Chip performance test system
By designing a chip performance testing system containing multiple functional modules, the shortcomings of chip performance testing in the prior art under fixed temperature conditions are solved, and the automatic optimization of chip performance under different temperature conditions is achieved, and the accuracy and efficiency of the test are improved.
Patent Information
- Application Number
- CN202510229174.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-28
- Publication Date
- 2025-06-13
AI Technical Summary
Existing chip performance testing methods are usually evaluated under fixed or limited temperature conditions, and cannot fully understand the performance of the chip in the actual working environment, and are inefficient and prone to human errors.
A chip performance testing system is designed, including a startup module, a temperature control module, a contact point monitoring module, a performance testing module, an impact identification module, a prediction module, a solution adjustment module and a data generation module. Through the preset gradient temperature scheme, the system monitors the temperature of each contact point of the chip in real time, recognizes the impact of temperature changes on performance parameters, uses machine learning algorithms to build a prediction model, dynamically adjusts the temperature delivery scheme, and achieves automatic performance optimization.
The system can adjust the temperature of each contact point more accurately, achieve automatic optimization of performance, greatly reduce human intervention, improve the accuracy and efficiency of testing, and can adapt to temperature changes in real time during the testing process, provide the best testing environment, and improve the reliability and effectiveness of testing.
Smart Images
Figure CN120142899A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of chip testing, and particularly to a chip performance testing system. Background Art
[0002] With the continuous innovation and technological progress of electronic products, especially in the fields of mobile phones, computers, automotive electronics, and Internet of Things devices, the complexity and performance requirements of chips have been continuously increasing. The demand for high-performance, low-power, and highly reliable electronic chips is increasing day by day, which has promoted the continuous evolution of chip design, manufacturing, and testing technologies. As the requirements for security and reliability in the application fields of electronic devices have increased, the testing and verification standards for chips in the industry have become more stringent than before;
[0003] The temperature change of the chip in different working environments will significantly affect its performance. High temperature or low temperature may both lead to increased power consumption, decreased speed, or potential failures. To ensure that the chip can also work stably in high temperature, low temperature, or extreme environments, designers must conduct comprehensive temperature tests and evaluations during the development stage;
[0004] Many traditional chip performance testing methods may only evaluate under fixed or limited temperature conditions, which may not comprehensively understand the performance of the chip in the actual working environment. They often rely on manual adjustment of temperature and test parameters, with low efficiency and prone to human errors. They lack flexibility in performance prediction, often rely on fixed models, and do not adapt to the rapidly changing technological requirements. They only focus on certain specific performance parameters and cannot comprehensively measure the performance of the chip in different environments. Summary of the Invention
[0005] (1) Technical Problems to be Solved
[0006] In view of the above-mentioned drawbacks of the prior art, the present invention provides a chip performance testing system, which can effectively solve the problems of the prior art.
[0007] (2) Technical Solutions
[0008] To achieve the above object, the present invention is realized through the following technical solutions:
[0009] The present invention discloses a chip performance testing system, including:
[0010] A startup module, which is used as a management terminal to start each functional module and perform preliminary configuration parameters, and performs a hardware self-check during initialization. The hardware self-check is performed twice. The first self-check uses a low-power self-check, and the second self-check uses a high-power self-check;
[0011] A temperature control module, for a preset gradual temperature scheme. According to the preset gradual temperature scheme, it controls the ambient temperature at different times to heat or cool the chip working environment to the target temperature, and monitors the temperature of each contact point of the chip in real time through a temperature sensor, providing a time series record of temperature changes; the gradual temperature scheme adopts a two-time heating and cooling scheme of first increasing from 5°C to 95°C, then cooling to -20°C, then increasing to 100°C, and then cooling to 25°C.
[0012] A contact point monitoring module, for monitoring and recording the temperature status, performance parameter changes, and environmental conditions of each contact point of the chip.
[0013] A performance testing module, for applying performance tests of several preset items when each contact point is at a set temperature.
[0014] An influence identification module, for each contact point, identifying the influence coefficient of temperature change on performance parameters, calculating through statistical analysis methods, and summarizing the data of the influence coefficients.
