to using a partial data set (usually called a validation set) to test the classification ability of the initial classification tree, and to measure the performance of the classification tree by predicting whether the verification model can accurately distinguish different categories of interface products, that is, to find out the shortcomings of the classification tree, such as whether overfitting occurs (the model performs well on the training data, but poorly on unseen data), and then improve its classification performance by optimizing the construction parameters of the decision tree (such as limiting the maximum depth of the classification tree, setting the minimum number of sample splits, controlling the minimum number of leaf node samples, etc.), avoiding overfitting and underfitting, and finally constructing an interface attribute classifier that can accurately classify according to the attribute characteristics of the Type-C interface (such as size specifications, functional attributes, waterproof level, etc.), and automatically assign attribute categories to each Type-C interface to be tested, so that subsequent testing processes (such as waterproof performance testing) can be adapted to specific test methods.

[0027] Step S300: obtaining an interface detection dual channel according to the control processor, wherein the interface detection dual channel includes a regular detection channel and a special detection channel.

[0028] Preferably, by controlling the processor, two different types of detection paths (interface detection dual channels) are constructed, namely, conventional detection channels and special detection channels, which are respectively used to meet the detection requirements of the Type-C interface under different conditions, thereby improving the flexibility and efficiency of the detection, so that the detection process can adapt to various interface properties and scenario requirements, wherein, by real-time control of the working parameters of the test equipment (such as the airtightness test chamber, the Hall pressure sensor, etc.), it is ensured that the detection process meets the preset channel requirements. Specifically, the conventional detection channel is a standardized detection channel for the Type-C interface, which is suitable for most interface products that meet conventional properties, and provides a set of preset, standardized detection parameters and methods for detecting the basic waterproof performance of the interface, including tests on the airtightness, pin sealing, pressure tolerance, etc. of the interface. For example, for the Type-C interface with a waterproof grade requirement of IP67, C interface, the conventional detection channel may include a pressure test of the airtightness test chamber, and perform airtightness detection according to fixed pressure curves and time parameters; the special detection channel is a detection channel designed for the Type-C interface with special attribute requirements or application scenarios, allowing targeted detection according to a specific set of interface attribute parameters (such as higher waterproof level requirements, specific functional requirements, etc.), supporting flexible adjustment of detection parameters, such as pressure range, detection time, ambient temperature or humidity, etc., to meet the needs of special interfaces, and can be used to test interface products with unconventional specifications, such as interfaces with non-standard pin numbers and special functions; by dividing the detection process into conventional detection channels and special detection channels, the detection system can adapt to Type-C interfaces with different attributes and requirements. The conventional detection channel focuses on efficiency and standardization, while the special detection channel provides flexibility and targeting, which can cover a wide range of detection needs.

[0029] Furthermore, step S300 also includes step S310, classifying and identifying the Type-C interface product database according to the Type-C interface production standard to obtain a conventional Type-C interface product data set and a special Type-C interface product data set; step S320, crawling airtightness detection data based on the conventional Type-C interface product data set and the special Type-C interface product data set to obtain a conventional interface airtightness detection data set and a special interface airtightness detection data set; step S330, performing airtightness detection analysis based on the conventional interface airtightness detection data set and the special interface airtightness detection data set, respectively, to obtain a conventional detection channel and a special detection channel; step S340, connecting the conventional detection channel and the special detection channel in parallel to obtain an interface detection dual-channel and store it in the control processor.

[0030] Preferably, the Type-C interface production standard is used to guide the production and testing of the Type-C interface, including technical indicators such as the interface size specifications, the number of pins, and the waterproof level requirements. It may specify which interfaces can be classified as "conventional interfaces" (such as interfaces that meet commonly used specifications) and "special interfaces" (such as interfaces with unconventional properties or designed for specific purposes). The attribute information (such as physical specifications, functional requirements, waterproof level, etc.) of each interface product is extracted from the Type-C interface product database. According to this attribute information and production standards, the products are classified into two categories: conventional Type-C interface product data set, which includes interfaces that meet common specifications, such as standard interfaces for smartphones and laptops, and special Type-C interface product data set, It includes interfaces with special requirements, such as high waterproof level requirements, interfaces for industrial equipment, or interfaces with non-standard size. Then, air tightness detection data is crawled, that is, air tightness test data related to conventional interfaces and special interfaces are collected from existing test records, including test conditions (such as pressure range, time), test results (such as pressure holding time, leakage rate), and the mapping relationship between interface properties and test data, to obtain conventional interface air tightness detection data sets (air tightness detection data of conventional Type-C interfaces under standard test conditions, such as the performance of pressure holding capacity under IP67 conditions) and special interface air tightness detection data sets (air tightness detection data of special Type-C interfaces under complex or non-standard conditions, such as IP68 test conditions or dynamic pressure test data).

