Scene adaptive aging test method and system for extra-high voltage MOS (Metal Oxide Semiconductor)

Abstract

The invention discloses a scene self-adaptive aging test method and system for an extra-high voltage MOS (Metal Oxide Semiconductor), and relates to the related technical field of MOS test, and the method comprises the steps: building a device aging test platform; performing test condition analysis on the application scene information of the target extra-high voltage MOS device; performing pretest adjustment on the target extra-high voltage MOS device, and determining an aging test update parameter table; performing aging test monitoring on the target extra-high voltage MOS device; and calling an extra-high voltage MOS aging adaptive evaluator to process and evaluate the device aging scene test data stream set to obtain a device scene aging performance test result. The technical problems that in the prior art, due to the fact that an MOS aging test lacks scene adaptability, the aging process of the MOS device in the actual application environment is difficult to accurately simulate, the test pertinence is insufficient, and the result accuracy is poor are solved, and the technical effect of improving the MOS device aging test pertinence and the result accuracy is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to MOS testing, and specifically to a scenario-adaptive aging test method and system for ultra-high voltage MOS. Background Art

[0002] With the increasing demand for high performance and high reliability of modern electronic devices, metal oxide semiconductor field effect transistors (MOSFET) are increasingly used in power electronics, automotive electronics, communication equipment and other fields. Especially in UHV application scenarios, the reliability and stability of MOS devices are particularly important. As an important semiconductor device, MOS's aging problem will gradually appear during long-term operation. MOS aging is mainly manifested in the degradation of device parameters, including changes in threshold voltage (Vth), increase in leakage current, and reduction in switching speed. The aging phenomenon is usually caused by the combined effects of high electric fields, high temperature environments, and long-term high-voltage operation of devices. These factors will lead to thinning of the oxide layer, migration, and interface defects in the device. Especially in UHV application environments, MOS faces more severe challenges. When working at high voltage, the electric field strength of the device increases, resulting in accelerated aging and greatly shortened device life. However, current MOS device aging test methods usually rely on standard accelerated life tests. By running MOSFET under specific accelerated conditions such as temperature, voltage, and frequency, the aging process of the device in the actual working environment is simulated. Although this can help engineers detect the life and reliability of MOS devices, it often lacks targeted evaluation of specific working scenarios, and the test process is relatively simplified, and cannot accurately and comprehensively reflect the aging phenomenon in the actual use environment.

[0003] Therefore, in the current related technologies, there are technical problems such as the lack of scenario adaptability of MOS aging tests and difficulty in accurately simulating the aging process of MOS devices in actual application environments, resulting in insufficient test targeting and poor result accuracy. Summary of the invention

[0004] The present application provides a scenario-adaptive aging test method and system for ultra-high voltage MOS, thereby solving the technical problems in the prior art that the MOS aging test lacks scenario adaptability and is difficult to accurately simulate the aging process of MOS devices in actual application environments, resulting in insufficient test targeting and poor result accuracy, thereby achieving the technical effect of improving the targeting and result accuracy of MOS device aging tests.

[0005] The present application provides a scenario-adaptive aging test method for ultra-high voltage MOS, the method comprising: establishing a device aging test platform, the device aging test platform comprising an environmental test chamber, a host computer, a test fixture and a test evaluation module; performing test condition parsing on application scenario information of a target ultra-high voltage MOS device by the host computer, and generating an aging test condition parameter table; fixing the target ultra-high voltage MOS device on the test fixture, performing pre-test adjustment on the target ultra-high voltage MOS device based on the aging test condition parameter table by the environmental test chamber, and determining an aging test update parameter table; performing aging test monitoring on the target ultra-high voltage MOS device based on the aging test update parameter table, and obtaining a device aging scenario test data stream set; calling an ultra-high voltage MOS aging adaptive evaluator by the test evaluation module, and processing and evaluating the device aging scenario test data stream set based on the ultra-high voltage MOS aging adaptive evaluator, and obtaining a device scenario aging performance test result.

[0006] In a possible implementation, the generation of the aging test condition parameter table further performs the following processing: extracting elements of the application scenario information of the target ultra-high voltage MOS device to obtain device application scenario element information; parsing the test conditions for each application scenario in the application scenario information in turn according to the device application scenario element information to obtain a device scenario test element parameter set; determining a device scenario aging test parameter set according to a device aging test target; and performing parameter design combination of the device scenario test element parameter set and the device scenario aging test parameter set to generate the aging test condition parameter table.

[0007] In a possible implementation, the determining of the aging test update parameter table further performs the following processing: performing pre-test monitoring on the target UHV MOS device based on the aging test condition parameter table to obtain a device aging pre-test data stream set; performing performance evaluation on the target UHV MOS device based on the device aging pre-test data stream set to obtain a device aging performance pre-test result; performing abnormal threshold analysis on the device aging performance pre-test result to determine a device performance abnormal test parameter threshold; adjusting and optimizing the aging test condition parameter table based on the device performance abnormal test parameter threshold to determine the aging test update parameter table.

[0008] In a possible implementation, the calling of the UHV MOS aging adaptive evaluator also performs the following processing: collecting and acquiring a UHV MOS aging test data set, performing key indicator analysis on the UHV MOS aging test data set, and determining a key evaluation indicator set for aging performance; performing shunting evaluation identification on the UHV MOS aging test data set according to the key evaluation indicator set for aging performance, and obtaining a key indicator aging test sample set; performing network structure selection and evaluation training on the key indicator aging test sample set respectively, and generating an indicator aging performance evaluation branch network set; integrating and fusing the indicator aging performance evaluation branch network set, obtaining a UHV MOS aging adaptive evaluator, and storing it in the test evaluation module.