[0015] A prediction module, through a machine learning algorithm, constructs a prediction model, trains based on historical influence coefficients, chip data, and sample data of the gradual temperature scheme, and the trained prediction model predicts the performance of each contact point of the chip at different temperatures.
[0016] A scheme adjustment module, for dynamically adjusting the temperature delivery scheme according to the content predicted and output by the prediction module, setting a new temperature application strategy, evaluating the temperature delivery scheme at the end of each test cycle, and preferentially recommending the temperature delivery scheme with a higher score.
[0017] A data generation module, for automatically generating a specific performance test report according to the test results and analysis data, and submitting it to the startup module.
[0018] Furthermore, the test cycle and temperature range in the preliminary configuration parameters of the startup module are input by the user or loaded according to a preset configuration file. When the user does not make an input, the test system automatically evaluates whether the preset configuration file matches after loading the preset configuration file. If it is found that the preset configuration file is not very matching, the test system recommends the closest configuration file as a reference and reminds the user to adjust the configuration parameters. If the user confirms not to make adjustments, no adjustments will be made, and the test system selects the preset configuration file based on the chip weight.
[0019] Furthermore, the startup module is connected to a data storage module through wireless network interaction. The data storage module is used to collect, store, and manage temperature records, performance parameters, and influence coefficients during the test process, organizes and indexes the data using a database management system, and provides a data backup and recovery mechanism.
[0020] Furthermore, the performance test content of the performance test module includes: data processing speed, throughput, and signal latency.
[0021] Furthermore, the expression of the prediction model constructed by the prediction module is:
[0022] P i (T) = k 0 + k 1 T + k 2 T 2 + k 3 T 3 +... + k n T n + e i ;
[0023] In the formula, P i (T) represents the performance parameter of the contact point i at temperature T, k 0 represents the intercept term, indicating the baseline value of the performance at zero degree, k 1 T, k 2 T 2 , k 3 T 3 ,..., k n T n represent the regression coefficients, indicating the degree of influence of temperature on the performance parameter P, where each regression coefficient k j represents the coefficient of the j-th power influence of temperature on the performance parameter P, n represents the maximum temperature power in the model, T represents temperature, and e i represents the error term.
[0024] Furthermore, the regression coefficients are estimated through historical sample data, and the regression coefficients are selected to minimize the sum of the squares of the errors between the predicted values and the actual observed values.
[0025] Furthermore, the temperature delivery plan preferentially recommended by the plan adjustment module targets the startup module for transmission, and the temperature delivery plan is submitted to the startup module as the preset configuration file of the startup module.
[0026] Furthermore, the plan adjustment module is connected to a cycle management module through wireless network interaction. The cycle management module is used to manage the scheduling of the entire test cycle, including starting, pausing, and ending each test stage, setting a single test mode or a loop test mode. When an abnormal interruption occurs, parameters are instantaneously recorded. The parameters include the power supply test setting parameters of the test equipment and the chip environment parameters. The instantaneously recorded parameters are directly imported into the latest parameter settings of the test equipment, and the state before the interruption can be restored. When starting the recovery program, the test equipment only records data when all parameters meet the instantaneously recorded parameters; otherwise, no data is recorded.
[0027] Furthermore, the data generation module provides a user interface that allows users to manually adjust settings, view the test process, and obtain real-time data. The specific performance test report includes: performance parameters of each contact point, temperature impact analysis, and optimization suggestions, and allows users to customize the report format and content according to their needs.
[0028] Furthermore, the startup module is interactively connected to the temperature control module via a wireless network. The temperature control module is interactively connected to the contact point monitoring module via a wireless network. The impact identification module is interactively connected to the contact point monitoring module, the performance test module, and the prediction module via a wireless network. The prediction module is interactively connected to the solution adjustment module via a wireless network. The solution adjustment module is interactively connected to the data generation module via a wireless network.
[0029] (III) Beneficial Effects
[0030] Adopting the technical solution provided by the present invention, compared with the known prior art, it has the following beneficial effects:
[0031] 1. By analyzing the performance influencing factors based on historical data and using machine learning technology to establish a prediction model, the system can continuously optimize the temperature delivery plan according to previous test results, so as to more accurately adjust the temperature of each contact point in subsequent tests, achieve automatic optimization of performance, greatly reduce human intervention, and improve the accuracy and efficiency of testing.