[0031] Preferably, air tightness detection analysis is performed according to the obtained conventional interface air tightness detection data set and special interface air tightness detection data set, that is, the crawled detection data is analyzed (such as analysis, modeling), and the laws and key parameters of the detection process are extracted. Specifically, the conventional interface air tightness detection data set is analyzed to extract the standard detection process and parameters applicable to the conventional interface, and a conventional detection channel is constructed. The special interface air tightness detection data set is analyzed to extract the complex or non-standard detection process and parameters, and a special detection channel is constructed. Finally, the conventional detection channel and the special detection channel obtained by the analysis are connected in parallel to form an interface detection dual channel, that is, the conventional Channels and special channels exist at the same time and can be switched dynamically according to the interface properties; the control processor can automatically select the appropriate detection channel according to the classification of the interface to be detected (conventional or special); by diverting the detection tasks, the detection efficiency is improved, and the diverse interface requirements are met at the same time; the interface detection dual channels are stored in the control processor, and the control processor can retrieve the corresponding classification information from the database according to the properties of the interface to be detected, and dynamically select the applicable detection channel to control the operation of the detection equipment (such as the airtightness test chamber, pressure sensor), to ensure that the detection process meets the preset parameters, thereby realizing automated detection, improving detection efficiency and ensuring the consistency and reliability of the detection results.

[0032] Furthermore, step S330 also includes step S331, performing preferential extraction of detection parameters for the conventional interface air tightness detection data set to obtain an available interface air tightness detection data set; step S332, performing correlation analysis on the interface attribute data and the air tightness detection parameters in the available interface air tightness detection data set to generate an interface attribute-air tightness detection parameter correlation model; step S333, performing conventional interface detection channel configuration based on the interface attribute-air tightness detection parameter correlation model to obtain the conventional detection channel; step S334, performing air tightness detection analysis based on the special interface air tightness detection data set and the interface attribute-air tightness detection parameter correlation model to obtain the special detection channel.

[0033] Preferably, the detection parameters of the conventional interface air tightness detection data set are preferentially extracted, that is, those better detection parameters that have the most critical impact on the air tightness performance of the interface, such as pressure value, detection time, ambient temperature, etc., are screened out from the detection data set to form an available interface air tightness detection data set, which contains high-quality, key detection parameters, and then the interface attribute data and the air tightness detection parameters are correlated and analyzed. Specifically, for each interface in the available interface air tightness detection data set, the relationship between its attribute data and the corresponding air tightness detection parameters is analyzed, and an interface attribute-air tightness detection parameter association model is generated through data analysis or machine learning methods (such as regression analysis, classification models, etc.). The model is used to describe the intrinsic relationship between the physical properties of the interface and its air tightness performance (such as leakage rate and pressure holding capacity under different pressures), and can predict the parameters that may be required in the air tightness test process (such as maximum pressure, test time, etc.) according to the input interface attributes (such as size, number of pins, waterproof level, etc.).

[0034] Preferably, an interface attribute-air tightness detection parameter association model is used, combined with the attribute data of conventional interfaces (such as the size and waterproof grade of a standard IP67 interface), to configure a suitable detection channel, including the pressure range of the detection channel, the detection duration, and the setting of environmental conditions (temperature, humidity, etc.), to ensure that the detection process of conventional interfaces can be completed efficiently and accurately under predetermined conditions, to obtain conventional detection channels, to be able to automatically perform air tightness detection on different types of conventional interfaces, and to provide a standardized detection process; similarly, an interface attribute-air tightness detection parameter association model is used to parse the air tightness detection data of special interfaces, to predict the optimal test parameters (such as pressure, time, etc.) of special interfaces through the association model, and to construct a detection channel suitable for special interfaces based on the results of the model output, and to generate a special detection channel for special interfaces based on the analysis results. The configuration of the special detection channel may include dynamic pressure change simulation (such as periodic pressure fluctuations) and adaptation to the temperature change range (such as detection in high or low temperature environments), so that air tightness detection of different types of interfaces can be performed efficiently and accurately, ensuring the waterproof performance of the interface in different application scenarios.

[0035] Furthermore, step S334 also includes step A, extracting special attribute data and associated detection parameters of the special interface airtightness detection data set to obtain special interface detection feature data; step B, taking the interface attribute-airtightness detection parameter association model as the basic model framework, performing training loss analysis on the special interface detection feature data to obtain detection analysis loss data; step C, performing incremental training update on the interface attribute-airtightness detection parameter association model based on the detection analysis loss data to obtain a special interface attribute-airtightness detection associated update model; and step D, configuring a special interface detection channel based on the special interface attribute-airtightness detection associated update model to obtain the special detection channel.