[0009] In a possible implementation, the method for determining the key evaluation indicator set for aging performance further performs the following processing: extracting associated indicators from the UHV MOS aging test data set to obtain a device aging associated evaluation indicator set; performing a clustering operation on the device aging associated evaluation indicator set based on the UHV MOS aging test data set to obtain an associated aging indicator clustering result; performing intra-cluster divergence and inter-cluster divergence calculation and evaluation on the associated aging indicator clustering result to determine a clustering divergence quality index; optimizing and updating the associated aging indicator clustering result and screening key indicators based on the clustering divergence quality index to determine the aging performance key evaluation indicator set.

[0010] In a possible implementation, the determining of the key evaluation indicator set for aging performance further performs the following processing: iteratively optimizing and updating the associated aging indicator clustering results based on the cluster divergence quality index until a preset termination condition is met to obtain an aging indicator clustering update result; performing a correlation evaluation on each indicator cluster in the aging indicator clustering update result to obtain an aging indicator cluster correlation degree set; determining an aging indicator cluster screening threshold set based on the aging indicator cluster correlation degree set; and performing key indicator screening on each indicator cluster in the aging indicator clustering update result based on the aging indicator cluster screening threshold set to determine the key evaluation indicator set for aging performance.

[0011] In a possible implementation, the obtaining of the UHV MOS aging adaptive evaluator further performs the following processing: performing a criticality evaluation on each branch network in the index aging performance evaluation branch network set to obtain a branch network criticality coefficient set; performing output performance verification on each branch network in the index aging performance evaluation branch network set to obtain a branch network precise factor set; and constructing a branch network decision function: ,in, Representative The branch network criticality coefficient, Identify the criticality coefficient of the detection factor, Identification A branch network precise factor; based on the branch network decision function, parameter calculation is performed on the branch network criticality coefficient set and the branch network precise factor set to obtain a branch network decision parameter set; based on the branch network decision parameter set, weighted integration and fusion are performed on the indicator aging performance evaluation branch network set to obtain the UHV MOS aging adaptive evaluator.

[0012] The present application also provides a scenario-adaptive aging test system for UHV MOS, including: a device aging test platform establishment module, used to establish a device aging test platform, the device aging test platform including an environmental test chamber, a host computer, a test fixture and a test evaluation module; a test condition parsing module, used to perform test condition parsing on application scenario information of a target UHV MOS device through the host computer, and generate an aging test condition parameter table; a pre-test adjustment module, used to fix the target UHV MOS device on the test fixture, perform pre-test adjustment on the target UHV MOS device based on the aging test condition parameter table through the environmental test chamber, and determine an aging test update parameter table; an aging test monitoring module, used to perform aging test monitoring on the target UHV MOS device based on the aging test update parameter table, and obtain a device aging scenario test data stream set; a performance test result acquisition module, used to call a UHV MOS aging adaptive evaluator through the test evaluation module, process and evaluate the device aging scenario test data stream set based on the UHV MOS aging adaptive evaluator, and obtain a device scenario aging performance test result.

[0013] It is intended to establish a device aging test platform through the scenario-adaptive aging test method and system for UHV MOS proposed in this application; analyze the test conditions of the application scenario information of the target UHV MOS device; make pre-test adjustments to the target UHV MOS device and determine the aging test update parameter table; perform aging test monitoring on the target UHV MOS device; call the UHV MOS aging adaptive evaluator to process and evaluate the device aging scenario test data stream set to obtain the device scenario aging performance test results. This solves the technical problems existing in the prior art that the MOS aging test lacks scenario adaptability and is difficult to accurately simulate the MOS device aging process in the actual application environment, resulting in insufficient test pertinence and poor result accuracy, and achieves the technical effect of improving the pertinence and result accuracy of the MOS device aging test. 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 flow chart of a scenario-adaptive aging test method for UHV MOS provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a scenario-adaptive aging test system for UHV MOS provided in an embodiment of the present application.

[0016] Description of the accompanying drawings: device aging test platform establishment module 10, test condition analysis module 20, pre-test adjustment module 30, aging test monitoring module 40, performance test result acquisition module 50. 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 scenario-adaptive aging test method for UHV MOS, such as Figure 1 As shown, the method includes: step S100, establishing a device aging test platform, the device aging test platform includes an environmental test box, a host computer, a test fixture and a test evaluation module.

[0021] Preferably, a device aging test platform is established. The device aging test platform refers to a comprehensive test platform including multiple components and equipment constructed in order to perform systematic and accurate aging tests on target ultra-high voltage MOS devices. The device aging test platform includes an environmental test chamber, a host computer, a test fixture and a test evaluation module. Specifically, the environmental test chamber is used to simulate specific environmental conditions (such as high temperature, high humidity, high voltage, etc.) to perform aging tests on MOS devices. The environmental test chamber can control factors such as the ambient temperature, humidity, and voltage of the device during the test process, thereby simulating the aging process of the device in different working environments. For example, for ultra-high voltage MOS devices, the environmental test chamber can be used to simulate their working conditions in a high voltage and high temperature environment to detect their aging characteristics; the host computer refers to a computer system that connects and controls the entire test system, and is responsible for managing, controlling and collecting data for the test process. Through the host computer, the operator can input test conditions, obtain test data, adjust test parameters, etc. The host computer is also responsible for parsing the application scenario information of the target MOS device and generating a corresponding aging test condition parameter table, thereby realizing precise control and automation of the test process.

[0022] Preferably, the test fixture is used to fix the target MOS device on the test platform to ensure the stability and accuracy of the device during the test. The fixture needs to be designed according to the specific size and shape of the MOS device to ensure that the fixture can properly contact the device and ensure that the device will not be displaced or otherwise disturbed during the test, thereby ensuring the consistency and reliability of the device under different test environments; the test evaluation module refers to a system module used to process and analyze test data, which can evaluate the aging process and performance changes of the device based on the data stream generated by the target MOS device under different test conditions. Usually, the test evaluation module is connected to the host computer and is responsible for calling the relevant aging adaptive evaluator to analyze the test data of the device, thereby obtaining the scene aging performance test results of the device. The device aging test platform is designed to simulate and evaluate the aging performance of MOS devices under different environmental conditions, control the test conditions through the environmental test chamber, manage and process data with the help of the host computer, use the test fixture to ensure the stable fixation of the device, and conduct in-depth analysis of the test data through the test evaluation module, so as to comprehensively evaluate the aging performance of the device.