[0032] 2. By obtaining the temperature of each contact point in real time and dynamically adjusting the delivery plan according to the prediction results of the self-learning algorithm, compared with the traditional static test method, the system can adapt to temperature changes in real time during the test, provide the best test environment for each contact point, and can more realistically simulate the actual use conditions, ultimately improving the reliability and effectiveness of the test.
[0033] 3. The system can not only test a single performance parameter, but also comprehensively consider multiple performance indicators, and analyze the association and mutual influence between each parameter through the impact identification module. Through multi-dimensional analysis methods, engineers can comprehensively understand the performance of the chip under different conditions, especially in the design of multi-functional integrated circuits, which promotes better design decisions. Description of the Drawings
[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0035] Figure 1 Schematic diagram of the framework of the present invention.
[0036] The reference numerals in the figure respectively represent: 1, startup module; 2, temperature control module; 3, contact point monitoring module; 4, performance testing module; 5, impact identification module; 6, prediction module; 7, scheme adjustment module; 8, data generation module; 9, data storage module; 10, cycle management module. Detailed implementation manners
[0037] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.
[0038] The present invention will be further described below with reference to the embodiments.
[0039] Embodiment 1
[0040] A chip performance testing system according to this embodiment, as Figure 1 shown, includes:
[0041] Startup module 1, used as a management terminal, to start each functional module and perform preliminary configuration parameters, and perform hardware self-check during initialization; during hardware self-check, it is self-checked twice. The first self-check uses low-power self-check, and the second self-check uses high-power self-check; during hardware self-check, it is self-checked twice. The first self-check uses low-power self-check, and the second self-check uses high-power self-check. The main purpose is that the power of the test system will be affected by the power requirement, resulting in power fluctuations. To ensure that the test system can run more stably, it is therefore self-checked once with low power and once with high power to ensure the reliability of the test system;
[0042] The test cycle and temperature range in the preliminary configuration parameters are input by the user or loaded according to a preset configuration file;
[0043] When the user does not make an input, after the test system loads the preset configuration file, it automatically evaluates whether the preset configuration file is matched. If it is found that the preset configuration file is not well-matched, the test system recommends the closest configuration file as a reference and reminds the user to adjust the configuration parameters. If the user confirms not to make adjustments, no adjustments will be made. The test system selects the preset configuration file based on the chip weight. This scheme design is beneficial to assist the test user to screen and adjust the most suitable configuration file according to the characteristics of the chip, improve the test scheme, and enhance the rationality of the test scheme;
[0044] The startup module 1 is connected to the data storage module 9 through wireless network interaction. The data storage module 9 is used to collect, store, and manage temperature records, performance parameters, and influence coefficients during the test process. It uses a database management system to organize and index the data, and provides a data backup and recovery mechanism. It can efficiently store, retrieve, and analyze a large amount of data generated during the test process, which not only improves the efficiency of data processing, but also provides guarantee for subsequent data backup and recovery, thus reducing the risk of data loss.
[0045] The temperature control module 2 is used for a preset gradual temperature scheme. According to the preset gradual temperature scheme, it controls the ambient temperature to heat or cool the chip working environment to the target temperature at different times, and real-time monitors the temperature of each contact point of the chip through a temperature sensor, providing a time series record of temperature changes. The gradual temperature scheme adopts a two-time heating and cooling scheme of first rising from 5°C to 95°C, then cooling to -20°C, then rising to 100°C, and then cooling to 25°C. By means of two consecutive different heating and cooling schemes, the chip is tested in a rapidly cooled and heated environment, which can not only test the performance under normal environment, but also detect the chip performance under extreme environment.
[0046] The contact point monitoring module 3 is used to monitor and record the temperature status, performance parameter changes, and environmental conditions of each contact point of the chip.
[0047] The performance testing module 4 is used to apply performance tests of several preset items when each contact point is at the set temperature. The performance test contents include: data processing speed, throughput, and signal delay.