[0036] Preferably, the extraction of special attribute data and associated detection parameters for the special interface air tightness detection data set includes extracting attribute data related to the special interface (such as non-standard size interface, higher waterproof level than conventional interface, etc.) from the data set, and extracting detection parameters corresponding to these special attributes (such as pressure range of high waterproof level, dynamic pressure change, temperature change range adaptation, etc.), and combining these data as special interface detection feature data; using the constructed interface attribute-air tightness detection parameter association model as the basic model framework (general model structure and initial parameters), and performing training loss analysis on the special interface detection feature data, that is, using the special interface detection feature data to train the basic model, and analyzing the loss of the model when processing these data, wherein the loss is the error between the model prediction value and the actual detection parameter value, reflecting the adaptability of the model to the special interface detection feature data, and obtaining detection analysis loss data, which represents the quantification of the model deficiencies, including which features and detection parameter predictions have large errors.

[0037] Preferably, incremental training and updating are performed based on the detection and analysis loss data, that is, the basic model is optimized and trained, and the detection and analysis loss data is used as a guide to dynamically adjust the weight and structure of the model to better adapt to the detection characteristics of the special interface, and the model is optimized so that it can accurately predict the detection parameters of the special interface, and finally a special interface attribute-airtightness detection association update model is obtained, which can better adapt to the special interface attributes and detection requirements; then the special interface attribute-airtightness detection association update model is used to configure a detection channel for the special interface, and the configuration content includes the detection pressure range (such as dynamic pressure range or extremely high pressure), detection time (such as long-term airtightness retention test), environmental conditions (such as high temperature, low temperature, humidity changes, etc.) and dynamic test requirements (such as periodic changes in pressure over time). Through the optimized model configuration, a channel for special interface detection is generated, which can accurately adapt to the properties and detection requirements of the special interface, ensuring the reliability and efficiency of the detection process.

[0038] Step S400: matching and parsing the interface attribute parameter set to be detected based on the interface detection dual channels to obtain a waterproof performance detection parameter curve.

[0039] Preferably, through the dual-channel interface detection (conventional detection channel and special detection channel), matching and parsing are performed according to the specific attribute parameter set of the Type-C interface to be detected, including matching the corresponding detection standards and methods, so as to generate a detection process and parameters suitable for the interface, and express them in the form of a parameter curve, that is, to obtain a waterproof performance detection parameter curve. Specifically, matching and parsing refers to selecting a suitable detection channel according to the attribute parameter set of the interface to be detected, and further determining the specific steps and requirements of the detection. If the parameter set of the interface meets the standard attributes (such as common size, waterproof grade IP67, etc.), it is matched to the conventional detection channel, which contains a preset detection process, such as a fixed pressure range, time and curve template. If the parameter set of the interface has special requirements (such as non-standard size, waterproof grade IP68 or special functional requirements), Match to a special detection channel and generate a customized detection process based on specific attributes. The result of the matching analysis is to determine the appropriate detection method and parameters to ensure that the detection process is consistent with the attribute requirements of the interface. Then, the matching analysis results are visualized to define the key parameters involved in the detection process and their changing rules, which may include the pressure curve (the change of pressure in the airtightness test chamber over time, such as simulating the airtightness of the interface under a certain pressure environment), the time curve (defining the detection duration to ensure sufficient testing), and the dynamic change curve of the special detection channel (for the waterproof performance of the interface in a changing environment, the curve may represent the dynamic changes of pressure and temperature, such as simulating different underwater depths or temperature changes), so that the detection process can accurately adapt to the attribute requirements of different Type-C interfaces, greatly improving the pertinence, reliability and efficiency of the detection.

[0040] Step S500, the Type-C interface to be tested is built into the airtightness test chamber, and the Type-C interface to be tested is fixed by the automatic fixture, and the airtightness detection and control of the Type-C interface to be tested is performed according to the waterproof performance detection parameter curve, and the pressure change test data stream is monitored and obtained by the Hall pressure sensor.