[0023] Step S200: The host computer performs test condition analysis on the application scenario information of the target UHV MOS device to generate an aging test condition parameter table.

[0024] Preferably, in the device aging test platform, the host computer analyzes and derives specific conditions suitable for aging test of the target UHV MOS device according to the application scenario information of the target UHV MOS device, and generates an aging test condition parameter table. Specifically, the application scenario information of the target UHV MOS device is obtained through the actual use scenario of the device (power electronic system, communication equipment, automotive electronic control system, etc.), that is, various parameters related to the working environment of the target MOS device, such as operating voltage, current, operating frequency, temperature range, load condition, operating time, ambient humidity, etc.; then the host computer analyzes the application scenario information of the target UHV MOS device and converts this information into conditions related to the aging test. Specifically, the host computer analyzes the application scenario information of the target UHV MOS device according to preset rules, in combination with the target device The electrical characteristics, structural characteristics and working scenarios of the device are converted into aging test conditions that can reflect the performance degradation of the device. For example, if the device will work in a high-temperature environment, the test conditions may be set to a certain temperature higher than the actual working environment to accelerate the aging process, and then an aging test condition parameter table is generated, which specifically lists the various settings in the aging test process, which may include but are not limited to temperature range, voltage range, current load, test time and test steps (such as preheating, load regulation, etc.). By generating a detailed test condition parameter table, the host computer ensures that the test conditions used in the entire test process can accurately simulate the actual working scenarios of the target MOS device, and can cover the performance of the MOS device under various working conditions to evaluate its long-term reliability.

[0025] Furthermore, step S200 also includes step S210, extracting elements of the application scenario information of the target ultra-high voltage MOS device to obtain device application scenario element information; step S220, parsing the test conditions of each application scenario in the application scenario information in turn according to the device application scenario element information to obtain a device scenario test element parameter set; step S230, determining a device scenario aging test parameter set according to a device aging test target; and step S240, performing parameter design combination on the device scenario test element parameter set and the device scenario aging test parameter set to generate the aging test condition parameter table.

[0026] Preferably, extracting elements from the application scenario information of the target UHV MOS device means extracting key feature data that is crucial to the device aging test from these application scenario information to obtain specific application scenario element information, which may include voltage level, temperature range, current load, load change and environmental factors, etc., and then analyzing the test conditions of each application scenario in the application scenario information in turn according to the device application scenario element information, that is, by analyzing each application scenario (such as high temperature, high voltage, current load, etc.) one by one, each element information extracted from the application scenario is converted into a specific test condition, and a device scenario test element parameter set is obtained, including temperature, humidity, voltage level and test time, etc.; then according to the device aging test target (in the actual test), the device aging test element parameter set is obtained. The desired goal is to accelerate the aging process of MOS devices by simulating extreme environmental conditions, and test the stability of devices under continuous load, such as changes in device leakage current and threshold voltage, so as to determine the device scenario aging test parameter set, including the device voltage, current load and temperature, etc.; finally, combine the scenario test element parameter set with the parameter set of the aging test target, that is, combine the voltage, current, temperature and other conditions in the test element parameter set with the extreme conditions such as high voltage and high temperature required by the aging test target, and form the final aging test condition parameter table, which includes all test conditions and parameters, to ensure that the test conditions can fully cover all working conditions that MOS devices may encounter in actual applications, and improve the accuracy and comprehensiveness of aging performance testing.

[0027] Step S300, the target UHV MOS device is fixedly mounted on the test fixture, and pre-test adjustment is performed on the target UHV MOS device based on the aging test condition parameter table through the environmental test chamber to determine an aging test update parameter table.

[0028] Preferably, during the device aging test, the operations of device fixing, environmental adjustment and test condition optimization are combined to ensure that the test can more accurately simulate the performance of the MOS device in the actual working environment, and update the test conditions to improve the effectiveness of the test. Specifically, the target UHV MOS device is fixedly mounted on the test fixture, that is, the target MOS device is fixed by the test fixture to ensure that the device will not be displaced or damaged during the aging test. The design of the fixture needs to match the size, structure and contact method of the MOS device to ensure that the device can be in good contact with the test conditions (such as temperature and voltage) in the environmental test chamber to avoid test errors caused by looseness or poor contact of the device during the test, thereby ensuring stability and accuracy during the test; then the environmental test chamber is used to simulate specific environmental conditions (such as high temperature, high humidity, high voltage, etc.), that is, the environment The test chamber performs pre-test adjustments on the target MOS device based on the aging test condition parameter table before the test. Specifically, by adjusting parameters such as temperature, voltage, and humidity, the working environment that the target MOS device may face in actual application scenarios is simulated. Through pre-test adjustments, the test conditions can be ensured to be optimal in advance to prepare for the formal aging test. After the pre-test adjustments, it is found that some of the originally set test conditions are not suitable for the actual device response or test requirements, and the test conditions need to be optimized, such as the adjustment of environmental factors such as temperature, voltage, and load, the adjustment of test time, and the optimization of test steps. These adjusted conditions are recorded and updated as a new aging test update parameter table to ensure that subsequent aging tests are carried out more accurately and efficiently, and that real and reliable aging performance data can be obtained, thereby improving the reliability and accuracy of the test data.