[0048] The influence identification module 5 is used to identify the influence coefficient of temperature change on performance parameters for each contact point, calculate it through statistical analysis methods, and summarize the data of the influence coefficient.
[0049] The prediction module 6 constructs a prediction model through machine learning algorithms, trains based on the sample data of historical influence coefficients, chip data, and the gradual temperature scheme, and the trained prediction model predicts the performance of each contact point of the chip at different temperatures.
[0050] The scheme adjustment module 7 is used to dynamically adjust the temperature delivery scheme according to the content predicted and output by the prediction module 6, set a new temperature application strategy, evaluate the temperature delivery scheme at the end of each test cycle, and give priority to recommending the temperature delivery scheme with a higher score. The temperature delivery scheme preferentially recommended by the scheme adjustment module 7 targets the startup module 1, and submits the temperature delivery scheme to the startup module 1 as the preset configuration file of the startup module 1.
[0051] The scheme adjustment module 7 is connected to the cycle management module 10 through wireless network interaction. The cycle management module 10 is used to manage the scheduling of the entire test cycle, including starting, pausing, and ending each test stage, setting a single test mode or a loop test mode. When an abnormal interruption occurs, parameters are instantaneously recorded. The parameters include the power supply test setting parameters of the test equipment and the chip environment parameters. The instantaneously recorded parameters are directly imported into the latest parameter settings of the test equipment, and then the state before the interruption can be restored. When starting the recovery program, the test equipment only records data when all parameters meet the instantaneously recorded parameters; otherwise, it does not record.
[0052] The data generation module 8 is used to automatically generate a specific performance test report based on the test results and analysis data and submit it to the start module 1. The data generation module 8 provides a user interface that allows users to manually adjust settings, view the test progress, and obtain real-time data. The specific performance test report includes: the performance parameters of each contact point, the temperature impact analysis, and optimization suggestions. It allows users to customize the report format and content according to their needs. The automatically generated specific performance test report reduces manual intervention, improves the efficiency and accuracy of report generation. Users can customize the report format according to their needs, and this flexibility can meet the specific needs of different users. The automatically generated specific performance test report reduces manual intervention, improves the efficiency and accuracy of report generation. Users can customize the report format according to their needs, and this flexibility can meet the specific needs of different users.
[0053] The start module 1 is connected to the temperature control module 2 through wireless network interaction. The temperature control module 2 is connected to the contact point monitoring module 3 through wireless network interaction. The impact identification module 5 is connected to the contact point monitoring module 3, the performance test module 4, and the prediction module 6 through wireless network interaction. The prediction module 6 is connected to the scheme adjustment module 7 through wireless network interaction. The scheme adjustment module 7 is connected to the data generation module 8 through wireless network interaction.
[0054] Compared with the prior art, by presetting a gradient temperature scheme and real-time temperature monitoring, the test conditions of the chip at different ambient temperatures can be accurately controlled, and the performance of the chip under different temperature conditions can be evaluated more comprehensively, thereby improving the accuracy and reliability of the test. Through the analysis of the impact of temperature changes on performance parameters, the system can identify and quantify the impact of different temperatures on the chip performance, which provides a scientific basis for optimizing chip design and testing.
[0055] The prediction model established by using machine learning algorithms can be trained based on historical data and predict the performance of the chip at different temperatures, which can greatly improve the test efficiency and reduce the number of actual tests. According to the prediction results, the temperature application scheme is dynamically adjusted. This real-time feedback mechanism can continuously optimize the test process and improve the adaptability and effectiveness of the test.
[0056] Example 2
[0057] On other levels, this embodiment also provides an expression for constructing a prediction model, specifically:
[0058] P i (T) = k 0 + k 1 T + k 2 T 2 + k 3 T 3 +... + k n T n + e i ;
[0059] In the formula, P i (T) represents the performance parameter of the contact point i at temperature T, k 0 represents the intercept term, indicating the baseline value of the performance at zero degree, k 1 T, k 2 T 2 , k 3 T 3 ,..., k n T n represent the regression coefficients, indicating the degree of influence of temperature on the performance parameter P. Each regression coefficient k j represents the coefficient of the jth power influence of temperature on the performance parameter P, n represents the maximum temperature power in the model, T represents the temperature, and e i represents the error term; the regression coefficients are estimated through historical sample data, and the regression coefficients are selected to minimize the sum of the squares of the errors between the predicted values and the actual observed values.