[0041] Preferably, when performing a waterproof performance test on the Type-C interface, an airtightness test chamber, an automatic fixture, a Hall pressure sensor and other equipment are used, and the interface is accurately tested for airtightness in combination with a waterproof performance test parameter curve. Specifically, the Type-C interface to be tested is built into the airtightness test chamber, and the Type-C interface to be tested is fixed by an automatic fixture, and the Type-C interface to be tested is controlled for airtightness testing according to the waterproof performance test parameter curve, and the pressure change test data stream is obtained by monitoring the Hall pressure sensor at the same time, wherein the Type-C interface to be tested is placed in this sealed test chamber, and it is ensured that the interface is completely enclosed in this environment to avoid external factors interfering with the test results, and the plug part and the connection area of ​​the interface are both inside the cavity to ensure that there is no gas leakage during the test; the automatic fixture can automatically adjust and clamp according to the size and shape of the interface to ensure that the interface is in line with the test chamber The sealing of the interface remains consistent to ensure that the position and angle of the interface do not change; airtightness detection control refers to automatically adjusting the pressure, time and other factors of the airtightness test chamber according to the waterproof performance detection parameter curve to simulate the real waterproof environment. For example, it may continue to pressurize for a certain period of time, or fluctuate within a specific pressure range to simulate the pressure changes that the interface may face in actual use; finally, the Hall pressure sensor senses the pressure change to generate a signal, so that the pressure change inside the cavity can be monitored in real time to obtain the pressure change test data stream (pressure change of the interface during the test). For example, if there is a defect in the sealing of the interface, it may cause pressure leakage. The Hall sensor can capture these pressure change data and feed them back to the control processor in real time; then it can accurately determine whether the interface meets the required waterproof performance standards, and realize automated and precise waterproof performance evaluation, thereby improving detection efficiency and accuracy.

[0042] Step S600: Migrate and obtain a Type-C interface waterproof performance evaluator, perform waterproof performance evaluation on the pressure change test data stream based on the Type-C interface waterproof performance evaluator, and obtain a Type-C interface waterproof performance test result.

[0043] Preferably, a transfer learning strategy is used to perform transfer training optimization to obtain a Type-C interface waterproof performance evaluator, which is used to analyze and evaluate the waterproof performance of the Type-C interface. It may be based on existing air tightness detection methods, pressure analysis algorithms, data modeling technologies, etc., through adaptation or optimization, so that it can accurately evaluate the waterproof performance of the Type-C interface, and through analysis of the pressure change test data stream, determine whether the interface meets the waterproof performance requirements, and output the test results. Then, the Type-C interface waterproof performance evaluator is used to evaluate the waterproof performance of the pressure change test data stream, which may include anomaly detection (by analyzing the pressure change data stream, detecting whether there is an abnormal fluctuation or pressure relief phenomenon). For example, if the pressure curve fails to remain stable within the specified time, it means that the interface may have air leakage or poor sealing), parameter matching (compare the test data with the waterproof performance test parameter curve to determine whether the data stream meets the standard, such as checking whether the pressure remains within the specified range for a long enough time), performance index calculation (calculate specific indicators of waterproof performance, such as pressure relief rate, maximum withstand pressure value, etc.), and output the Type-C interface waterproof performance test results based on the analysis results, such as qualified, unqualified, or detailed listing of various performance indicators of the interface (such as maximum withstand pressure, pressure relief rate, etc.), that is, if the pressure data stream completely meets the preset parameter curve, the output test result is qualified, indicating that the interface waterproof performance meets the requirements. Through automated and intelligent waterproof performance evaluation, quality control and reliability detection of the Type-C interface can be achieved.

[0044] Further, step S600 also includes step S610, selecting a source domain interface waterproof performance evaluation data set, wherein the source domain interface waterproof performance evaluation data set includes waterproof performance evaluation data sets of different types of interfaces; step S620, respectively performing evaluation training on the waterproof performance evaluation data sets of different types of interfaces to obtain a source domain interface waterproof performance evaluation model set; step S630, obtaining a Type-C interface waterproof performance evaluation target domain, and determining a transfer learning strategy based on the source domain interface waterproof performance evaluation model set and the Type-C interface waterproof performance evaluation target domain; step S640, performing transfer training and tuning on the Type-C interface waterproof performance evaluation data set and the source domain interface waterproof performance evaluation model set based on the transfer learning strategy to obtain the Type-C interface waterproof performance evaluator.