[0029] Furthermore, step S300 also includes step S310, performing pre-test monitoring on the target UHV MOS device based on the aging test condition parameter table to obtain a device aging pre-test data stream set; step S320, performing performance evaluation on the target UHV MOS device based on the device aging pre-test data stream set to obtain a device aging performance pre-test result; step S330, performing abnormal threshold analysis on the device aging performance pre-test result to determine a device performance abnormal test parameter threshold; step S340, adjusting and optimizing the aging test condition parameter table based on the device performance abnormal test parameter threshold to determine the aging test update parameter table.

[0030] Preferably, the target UHV MOS device is pre-tested and monitored based on the aging test condition parameter table to verify whether the set test conditions meet the actual requirements and ensure the stability and accuracy of the data during the test. In the pre-test stage, the MOS device will operate for a period of time under the specified environmental conditions, and the performance data (such as current, voltage, leakage current, temperature change, etc.) during this period will be monitored and recorded in real time to generate an aging pre-test data stream set, which is usually recorded in a time series manner, reflecting the performance changes of the MOS device during the preliminary test process, including the changes of multiple dimensions of information (such as voltage, current, temperature, etc.) over time, reflecting the aging trend of the device under given conditions; then various evaluation methods are used to process and analyze the data, including analyzing the change trends of various performance indicators of the device (such as leakage current, threshold voltage, current carrying capacity, etc.) over time, to determine whether the device has unexpected degradation or abnormal phenomena during the aging process, and the evaluation results are used as the device aging performance pre-test results, such as the predicted aging trend (such as whether it meets the normal aging curve), whether premature performance degradation or abnormality occurs.

[0031] Preferably, an abnormal threshold analysis is performed on the device aging performance pre-test results, that is, analyzing the changes in device performance, especially those performance degradations beyond the normal range, wherein the abnormal threshold refers to the fact that during the aging process, certain performance of the device (such as leakage current, threshold voltage, switching speed, etc.) exceeds the preset safety range, indicating that the device may have undergone abnormal aging or failure, thereby defining the device performance abnormality test parameter threshold as a standard for monitoring and evaluation in subsequent formal aging tests, helping to determine whether a sudden change in device performance has occurred during the test; finally, based on the performance abnormality test parameter threshold, the original aging test condition parameter table is optimized and adjusted, that is, when it is found that the device performance has significantly decreased, the test parameters need to be optimized to avoid device damage, identify any abnormal or unexpected results, optimize the test element parameters in the test plan, and obtain the aging test update parameter table to ensure that the subsequent formal aging test can more accurately simulate the long-term use status of the MOS device.

[0032] Step S400: Perform aging test monitoring on the target UHV MOS device based on the aging test update parameter table to obtain a device aging scenario test data stream set.

[0033] Preferably, actual test monitoring is performed on the target UHV MOS device according to the aging test conditions in the aging test update parameter table, and real-time data of the device under different working environments is collected to form a device aging scenario test data stream set. Specifically, these specific environmental conditions are applied to the target MOS device according to the aging test update parameter table to perform actual aging testing. For example, the test may include long-term high-temperature and high-voltage operation, or simulate the performance of the device under extreme current and voltage changes. Then, during the entire aging test process, various operating data of the target MOS device are acquired in real time through a monitoring system (such as a variety of sensors, data acquisition systems, and instruments and equipment). , including current, voltage, temperature, power consumption, leakage current, etc., to ensure that the test environment and parameters meet the requirements of aging test, and at the same time, timely capture the performance changes of the device during operation, helping testers to find abnormal situations in time, so as to obtain the device aging scenario test data stream set, including the various performance indicators of the device at each time point (such as voltage, temperature, leakage current, etc.), such as voltage, current, temperature, power, temperature inside the device, leakage current and other multi-dimensional information, each dimension of data changes with time, recording the performance change trend of the device during the aging process, the data stream set provides the performance data of the device under different aging conditions, which is an important basis for evaluating the aging process of MOS devices. By analyzing these data, it is possible to determine whether the device meets the design requirements, whether its performance is degraded during the aging process, and infer the service life and reliability of the MOS device.

[0034] Step S500: calling the UHV MOS aging adaptive evaluator through the test evaluation module, processing and evaluating the device aging scenario test data stream set based on the UHV MOS aging adaptive evaluator, and obtaining the device scenario aging performance test result.

[0035] Preferably, the UHV MOS aging adaptive evaluator is called through the test evaluation module to analyze and process the test data stream set obtained from the aging test, so as to evaluate the aging performance of the target MOS device and obtain the final aging performance test result, that is, the device scenario aging performance test result. Specifically, during the test process, the test evaluation module is connected with the UHV MOS aging adaptive evaluator to call the latter to conduct an in-depth analysis of the collected data. The UHV MOS aging adaptive evaluator can automatically adjust the analysis model according to the working environment and aging test data of the target MOS device to adapt to different aging test scenarios. It not only considers the conventional electrical performance changes in the test data, but also may combine some environmental changes, device life prediction and other factors for comprehensive evaluation.

[0036] Preferably, processing and evaluating the aging scenario test data stream set refers to screening, cleaning, analyzing and modeling these original test data to extract valuable information, including dynamically evaluating the parameters in the data stream set according to algorithms (such as regression analysis, machine learning algorithms, etc.) to quantify the aging state and performance degradation of the device, specifically including, the UHV MOS aging adaptive evaluator determines whether the device conforms to the expected degradation mode during the aging process and whether there is abnormal degradation according to the change trend of the electrical performance (such as leakage current, threshold voltage, switching speed, etc.) in the data stream, and evaluates the adaptability of the device in a specific environment according to the temperature and voltage changes in the aging test scenario. For example, under UHV conditions, the threshold voltage and leakage current of the MOS device may change greatly, and the stability of the device needs to be evaluated. By analyzing the aging trend of the device, the possible performance of the device in long-term use is evaluated, and the remaining service life of the device is predicted; thereby obtaining the device scenario aging performance test results, such as the degree of performance degradation, the reliability evaluation of the device (reliability in specific environments such as high temperature and high voltage and whether it can work stably for a long time), and the life prediction data (the expected life or remaining life of the device), which reflects the performance degradation of the target MOS device in a given aging test scenario. Through a data-driven approach, the accuracy and efficiency of testing are improved, avoiding the limitations of manual judgment in traditional testing.

