47 results about "Test optimization" patented technology

The invention is applicable to the technical field of interface testing, and provides an artificial intelligence-based interface testing optimization method, which comprises the following steps: constructing a multi-dimensional interface knowledge graph of a tested system, the multi-dimensional interface knowledge graph comprising but not limited to static structure information, business semantic information and running state feature information; based on the multi-dimensional interface knowledge graph, the driving state and the action space, deploying a test agent based on reinforcement learning; in the test agent, according to a preset multi-target reward function, executing a target-oriented exploration action, and generating a dynamic test case; according to the method, the twinborn test environment of the tested system is constructed for the test agent to perform exploratory test and generate the test case set, the value density of the test cases generated by the method is high, defects can be effectively found, the test cases are associated with interface service semantics and operation rules, and the reliability of the test cases is improved.

The invention relates to the technical field of software engineering and automatic testing, in particular to an E2E scene test optimization method and system based on target man-machine cooperation. According to the scheme, an optimization target is manually set, an initial test case and a business process are input, and a test resource library is constructed; the system automatically analyzes a service path, generates a use case dependency graph and a key path, and determines a core scene through manual verification; a candidate optimization strategy is generated by the system, and a target strategy is determined through manual screening according to resources and priorities; the system carries out simplification, merging and scheduling optimization on the use cases, and deploys and executes the use cases after manual sampling verification of coverage; the system collects execution data in real time and generates an evaluation report, and whether a use case is supplemented or a strategy is adjusted is determined after manual analysis; and finally updating the resource library and the strategy model, establishing a dynamic feedback mechanism, and triggering continuous optimization during system iteration. According to the method, the E2E test efficiency and the software delivery quality are remarkably improved through man-machine cooperation and closed-loop optimization.

The utility model discloses a transmission shaft torsional fatigue testing machine, which relates to the technical field of transmission shaft testing and comprises a workbench, a torsion component arranged on one side of the top surface of the workbench, a slide rail component arranged on the other side of the top surface of the workbench, and an angle adjusting mechanism arranged on the top surface of the slide rail component. A supporting component is arranged between the sliding rail assembly and the angle adjusting mechanism, the supporting component is arranged on the top face of the workbench, and a protection assembly is arranged above the workbench. In the using process of the device, the transmission shaft can be stably clamped, and accurate torsion testing can be achieved; the structure of the testing machine is optimized, and stability and reliability are improved; wear-resistant materials and structural reinforcement design are adopted, vulnerable parts are reduced, the service life is prolonged, a comprehensive and reliable basic database can be established through a fatigue life test, analysis design reliability is provided, development time is shortened, development cost is reduced, and the problems of product life reliability and bearing capacity are solved.

The invention provides a fan blade lightning protection conduction testing method and system based on machine learning, and relates to the technical field of lightning protection conduction testing, and the method comprises the steps: carrying out the current testing of a fan blade lightning protection system through a multi-channel MOS tube control circuit; performing multi-dimensional feature extraction and local feature analysis on the current response data; carrying out feature enhancement and defect identification based on the local feature sequence, and carrying out multistage clustering on an identification result; and performing global health analysis and defect traceability of lightning protection conduction performance on the fan blade lightning protection system according to a defect classification result, generating a defect attribution point location for monitoring, performing feedback optimization on a multi-channel MOS tube control circuit, and constructing a test optimization closed loop. According to the invention, the technical problem that the lightning protection conduction test efficiency is low due to the fact that the static conduction test is difficult to identify early hidden defects in the prior art is solved, the current test is carried out through the multi-channel MOS tube control circuit, and the lightning protection conduction test efficiency is improved.