[0045] Preferably, transfer learning is used to extract knowledge from existing waterproof performance evaluation data and models, and the Type-C interface waterproof performance evaluator is trained and optimized in combination with the specific data and requirements of the Type-C interface. Specifically, data suitable for the Type-C interface characteristics (such as similar physical size, waterproof level requirements, etc.) are selected from the source domain dataset. The source domain interface waterproof performance evaluation dataset is an existing, collected and organized waterproof performance test data, which is used to describe the waterproof performance evaluation results and characteristics of different types of interfaces, including tests of various interface types (such as USB-A, USB-B, Type-C, etc.). Data covers the behavior and evaluation results of interfaces with different attributes (such as size, number of pins, waterproof level, etc.) in waterproof performance tests; evaluation training is performed on waterproof performance evaluation data sets of different types of interfaces, that is, the selected source domain data set is input into the basic evaluation model, and the characteristic patterns in the data are learned through the training model. Data of different interface types are used to train multiple sub-models, and each model corresponds to an interface type (such as USB-A, USB-B, etc.), so that the model can accurately evaluate the waterproof performance of the input data, such as pressure holding capacity, leakage characteristics, etc., and then form a source domain interface waterproof performance evaluation model set.

[0046] Preferably, a target domain for evaluating the waterproof performance of the Type-C interface is obtained. The target domain for evaluating the waterproof performance of the Type-C interface is a data set specific to the Type-C interface, including relevant data for its waterproof performance test, including the test data stream of the Type-C interface (pressure change, time curve, etc.) and the attribute information of the Type-C interface (size, number of pins, waterproof level requirements, etc.). Then, according to the characteristics of the source domain model set and the target domain data, a suitable transfer learning strategy is designed to transfer the knowledge of the source domain model to the Type-C interface waterproof performance evaluation task, including extracting common waterproof performance features from the source domain model for Type-C interface data analysis, using the parameters of the source domain model as initial values, and fine-tuning the target domain data adapted to the Type-C interface. The source domain and target domain data are trained at the same time, so that the model can optimize the target domain while maintaining the source domain knowledge. domain tasks; then, based on the transfer learning strategy, the Type-C interface waterproof performance evaluation dataset and the source domain interface waterproof performance evaluation model set are transferred and trained. Specifically, the source domain model is combined with the target domain data of the Type-C interface for joint training. During the training process, the model gradually adjusts its parameters so that it can adapt to the data characteristics of the source domain and the target domain at the same time. The model is optimized through the test data of the target domain to more accurately evaluate the waterproof performance of the Type-C interface. The key parameters of the model (such as learning rate, regularization coefficient, etc.) are adjusted to ensure that the migrated model can better adapt to the characteristics of the Type-C interface, and then the Type-C interface waterproof performance evaluator is obtained, which integrates the evaluation experience of the source domain interface and the specific data of the Type-C interface, can accurately analyze the waterproof performance test data stream of the Type-C interface, and give the evaluation results.

[0047] Furthermore, step S640 also includes step S641, respectively extracting the model parameters of the source domain interface waterproof performance evaluation model set to obtain the source domain model parameter set; step S642, selectively migrating and fine-tuning the source domain model parameter set based on the transfer learning strategy to obtain basic evaluation model structure parameters; step S643, using the basic evaluation model structure parameters to perform performance evaluation and model tuning on the Type-C interface waterproof performance evaluation data set to obtain the Type-C interface waterproof performance evaluator.

[0048] Preferably, the knowledge in the existing source domain model (such as model parameters and structure) is transferred to the Type-C interface waterproof performance evaluation task through transfer learning, and the performance evaluation model for the Type-C interface is gradually optimized and generated. Specifically, the model parameters of the source domain interface waterproof performance evaluation model set are extracted, that is, for each model in the source domain model set, the parameters obtained by optimization after training are extracted to obtain the source domain model parameter set, which may include weight parameters and bias parameters of each layer of the model, so as to provide reference initial parameters for migration to the Type-C interface waterproof performance evaluation; then, the source domain model parameter set is selected and fine-tuned based on the transfer learning strategy. Selecting transfer refers to selecting the model parameters most relevant to the Type-C interface waterproof performance evaluation task from the source domain model parameter set. The selection basis may include the similarity between the characteristics of the source domain interface and the target Type-C interface (such as size, waterproof level, functional attributes, etc.) or the performance of the model on the source domain task, and fine-tuning the transfer. It means taking the selected model parameters as the initial parameters of the Type-C interface model, and using the target domain data of the Type-C interface to fine-tune these parameters, for example, only optimizing the parameters that are highly related to the Type-C interface characteristics, so as to obtain the basic evaluation model structure parameters; finally, using the basic evaluation model structure parameters to perform performance evaluation and model tuning on the Type-C interface waterproof performance evaluation dataset, including using the fine-tuned basic evaluation model structure parameters to perform performance testing on the Type-C interface waterproof performance evaluation dataset to verify the prediction ability of the model, and further optimizing the model based on the evaluation results, adjusting the parameters and structure to improve the performance of the model on the Type-C interface task, and finally obtaining a Type-C interface waterproof performance evaluator, which can accurately evaluate the waterproof performance of the interface based on the waterproof performance test data of the Type-C interface, provide intelligent and automated support for waterproof performance testing, and greatly improve the evaluation efficiency and accuracy.