[0037] Furthermore, step S500 also includes step S510, collecting and acquiring a UHV MOS aging test data set, performing key indicator analysis on the UHV MOS aging test data set, and determining a key evaluation indicator set for aging performance; step S520, performing shunting evaluation identification on the UHV MOS aging test data set according to the key evaluation indicator set for aging performance, and obtaining a key indicator aging test sample set; step S530, performing network structure selection and evaluation training on the key indicator aging test sample set respectively, and generating an indicator aging performance evaluation branch network set; step S540, integrating and fusing the indicator aging performance evaluation branch network set, obtaining a UHV MOS aging adaptive evaluator and storing it in the test evaluation module.

[0038] Preferably, the performance data of the ultra-high voltage MOS device during the aging test is collected through various sensors to obtain an ultra-high voltage MOS aging test data set, including various indicators such as voltage, current, leakage current, threshold voltage, switching speed, power loss, temperature, etc., which reflects the aging process of the device under specific test conditions. The collected aging test data is then analyzed to identify the core indicators that can truly reflect the aging degree of the MOS device, such as leakage current, threshold voltage change and switching performance, and then determine the aging performance key evaluation indicator set, which contains the indicators that best reflect the aging characteristics and performance degradation of the device; according to the determined aging performance key evaluation indicator set, the collected aging test data is diverted and evaluated according to these key indicators, that is, different indicator data are processed and analyzed separately, so that the change trend of each indicator can be independently evaluated, and then a data set of each type of key indicator (such as leakage current, threshold voltage, etc.) is obtained to form a key indicator aging test sample set.

[0039] Preferably, the network structure selection and evaluation training are performed on the key indicator aging test sample sets respectively, including selecting a suitable neural network architecture (such as a convolutional neural network, a long short-term memory network, etc.) for modeling according to different aging test sample sets (such as leakage current, threshold voltage, etc.), and then using the test sample set of each key indicator for training. The network will learn the relationship between each key indicator and the performance aging of the MOS device, and model the device aging process based on a large amount of historical data, and then generate multiple indicator aging performance evaluation branch networks to form an indicator aging performance evaluation branch network set, each branch network is specifically used to process one or more specific key performance indicators, and perform aging prediction on these indicators; finally, the indicator aging performance evaluation branch network set is integrated and fused, that is, multiple indicator aging performance evaluation branch networks are integrated through integrated learning or model fusion technology using weighted average, voting mechanism, etc., to obtain a UHV MOS aging adaptive evaluator, which can combine all key performance indicators to comprehensively evaluate the aging process of the MOS device, predict the aging trend of the device in the future, and then store it in the test evaluation module. The test evaluation module can call the evaluator in real time to perform real-time analysis on the newly collected MOS device aging test data to ensure that it can cope with situations under different test conditions.

[0040] Furthermore, step S510 also includes step S511, extracting associated indicators from the UHV MOS aging test data set to obtain a device aging associated evaluation indicator set; step S512, performing a clustering operation on the device aging associated evaluation indicator set based on the UHV MOS aging test data set to obtain an associated aging indicator clustering result; step S513, performing intra-cluster divergence and inter-cluster divergence calculation and evaluation on the associated aging indicator clustering result to determine a clustering divergence quality index; step S514, optimizing and updating the associated aging indicator clustering result and screening key indicators based on the clustering divergence quality index to determine the aging performance key evaluation indicator set.

[0041] Preferably, the UHV MOS aging test data set is subjected to associated index extraction, that is, different associated indicators are extracted, such as the relationship between voltage change and leakage current, temperature change and threshold voltage change trend, etc., which can jointly reflect the aging process of the MOS device. These associated indicators are usually the result of the mutual influence between multiple different test data. The obtained aging associated evaluation indicator set may include voltage-leakage current correlation, temperature-threshold voltage correlation and switching frequency-power consumption correlation. Then, a clustering operation is performed on the device aging associated evaluation indicator set based on the UHV MOS aging test data set, and indicators with similar aging trends or performance change patterns are classified using (K-means clustering, hierarchical clustering, etc.) to generate associated aging indicator clustering results. For example, at different temperatures, the leakage current change and threshold voltage change of some MOS devices may show similar patterns, and they are clustered into the same group.

[0042] Preferably, the clustering results of the associated aging indicators are evaluated by calculating the intra-cluster divergence and inter-cluster divergence. The intra-cluster divergence refers to the degree of dispersion between data points in the same cluster, reflecting the degree of compactness within the cluster. If the intra-cluster divergence is small, it means that the indicators within the cluster have high similarity, otherwise it means that the clustering effect is poor. The inter-cluster divergence refers to the degree of dispersion between different clusters, reflecting the degree of distinction between clusters. A larger inter-cluster divergence indicates that there are significant differences between different clusters and a better clustering effect; while a smaller inter-cluster divergence indicates that there is a large overlap between different clusters and a poor clustering effect. The intra-cluster divergence and inter-cluster divergence are calculated together to obtain the cluster divergence quality index, which is used to measure the quality of the clustering results. The smaller the index, the higher the clustering quality. According to the cluster divergence quality index, the clustering results are selected and optimized. If the quality of some clustering results is poor (that is, the intra-cluster divergence is large or the inter-cluster divergence is small), it is necessary to adjust the clustering algorithm or reselect features to improve the quality of clustering, and then screen out the key evaluation indicators that have the greatest impact on the aging process, which can best reflect the aging performance of MOS devices, and form a set of key evaluation indicators for aging performance to ensure that the aging performance of MOS devices can be effectively evaluated.