[0060] Compared with the prior art, through the form of polynomial, the non - linear relationship between temperature and performance parameters can be effectively captured. In many cases, the influence of temperature on performance is not linear, and using a simple linear model may not accurately reflect this complexity. The temperature coefficients in the model are adjustable, allowing the model to be flexibly adjusted according to the complexity of the actual data. Higher - order polynomials can better adapt to the data, while lower - order polynomials can provide a relatively simple model, which helps to prevent overfitting;
[0061] The form of the model is relatively simple, easy to understand and interpret. Each regression coefficient represents the specific influence of temperature on the performance parameter, facilitating the analysis and interpretation of how temperature changes affect chip performance. Polynomial regression is usually more adaptable to small - sample data. In the case of limited sample size, a reasonable fit can be found through appropriate polynomial powers. The model can be updated in real - time after new data input, automatically adjusting the regression coefficients to maintain the prediction accuracy of the model.
[0062] In the specific implementation of the present invention, through presetting a gradient temperature scheme and real-time temperature monitoring, the test conditions of the chip at different ambient temperatures can be accurately controlled, and the performance of the chip under different temperature conditions can be evaluated more comprehensively, thereby improving the accuracy and reliability of the test. Through the analysis of the influence of temperature changes on performance parameters, the system can identify and quantify the influence of different temperatures on the chip performance, which provides a scientific basis for optimizing chip design and testing. The prediction model established by using machine learning algorithms can be trained based on historical data and predict the chip performance at different temperatures, which can greatly improve the test efficiency and reduce the number of actual tests. According to the prediction results, the temperature application scheme is dynamically adjusted. This real-time feedback mechanism can continuously optimize the test process and improve the adaptability and effectiveness of the test;
[0063] In summary, the present invention analyzes the performance influencing factors based on historical data and uses machine learning technology to establish a prediction model, enabling the system to continuously optimize the temperature application scheme according to the previous test results, so as to more accurately adjust the temperature of each contact point in subsequent tests and achieve automatic optimization of performance, greatly reducing human intervention and improving the accuracy and efficiency of the test. By obtaining the temperature of each contact point in real time and dynamically adjusting the application scheme according to the prediction results of the self-learning algorithm, compared with the traditional static test method, the system can adapt to temperature changes in real time during the test, provide the best test environment for each contact point, and can more realistically simulate the actual use conditions, ultimately improving the reliability and effectiveness of the test;
[0064] The system can not only test a single performance parameter, but also comprehensively consider multiple performance indicators, and analyze the association and mutual influence between various parameters through the influence identification module 5. Through multi-dimensional analysis methods, engineers can comprehensively understand the performance of the chip under different conditions, especially in the design of multi-functional integrated circuits, promoting better design decisions.
[0065] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A chip performance testing system, characterized in that: include: The startup module (1) is used as a management terminal to start each functional module and perform preliminary configuration parameters. During initialization, the hardware self-test is performed twice. The first self-test adopts low-power self-test and the second self-test adopts high-power self-test. The temperature control module (2) is used for a preset gradual temperature scheme. According to the preset gradual temperature scheme, the ambient temperature is controlled at different times to heat or cool the chip working environment to a target temperature. The temperature of each contact point of the chip is monitored in real time by a temperature sensor to provide a time series record of the temperature change. The gradual temperature scheme adopts a two-time heating and cooling scheme of first heating from 5°C to 95°C, then cooling to -20°C, then heating to 100°C, and then cooling to 25°C. A contact point monitoring module (3), used to monitor and record the temperature state, performance parameter changes and environmental conditions of each contact point of the chip; A performance test module (4) is used to apply a plurality of preset performance tests when each contact point is at a set temperature; An influence identification module (5) is used to identify the influence coefficient of temperature change on the performance parameter for each contact point, calculate it by statistical analysis method, and summarize the data of the influence coefficient; Prediction module (6), constructing a prediction model through a machine learning algorithm, and training based on historical impact coefficients, chip data and sample data of a gradual temperature scheme, wherein the trained prediction model predicts the performance of each contact point of the chip at different temperatures; A scheme adjustment module (7) is used to dynamically adjust the temperature delivery scheme according to the content predicted and output by the prediction module (6), set a new temperature application strategy, evaluate the temperature delivery scheme after each test cycle, and give priority to recommending the temperature delivery scheme with a higher score; The data generation module (8) is used to automatically generate a specific performance test report based on the test results and analysis data, and submit it to the start module (1).