[0049] In the above, refer to Figure 1 The waterproof performance detection method of the Type-C interface according to the embodiment of the present invention is described in detail. Figure 2 A waterproof performance detection system for a Type-C interface according to an embodiment of the present invention is described.

[0050] The Type-C interface waterproof performance detection system according to the embodiment of the present invention is used to solve the technical problem that it is difficult to efficiently and accurately match the detection parameters in the prior art, resulting in low waterproof performance detection accuracy and poor efficiency, and achieves the technical effect of improving the interface waterproof performance detection efficiency, accuracy and reliability of the detection results. Figure 2As shown, the waterproof performance detection system of the Type-C interface includes: a waterproof performance detection device acquisition module 10, an interface attribute classifier construction module 20, an interface detection dual-channel acquisition module 30, a parameter matching and analysis module 40, an airtightness detection control module 50, and a waterproof performance evaluation module 60.

[0051] A waterproof performance detection device acquisition module 10 is used to acquire a waterproof performance detection device, wherein the waterproof performance detection device includes an airtightness test chamber, a Hall pressure sensor, a control processor, and an automatic fixture; an interface attribute classifier construction module 20 is used to construct an interface attribute classifier, and classify the attribute information of the Type-C interface to be detected based on the interface attribute classifier to obtain the interface attribute parameter set to be detected; an interface detection dual-channel acquisition module 30 is used to obtain an interface detection dual-channel according to the control processor, wherein the interface detection dual-channel includes a conventional detection channel and a special detection channel; a parameter matching analysis module 40 is used to match the interface attribute parameter set to be detected based on the interface detection dual-channel. The test chamber is equipped with an analysis module to obtain a waterproof performance detection parameter curve; an airtightness detection control module 50 is used to place the Type-C interface to be detected in the airtightness test chamber, and fix the Type-C interface to be detected by the automatic fixture, and perform airtightness detection control on the Type-C interface to be detected according to the waterproof performance detection parameter curve, and at the same time monitor and obtain the pressure change test data stream through the Hall pressure sensor; a waterproof performance evaluation module 60 is used to migrate and obtain a Type-C interface waterproof performance evaluator, and perform waterproof performance evaluation on the pressure change test data stream based on the Type-C interface waterproof performance evaluator to obtain a Type-C interface waterproof performance test result.

[0052] The specific configuration of the interface attribute classifier construction module 20 will be described in detail below. The interface attribute classifier construction module 20 further includes: obtaining interface attribute factor information, the interface attribute factor information includes size specifications, number of pins, functional attributes, application attributes and waterproof level requirements; mining and obtaining a Type-C interface product database, extracting attribute features from the Type-C interface product database based on the interface attribute factor information, and obtaining an interface product attribute feature data set; using a decision tree to perform feature segmentation and recursive construction on the interface product attribute feature data set to obtain an initial interface attribute classification tree; performing classification prediction verification and parameter strategy tuning on the initial interface attribute classification tree to construct the interface attribute classifier.

[0053] The specific configuration of the interface detection dual-channel acquisition module 30 will be described in detail below. The interface detection dual-channel acquisition module 30 further includes: classifying and identifying the Type-C interface product database according to the Type-C interface production standard, obtaining a conventional Type-C interface product data set and a special Type-C interface product data set; crawling airtightness detection data based on the conventional Type-C interface product data set and the special Type-C interface product data set to obtain a conventional interface airtightness detection data set and a special interface airtightness detection data set; performing airtightness detection analysis based on the conventional interface airtightness detection data set and the special interface airtightness detection data set, respectively, to obtain a conventional detection channel and a special detection channel; connecting the conventional detection channel and the special detection channel in parallel, obtaining an interface detection dual channel and storing it in the control processor.

[0054] The specific configuration of the interface detection dual-channel acquisition module 30 will be described in detail below. The interface detection dual-channel acquisition module 30 further includes: performing detection parameter optimization extraction on the conventional interface airtightness detection data set to obtain an available interface airtightness detection data set; performing correlation analysis on the interface attribute data and airtightness detection parameters in the available interface airtightness detection data set to generate an interface attribute-airtightness detection parameter correlation model; performing conventional interface detection channel configuration based on the interface attribute-airtightness detection parameter correlation model to obtain the conventional detection channel; performing airtightness detection analysis based on the special interface airtightness detection data set and the interface attribute-airtightness detection parameter correlation model to obtain the special detection channel.