[0043] Furthermore, step S514 also includes step S514a, iteratively optimizing and updating the associated aging indicator clustering results based on the cluster divergence quality index until a preset termination condition is reached to obtain the aging indicator clustering update results; step S514b, performing correlation evaluation on each indicator cluster in the aging indicator clustering update results to obtain an aging indicator cluster correlation degree set; step S514c, determining an aging indicator cluster screening threshold set based on the aging indicator cluster correlation degree set; and step S514d, performing key indicator screening on each indicator cluster in the aging indicator clustering update results based on the aging indicator cluster screening threshold set to determine the aging performance key evaluation indicator set.

[0044] Preferably, the clustering results of the associated aging indicators are iteratively optimized and updated according to the clustering divergence quality index, that is, based on the clustering divergence quality index, the preliminary clustering results are repeatedly optimized, and the intra-cluster divergence (improving the compactness of the cluster) and the inter-cluster divergence (increasing the difference between clusters) are minimized by adjusting the clustering method and parameters, so as to obtain a more accurate clustering result. Each round of optimization will readjust the clustering boundary, select a different clustering method or reallocate data points until the optimal clustering structure is reached. By repeatedly comparing the difference between the current clustering result and the target quality index until a preset termination condition is reached, such as reaching a predetermined clustering divergence quality index (i.e., the clustering quality reaches a certain standard), reaching a maximum number of iterations or the clustering result no longer changes significantly, the updated clustering result of the aging indicator is obtained; and then the correlation is evaluated, that is, the correlation between different clusters is measured by a statistical method (such as the Pearson correlation coefficient, etc.), the correlation between each indicator cluster is evaluated, and it is determined which indicator clusters have a strong correlation with each other, so as to obtain a set of aging indicator cluster correlations, which describes the degree of correlation between each cluster.

[0045] Preferably, a suitable threshold is determined based on the correlation data in the aging indicator cluster correlation set, which is used to screen out indicator clusters with higher correlation. The aging indicator cluster screening threshold is determined by setting a fixed value or dynamic calculation (such as by statistical analysis, average correlation of clusters, etc.) to obtain an aging indicator cluster screening threshold set. Finally, each indicator cluster in the cluster update result is screened according to the set aging indicator cluster screening threshold set. Depending on whether the correlation of each cluster reaches a predetermined threshold, it is decided whether to retain the indicators in the cluster as key evaluation indicators. If the correlation of a cluster is higher than the threshold, the indicators in the cluster are considered to have a significant impact on the aging process and are added to the aging performance key evaluation indicator set. Finally, by screening out indicator clusters with significant impact, the aging performance key evaluation indicator set is determined, which includes all core indicators that can accurately reflect the aging process of MOS devices, making the evaluation process more scientific and efficient, and being able to accurately evaluate the performance changes of UHV MOS devices during the aging process.

[0046] Further, step S540 also includes step S541, performing criticality evaluation on each branch network in the indicator aging performance evaluation branch network set to obtain a branch network criticality coefficient set; step S542, performing output performance verification on each branch network in the indicator aging performance evaluation branch network set to obtain a branch network precise factor set; step S543, constructing a branch network decision function: ,in, Representative The branch network criticality coefficient, Identify the criticality coefficient of the detection factor, Identification branch network precise factors; step S544, based on the branch network decision function, parameter calculation is performed on the branch network critical coefficient set and the branch network precise factor set to obtain a branch network decision parameter set; step S545, based on the branch network decision parameter set, weighted integration and fusion are performed on the indicator aging performance evaluation branch network set to obtain the UHV MOS aging adaptive evaluator.

[0047] Preferably, each branch network represents an evaluation model for different aging performance indicators. For each branch network, its criticality in the aging test is evaluated, that is, the contribution of the network to the overall aging evaluation, and multiple branch network criticality coefficients are obtained, which reflect the importance of the network in the overall evaluation, and then the branch network criticality coefficient set is determined. Then, the output results of each branch network are verified, usually by comparing the actual test data with the model output results, checking the performance of the model in predicting the aging characteristics of MOS devices, and evaluating its accuracy. Specifically, through the verification process, the prediction accuracy of each branch network is evaluated to obtain the precision factor. The precision factor represents the accuracy and reliability of the output results of the branch network. The precision factor set is the collection of precision factors of all branch networks. If a branch network performs more accurately in the prediction process, the corresponding precision factor will be higher.

[0048] Preferably, a branch network decision function is constructed: ,in, represents the criticality coefficient of the nth branch network, Identify the criticality coefficient of the detection factor, Identify the nth branch network precision factor, Identify the n-1th branch network precision factor, Represents the total criticality coefficient of all branch networks, Representing the total precision factor of all branch networks, the branch network decision function weights the criticality and precision of each branch network, and comprehensively considers the role of each branch network in the final evaluation, thereby helping to generate the final aging performance evaluation result. Then, based on the decision function, the criticality coefficient, precision factor and detection factor criticality coefficient of all branch networks are calculated to obtain the decision parameters of each branch network, and the branch network decision parameter set, that is, the influence of each branch network in the final evaluation, is obtained. Finally, the indicator aging performance evaluation branch network set is weighted and integrated according to the branch network decision parameter set to ensure that each branch network occupies an appropriate weight in the final evaluation result according to its criticality and precision, and generate a UHV MOS aging adaptive evaluator, which can make a comprehensive evaluation of the aging process of the MOS device based on the input aging test data and the weighted results of each branch network, and provide strong evaluation support for the long-term stability and reliability of the equipment.

[0049] In the above, refer to Figure 1 The following describes in detail a scenario-adaptive aging test method for UHV MOS according to an embodiment of the present invention. Figure 2 A scenario-adaptive aging test system for ultra-high voltage MOS according to an embodiment of the present invention is described.