The invention provides a multi-axis loading five-dimensional force sensor precision test method and system, and relates to the technical field of sensor testing, and the method comprises the steps: simulating a five-dimensional force sensor through a multi-axis loading platform, obtaining simulation loading data, carrying out the data collection of the five-dimensional force sensor, and carrying out the deviation precision calculation, performing analysis and calibration based on the measurement deviation value, performing correction compensation on the five-dimensional force sensor, performing cyclic loading test based on compensation parameters, performing verification optimization on the compensation parameters, and backtracking compensation optimization data to the cyclic loading test for data iteration update to form a test optimization closed loop of the five-dimensional force sensor. The technical problems that in the prior art, a precision testing method of a five-dimensional force sensor in a multi-axis loading environment has limitation, and the performance of the sensor cannot be comprehensively evaluated are solved. The technical effects of comprehensively evaluating the performance of the five-dimensional force sensor under the multi-dimensional load and improving the measurement precision and reliability of the five-dimensional force sensor are achieved.

The invention discloses a motor testing system based on a sliding frame and a guide plate, and relates to the field of motor testing. The test rack module is welded by a Q235B steel plate and is fixed by an expansion bolt; the sliding frame module is composed of a sliding base, a connecting beam and a supporting platform and is connected with a spring for buffering. The guide plate module comprises symmetrical guide plates which are finely adjusted through a sliding block and an adjusting assembly. The motor fixing module comprises an L-shaped baffle, a spring and a clamping bolt, and a built-in pressure sensor is used for measuring clamping force; an output shaft of the test driving module is connected with a torque sensor and a tested motor, and is provided with a controller and an acquisition module; the data acquisition module synchronously acquires multiple parameters, and a report is generated through a touch screen display, storage and software setting process; the buffering and damping module reduces noise and vibration and corrects the level through a gasket, a foot pad and a sizing block, and stable operation of the device is guaranteed. The method is fast adaptive to multi-model motor testing, optimizes the traditional technology, improves the detection efficiency and accuracy, guarantees the testing stability and reliability, and meets the batch testing requirements.

The embodiment of the invention discloses an energy flow test and correction method and device for a hydraulic system of a flowing machine and a medium, relates to the technical field of equipment energy efficiency test optimization, and is used for solving the problem of test misalignment in an existing mode. The method comprises the following steps: defining test action demand data of a to-be-tested mobile machine through preset typical operation action characteristics of a data acquisition and analysis system; the test action demand data is received based on the controller and combined with the multi-sensor information, and an electro-hydraulic control signal is generated to control the action of the electro-proportional hydraulic valve, so that the to-be-tested flowing machine executes the corresponding test action under the preset environment load, and the action control can be repeated; acquiring initial measurement data corresponding to each test action acquired by the CAN bus, correcting the initial measurement data based on a preset correction strategy, and outputting the corrected measurement data; and correcting the energy flow of the to-be-tested flow mechanical hydraulic system based on the corrected measurement data and the data acquired by the test platform sensor for the test action.

The invention discloses a matching optimization device for a mechanical characteristic test of a vacuum contactor type circuit breaker, which relates to the technical field of vacuum contactor type circuit breakers and comprises a mechanical characteristic tester, a mechanical characteristic test matching optimization instrument, the vacuum contactor type circuit breaker and a secondary socket, the mechanical characteristic tester is electrically connected with the vacuum contactor circuit breaker through the mechanical characteristic test matching optimization instrument and the secondary socket, and the mechanical characteristic test matching optimization instrument tests the vacuum contactor circuit breaker by switching an opening and closing loop between the mechanical characteristic tester and the vacuum contactor circuit breaker; the mechanical characteristic tester can be prevented from being directly connected with the vacuum contactor circuit breaker, the problems of long time consumption, wiring errors and short circuit of the tester during manual wire clamp replacement in the mechanical characteristic test process are solved, the working efficiency of testers is greatly improved, the failure rate of the tester is reduced, and the detection operation of the vacuum contactor circuit breaker is convenient and rapid.

The invention relates to the technical field of vehicle bench tests, in particular to a vehicle bench endurance test optimization method, system and equipment, and the method comprises the steps: determining a frame strain measurement position based on historical vehicle model data, defining a response channel, and building a response boundary condition of a bench test through a statistical method; arranging a strain sensor at the strain measurement position, and collecting actual road load data; decomposing and synthesizing an actual road load into a bench excitation signal meeting the boundary condition, and generating a typical road spectrum for a bench test; converting the typical road spectrum into an optimized bench excitation signal through bench transfer characteristic analysis and an iterative test; in the optimization process, the rack excitation signal is verified and adjusted based on a damage equivalence principle; and synchronously applying the optimized bench excitation signal to a physical bench test and virtual simulation analysis to realize a test verification closed loop. And the test verification period is greatly shortened.