2. A chip performance testing system according to claim 1, characterized in that: The test cycle and temperature range in the preliminary configuration parameters of the startup module (1) are input by the user or loaded according to a preset configuration file. When the user does not make any input, the test system automatically evaluates whether the preset configuration file matches after loading the preset configuration file. If it is found that the preset configuration file does not match enough, the test system recommends the closest configuration file as a reference and reminds the user to adjust the configuration parameters. If the user confirms that no adjustment is made, no adjustment is made, and the test system selects the preset configuration file based on the chip weight.
3. A chip performance testing system according to claim 1, characterized in that: The startup module (1) is interactively connected to a data storage module (9) via a wireless network. The data storage module (9) is used to collect, store and manage temperature records, performance parameters and influence coefficients during the test process, use a database management system to organize and index the data, and provide a data backup and recovery mechanism.
4. A chip performance testing system according to claim 1, characterized in that: The performance test content of the performance test module (4) includes: data processing speed, throughput and signal delay.
5. A chip performance testing system according to claim 1, characterized in that: The prediction model constructed by the prediction module (6) is expressed as: P i (T)=k0+k1T+k2T 2 +k3T 3 +...+k n T n +e i ; Where P i (T) represents the performance parameter of contact point i at temperature T, k0 represents the intercept term, indicating the baseline value of the performance at zero degrees, k1T, k2T 2 ,k3T 3 , ..., k n T n Represents the regression coefficient, indicating the influence of temperature on the performance parameter P. Each regression coefficient k j represents the coefficient of the effect of temperature on the performance parameter P to the jth power, n represents the maximum temperature power in the model, T represents temperature, e i represents the error term.
6. A chip performance testing system according to claim 5, characterized in that: The regression coefficient is estimated by historical sample data, and the regression coefficient is selected so as to minimize the sum of squares of the errors between the predicted value and the actual observed value.
7. A chip performance testing system according to claim 1, characterized in that: The temperature delivery plan preferentially recommended by the plan adjustment module (7) takes the startup module (1) as the transmission target, and submits the temperature delivery plan to the startup module (1) as a preset configuration file of the startup module (1).
8. A chip performance testing system according to claim 1, characterized in that: The scheme adjustment module (7) is interactively connected to a cycle management module (10) via a wireless network. The cycle management module (10) is used to manage the scheduling of the entire test cycle, including starting, pausing and ending each test phase, setting a single test mode or a cyclic test mode, and instantaneously recording parameters when an abnormal interruption occurs. The parameters include power supply test setting parameters and chip environment parameters of the test equipment. The instantaneously recorded parameters are directly imported into the latest parameter settings of the test equipment to restore the state before the interruption. When the recovery program is started, the test equipment will only record data when all parameters meet the instantaneous recording parameters, otherwise no recording will be performed.
9. A chip performance testing system according to claim 1, characterized in that: The data generation module (8) provides a user interface, allowing the user to manually adjust settings, view test progress and obtain real-time data. The specific performance test report includes: performance parameters of each contact point, temperature impact analysis and optimization suggestions, allowing the user to customize the report format and content according to needs.
10. A chip performance testing system according to claim 1, characterized in that: The startup module (1) is interactively connected to the temperature control module (2) via a wireless network, the temperature control module (2) is interactively connected to the contact point monitoring module (3) via a wireless network, the impact identification module (5) is interactively connected to the contact point monitoring module (3), the performance testing module (4) and the prediction module (6) via a wireless network, the prediction module (6) is interactively connected to the solution adjustment module (7) via a wireless network, and the solution adjustment module (7) is interactively connected to the data generation module (8) via a wireless network.