[0055] The specific configuration of the interface detection dual-channel acquisition module 30 will be described in detail below. The interface detection dual-channel acquisition module 30 further includes: extracting special attribute data and associated detection parameters from the special interface airtightness detection data set to obtain special interface detection feature data; using the interface attribute-airtightness detection parameter association model as the basic model framework, performing training loss analysis on the special interface detection feature data to obtain detection analysis loss data; performing incremental training update on the interface attribute-airtightness detection parameter association model based on the detection analysis loss data to obtain a special interface attribute-airtightness detection association update model; performing special interface detection channel configuration based on the special interface attribute-airtightness detection association update model to obtain the special detection channel.

[0056] The specific configuration of the waterproof performance evaluation module 60 will be described in detail below. The waterproof performance evaluation module 60 further includes: selecting a source domain interface waterproof performance evaluation data set, the source domain interface waterproof performance evaluation data set includes waterproof performance evaluation data sets of different types of interfaces; respectively evaluating and training the waterproof performance evaluation data sets of different types of interfaces to obtain a source domain interface waterproof performance evaluation model set; obtaining a Type-C interface waterproof performance evaluation target domain, and determining a transfer learning strategy based on the source domain interface waterproof performance evaluation model set and the Type-C interface waterproof performance evaluation target domain; performing transfer training and tuning on the Type-C interface waterproof performance evaluation data set and the source domain interface waterproof performance evaluation model set based on the transfer learning strategy to obtain the Type-C interface waterproof performance evaluator.

[0057] The specific configuration of the waterproof performance evaluation module 60 will be described in detail below. The waterproof performance evaluation module 60 further includes: extracting the model parameters of the source domain interface waterproof performance evaluation model set respectively to obtain the source domain model parameter set; performing selective migration and fine-tuning on the source domain model parameter set based on the transfer learning strategy to obtain the basic evaluation model structure parameters; using the basic evaluation model structure parameters to perform performance evaluation and model tuning on the Type-C interface waterproof performance evaluation data set to obtain the Type-C interface waterproof performance evaluator.

[0058] The waterproof performance detection system of the Type-C interface provided in the embodiment of the present invention can execute the waterproof performance detection method of the Type-C interface provided in any embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method.

[0059] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0060] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for detecting the waterproof performance of a Type-C interface, characterized in that: The method comprises: Obtain a waterproof performance testing device, wherein the waterproof performance testing device includes an airtightness test chamber, a Hall pressure sensor, a control processor, and an automatic fixture; Construct an interface attribute classifier, classify the attribute information of the Type-C interface to be detected based on the interface attribute classifier, and obtain an interface attribute parameter set to be detected; Obtaining an interface detection dual channel according to the control processor, wherein the interface detection dual channel includes a conventional detection channel and a special detection channel; Based on the interface detection dual channels, matching and parsing the interface attribute parameter set to be detected are performed to obtain a waterproof performance detection parameter curve; The Type-C interface to be tested is built into the airtightness test chamber, and the Type-C interface to be tested is fixed by the automatic fixture, and the airtightness detection and control of the Type-C interface to be tested is performed according to the waterproof performance detection parameter curve, and at the same time, the pressure change test data stream is obtained by monitoring the Hall pressure sensor; The Type-C interface waterproof performance evaluator is obtained by migration, and waterproof performance evaluation is performed on the pressure change test data stream based on the Type-C interface waterproof performance evaluator to obtain a Type-C interface waterproof performance test result.

2. The waterproof performance detection method of the Type-C interface according to claim 1, characterized in that: The construction of the interface attribute classifier includes: Acquire interface attribute factor information, wherein the interface attribute factor information includes size specification, number of pins, functional attributes, application attributes, and waterproof level requirements; Mining and acquiring a Type-C interface product database, extracting attribute features from the Type-C interface product database based on the interface attribute factor information, and obtaining an interface product attribute feature data set; Using a decision tree to perform feature segmentation and recursive construction on the interface product attribute feature data set to obtain an initial interface attribute classification tree; The initial interface attribute classification tree is subjected to classification prediction verification and parameter strategy tuning to construct the interface attribute classifier.

3. The waterproof performance detection method of the Type-C interface according to claim 1, characterized in that: The obtaining of the interface detection dual channel according to the control processor comprises: Classify and identify the Type-C interface product database according to the Type-C interface production standard to obtain a regular Type-C interface product data set and a special Type-C interface product data set; Crawling air tightness detection data based on the conventional Type-C interface product data set and the special Type-C interface product data set to obtain a conventional interface air tightness detection data set and a special interface air tightness detection data set; Based on the conventional interface air tightness detection data set and the special interface air tightness detection data set, air tightness detection analysis is performed respectively to obtain a conventional detection channel and a special detection channel; The conventional detection channel and the special detection channel are connected in parallel to obtain an interface detection dual channel and store it in the control processor.