[0050] The scenario-adaptive aging test system for UHV MOS according to the embodiment of the present invention is used to solve the technical problems that the MOS aging test in the prior art lacks scenario adaptability and is difficult to accurately simulate the aging process of MOS devices in the actual application environment, resulting in insufficient test pertinence and poor result accuracy, thereby achieving the technical effect of improving the pertinence and result accuracy of MOS device aging tests. The scenario-adaptive aging test system for UHV MOS includes: a device aging test platform establishment module 10, a test condition analysis module 20, a pre-test adjustment module 30, an aging test monitoring module 40, and a performance test result acquisition module 50.

[0051] A device aging test platform establishment module 10 is used to establish a device aging test platform, and the device aging test platform includes an environmental test chamber, a host computer, a test fixture and a test evaluation module; a test condition parsing module 20 is used to perform test condition parsing on the application scenario information of the target UHV MOS device through the host computer to generate an aging test condition parameter table; a pre-test adjustment module 30 is used to fix the target UHV MOS device on the test fixture, perform pre-test adjustment on the target UHV MOS device based on the aging test condition parameter table through the environmental test chamber, and determine the aging test update parameter table; an aging test monitoring module 40 is used to perform aging test monitoring on the target UHV MOS device based on the aging test update parameter table to obtain a device aging scenario test data stream set; a performance test result acquisition module 50 is used to call the UHV MOS aging adaptive evaluator through the test evaluation module, process and evaluate the device aging scenario test data stream set based on the UHV MOS aging adaptive evaluator, and obtain a device scenario aging performance test result.

[0052] The specific configuration of the test condition analysis module 20 will be described in detail below. The test condition analysis module 20 further includes: extracting elements from the application scenario information of the target UHV MOS device to obtain the device application scenario element information; performing test condition analysis on each application scenario in the application scenario information in turn according to the device application scenario element information to obtain a device scenario test element parameter set; determining a device scenario aging test parameter set according to the device aging test target; and combining the device scenario test element parameter set and the device scenario aging test parameter set by parameter design to generate the aging test condition parameter table.

[0053] The specific configuration of the pre-test adjustment module 30 will be described in detail below. The pre-test adjustment module 30 further includes: performing pre-test monitoring on the target UHV MOS device based on the aging test condition parameter table to obtain a device aging pre-test data stream set; performing performance evaluation on the target UHV MOS device based on the device aging pre-test data stream set to obtain a device aging performance pre-test result; performing abnormal threshold analysis on the device aging performance pre-test result to determine a device performance abnormal test parameter threshold; adjusting and optimizing the aging test condition parameter table based on the device performance abnormal test parameter threshold to determine the aging test update parameter table.

[0054] The specific configuration of the performance test result acquisition module 50 will be described in detail below. The performance test result acquisition module 50 further includes: collecting and acquiring a UHV MOS aging test data set, performing key indicator analysis on the UHV MOS aging test data set, and determining a key evaluation indicator set for aging performance; performing shunting evaluation identification on the UHV MOS aging test data set according to the key evaluation indicator set for aging performance, and obtaining a key indicator aging test sample set; performing network structure selection and evaluation training on the key indicator aging test sample set respectively, and generating an indicator aging performance evaluation branch network set; integrating and fusing the indicator aging performance evaluation branch network set, and obtaining a UHV MOS aging adaptive evaluator and storing it in the test evaluation module.

[0055] The specific configuration of the performance test result acquisition module 50 will be described in detail below. The performance test result acquisition module 50 further includes: extracting related indicators from the UHV MOS aging test data set to obtain a device aging related evaluation indicator set; performing a clustering operation on the device aging related evaluation indicator set based on the UHV MOS aging test data set to obtain a related aging indicator clustering result; performing intra-cluster divergence and inter-cluster divergence calculation and evaluation on the related aging indicator clustering result to determine a clustering divergence quality index; optimizing and updating the related aging indicator clustering result and screening key indicators based on the clustering divergence quality index to determine the aging performance key evaluation indicator set.

[0056] The specific configuration of the performance test result acquisition module 50 will be described in detail below. The performance test result acquisition module 50 further includes: iteratively optimizing and updating the associated aging indicator clustering result based on the cluster divergence quality index until a preset termination condition is reached to obtain an aging indicator clustering update result; performing a correlation evaluation on each indicator cluster in the aging indicator clustering update result to obtain an aging indicator cluster correlation degree set; determining an aging indicator cluster screening threshold set based on the aging indicator cluster correlation degree set; performing key indicator screening on each indicator cluster in the aging indicator clustering update result based on the aging indicator cluster screening threshold set to determine the aging performance key evaluation indicator set.

[0057] The specific configuration of the performance test result acquisition module 50 will be described in detail below. The performance test result acquisition module 50 further includes: performing a criticality evaluation on each branch network in the index aging performance evaluation branch network set to obtain a branch network criticality coefficient set; performing output performance verification on each branch network in the index aging performance evaluation branch network set to obtain a branch network precise factor set; and constructing a branch network decision function: ,in, represents the criticality coefficient of the nth branch network, Identify the criticality coefficient of the detection factor, Identify the nth branch network precise factor; perform parameter calculation on the branch network criticality coefficient set and the branch network precise factor set based on the branch network decision function to obtain a branch network decision parameter set; perform weighted integration fusion on the indicator aging performance evaluation branch network set based on the branch network decision parameter set to obtain the UHV MOS aging adaptive evaluator.

[0058] The scenario-adaptive aging test system for UHV MOS provided in the embodiment of the present invention can execute the scenario-adaptive aging test method for UHV MOS provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of 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 scenario-adaptive aging test method for UHV MOS, characterized in that: The method comprises: Establishing a device aging test platform, the device aging test platform includes an environmental test chamber, a host computer, a test fixture and a test evaluation module; The host computer performs test condition analysis on the application scenario information of the target UHV MOS device to generate an aging test condition parameter table; The target UHV MOS device is fixedly mounted on the test fixture, and a pre-test adjustment is performed on the target UHV MOS device based on the aging test condition parameter table through the environmental test chamber to determine an aging test update parameter table; Perform aging test monitoring on the target UHV MOS device based on the aging test update parameter table to obtain a device aging scenario test data stream set; The UHV MOS aging adaptive evaluator is called through the test evaluation module, and the device aging scenario test data stream set is processed and evaluated based on the UHV MOS aging adaptive evaluator to obtain the device scenario aging performance test result.

2. The scenario-adaptive aging test method for UHV MOS according to claim 1, characterized in that: The step of generating the aging test condition parameter table includes: Extracting elements of the application scenario information of the target UHV MOS device to obtain device application scenario element information; According to the device application scenario element information, test condition analysis is performed on each application scenario in the application scenario information in turn to obtain a device scenario test element parameter set; Determine the device scenario aging test parameter set according to the device aging test objectives; The device scenario test factor parameter set and the device scenario aging test parameter set are combined by parameter design to generate the aging test condition parameter table.

3. The scenario-adaptive aging test method for UHV MOS according to claim 1, characterized in that: The step of determining an aging test update parameter table includes: Performing pre-test monitoring on the target UHV MOS device based on the aging test condition parameter table to obtain a device aging pre-test data stream set; Performing performance evaluation on the target UHV MOS device based on the device aging pre-test data stream set to obtain a device aging performance pre-test result; Performing abnormal threshold analysis on the device aging performance pre-test results to determine device performance abnormality test parameter thresholds; The aging test condition parameter table is adjusted and optimized based on the device performance abnormality test parameter threshold to determine the aging test update parameter table.

4. The scenario-adaptive aging test method for UHV MOS according to claim 1, characterized in that: The calling of the UHV MOS aging adaptive evaluator comprises: Acquiring a UHV MOS aging test data set, performing key indicator analysis on the UHV MOS aging test data set, and determining a key evaluation indicator set for aging performance; According to the aging performance key evaluation indicator set, the UHV MOS aging test data set is shunted and evaluated to obtain a key indicator aging test sample set; Performing network structure selection and evaluation training on the key indicator aging test sample sets respectively to generate an indicator aging performance evaluation branch network set; The indicator aging performance evaluation branch network set is integrated and fused to obtain a UHV MOS aging adaptive evaluator and store it in the test evaluation module.

5. The scenario-adaptive aging test method for UHV MOS according to claim 4, characterized in that: The key evaluation index set for aging performance is determined, including: Extracting related indicators from the UHV MOS aging test data set to obtain a device aging related evaluation indicator set; Based on the UHV MOS aging test data set, a clustering operation is performed on the device aging associated evaluation index set to obtain a clustering result of the associated aging index; Performing intra-cluster divergence and inter-cluster divergence calculation and evaluation on the clustering results of the associated aging indicators to determine a cluster divergence quality index; Based on the cluster divergence quality index, the clustering result of the associated aging indicators is optimized and updated, and key indicators are screened to determine the aging performance key evaluation indicator set.

6. The scenario-adaptive aging test method for UHV MOS according to claim 5, characterized in that: Determining the aging performance key evaluation indicator set includes: Iteratively optimizing and updating the associated aging indicator clustering result based on the cluster divergence quality index until a preset termination condition is reached to obtain an aging indicator clustering update result; Performing a correlation evaluation on each indicator cluster in the aging indicator clustering update result to obtain an aging indicator cluster correlation degree set; Determining an aging indicator cluster screening threshold set according to the aging indicator cluster association degree set; Based on the aging indicator cluster screening threshold set, key indicators of each indicator cluster in the aging indicator clustering update result are screened respectively to determine the aging performance key evaluation indicator set.

7. The scenario-adaptive aging test method for UHV MOS according to claim 4, characterized in that: The method of obtaining the UHV MOS aging adaptive evaluator comprises: Performing a criticality assessment on each branch network in the indicator aging performance assessment branch network set to obtain a branch network criticality coefficient set; Verifying the output performance of each branch network in the indicator aging performance evaluation branch network set to obtain an accurate factor set of the branch network; Construct a branch network decision function: ,in, Representative The branch network criticality coefficient, Identify the criticality coefficient of the detection factor, Identification The branch network precision factor; Perform parameter calculation on the branch network criticality coefficient set and the branch network precise factor set based on the branch network decision function to obtain a branch network decision parameter set; The indicator aging performance evaluation branch network set is weightedly integrated and fused based on the branch network decision parameter set to obtain the ultra-high voltage MOS aging adaptive evaluator.

8. The scenario-adaptive aging test system for UHV MOS is characterized by: The system is used to implement the scenario-adaptive aging test method for UHV MOS according to any one of claims 1 to 7, and the system comprises: A device aging test platform establishment module is used to establish a device aging test platform, wherein the device aging test platform includes an environmental test chamber, a host computer, a test fixture and a test evaluation module; A test condition analysis module, used to analyze the application scenario information of the target UHV MOS device through the host computer to generate an aging test condition parameter table; A pre-test adjustment module, used for fixing the target UHV MOS device on the test fixture, performing pre-test adjustment on the target UHV MOS device based on the aging test condition parameter table through the environmental test chamber, and determining an aging test update parameter table; An aging test monitoring module, used to perform aging test monitoring on the target UHV MOS device based on the aging test update parameter table, and obtain a device aging scenario test data stream set; The performance test result acquisition module is used to call the UHV MOS aging adaptive evaluator through the test evaluation module, process and evaluate the device aging scenario test data stream set based on the UHV MOS aging adaptive evaluator, and obtain the device scenario aging performance test result.

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