4. The waterproof performance detection method of the Type-C interface as claimed in claim 3, characterized in that: The obtaining of conventional detection channels and special detection channels comprises: Performing optimal extraction of detection parameters on the conventional interface air tightness detection data set to obtain an available interface air tightness detection data set; Performing correlation analysis on the interface attribute data and the air tightness detection parameters in the available interface air tightness detection data set to generate an interface attribute-air tightness detection parameter correlation model; Performing conventional interface detection channel configuration based on the interface attribute-air tightness detection parameter association model to obtain the conventional detection channel; Airtightness detection analysis is performed based on the special interface airtightness detection data set and the interface attribute-airtightness detection parameter association model to obtain the special detection channel.

5. The waterproof performance detection method of the Type-C interface as claimed in claim 4, characterized in that: The obtaining of the special detection channel comprises: Extracting special attribute data and associated detection parameters from the special interface air tightness detection data set to obtain special interface detection feature data; The interface attribute-air tightness detection parameter association model is used as a basic model framework, and a training loss analysis is performed on the special interface detection feature data to obtain detection analysis loss data; Based on the detection and analysis loss data, incremental training and updating are performed on the interface attribute-air tightness detection parameter association model to obtain a special interface attribute-air tightness detection association update model; Based on the special interface attribute-airtightness detection association update model, a special interface detection channel is configured to obtain the special detection channel.

6. The waterproof performance detection method of the Type-C interface according to claim 1, characterized in that: The migration obtains a Type-C interface waterproof performance evaluator, including: Selecting a source domain interface waterproof performance evaluation data set, wherein the source domain interface waterproof performance evaluation data set includes waterproof performance evaluation data sets of different types of interfaces; Conducting evaluation training on the waterproof performance evaluation data sets of the different types of interfaces respectively to obtain a source domain interface waterproof performance evaluation model set; Acquire a Type-C interface waterproof performance evaluation target domain, and determine a transfer learning strategy according to the source domain interface waterproof performance evaluation model set and the Type-C interface waterproof performance evaluation target domain; Based on the transfer learning strategy, the Type-C interface waterproof performance evaluation data set and the source domain interface waterproof performance evaluation model set are subjected to migration training and optimization to obtain the Type-C interface waterproof performance evaluator.

7. The method for detecting waterproof performance of a Type-C interface according to claim 6, characterized in that: The obtaining of the Type-C interface waterproof performance evaluator comprises: Extracting the model parameters of the source domain interface waterproof performance evaluation model set respectively to obtain a source domain model parameter set; Based on the transfer learning strategy, the source domain model parameter set is selected for transfer and fine-tuning to obtain basic evaluation model structure parameters; The basic evaluation model structure parameters are used to perform performance evaluation and model tuning on the Type-C interface waterproof performance evaluation data set to obtain the Type-C interface waterproof performance evaluator.

8. A waterproof performance detection system for a Type-C interface, characterized in that: The system is used to implement the waterproof performance detection method of the Type-C interface according to any one of claims 1 to 7, and the system includes: A waterproof performance detection device acquisition module, used to acquire a waterproof performance detection device, wherein the waterproof performance detection device includes an airtightness test chamber, a Hall pressure sensor, a control processor and an automatic fixture; An interface attribute classifier construction module is used to construct an interface attribute classifier, classify the attribute information of the Type-C interface to be detected based on the interface attribute classifier, and obtain a set of interface attribute parameters to be detected; An interface detection dual-channel acquisition module, used for acquiring an interface detection dual-channel according to the control processor, wherein the interface detection dual-channel includes a conventional detection channel and a special detection channel; A parameter matching and analysis module, used for matching and analyzing the attribute parameter set of the interface to be detected based on the interface detection dual channels to obtain a waterproof performance detection parameter curve; An airtightness detection control module is used to place the Type-C interface to be detected in the airtightness test chamber, fix the Type-C interface to be detected by the automatic fixture, perform airtightness detection control on the Type-C interface to be detected according to the waterproof performance detection parameter curve, and monitor and obtain a pressure change test data stream through the Hall pressure sensor; The waterproof performance evaluation module is used to migrate and obtain a Type-C interface waterproof performance evaluator, and based on the Type-C interface waterproof performance evaluator, perform waterproof performance evaluation on the pressure change test data stream to obtain a Type-C interface waterproof performance test result.

Images