The invention relates to the technical field of code testing, in particular to a software code testing system and device and a storage medium, and the testing system comprises a static analysis module which is used for carrying out grammar and semantic analysis on source codes and generating an abstract syntax tree and a control flow diagram; the dynamic test module is used for executing source codes, monitoring behaviors during operation and capturing behavior abnormal data and code performance data; the knowledge graph construction module is used for constructing a code defect knowledge graph based on a historical defect database, and the code defect knowledge graph comprises an incidence relation between a code mode and a defect type; the test optimization engine is used for dynamically adjusting a test case generation strategy according to the static analysis result and the code defect knowledge graph; and the multi-dimensional evaluation module outputs a code coverage rate, a defect detection rate and a performance bottleneck analysis report. According to the software code test system, the test efficiency of the test optimization engine is improved through combination of the static analysis module and the dynamic test module; 48% of redundancy tests are reduced through priority distribution, and the test efficiency is further improved.

The invention discloses a low-damping air flotation system hybrid control method integrating intelligent parameter setting, and the method comprises the steps: obtaining a controlled object model according to the sweep frequency of an open-loop system and system identification, and constructing a closed-loop hybrid control model based on proportional integral differential control, speed / acceleration feedforward control and fuzzy sliding mode control; a closed-loop control framework is built by continuously calculating system output and control errors; a two-stage intelligent parameter setting method based on genetic algorithm preliminary setting and manual accurate setting is adopted to complete parameter adjustment of a hybrid control algorithm; and writing the hybrid control model into PMAC hardware, optimizing and adjusting control parameters according to step and sine response tests, and realizing high-precision machining of the low-damping air flotation system. According to the method, the response speed and the control precision of the system can be remarkably improved, nonlinear disturbance in a complex machining task can be adapted, and the parameter setting problem in actual engineering can be solved.

The invention belongs to the field of energy storage power station testing, relates to a data analysis technology, is used for solving the problem that the fault type occurrence frequency of an energy storage battery in different operation stages cannot be counted and analyzed in the prior art, and particularly relates to an energy storage power station preventive testing platform based on artificial intelligence. Comprising a stage evaluation module, a fault analysis module and a test optimization module which are in communication connection in sequence, and the stage evaluation module, the fault analysis module and the test optimization module are in communication connection with a database; according to the invention, the execution frequency of the test item can be dynamically adjusted according to the actual operation stage of the supervision object; the dynamic adaptive adjustment enables the test resources to be distributed more effectively, and the test resources are positively correlated with the fault occurrence probability, so that the waste of the test resources is avoided, the efficiency and the accuracy of the preventive test are improved, and the intelligent and refined operation and maintenance management of the energy storage power station is realized.

The application discloses an element replacement adaptive test optimization method and system, and relates to the technical field of element test optimization. The method comprises the following steps: extracting performance data and element types of scarce elements in target element replacement scene information, performing first-order multidimensional screening, and obtaining a verified rich element combination set; performing virtual characterization reverse fine-tuning, and obtaining a verified fine-tuning rich element combination set; obtaining a verified fine-tuning rich element combination sample set and a sputtering experiment result set; performing test evaluation according to a preset performance test type, and determining a target fine-tuning rich element combination. The application solves the technical problems of low test efficiency, high research and development loss, difficult performance guarantee and insufficient differentiation of rich element replacement scarce element test in the prior art, achieves the replacement test optimization of rich elements on scarce elements, improves the research and development efficiency, reduces the research and development loss, and guarantees the performance and differentiation potential of the rich element combination.

The invention discloses an element replacement adaptability test optimization method and system, and relates to the technical field of element test optimization, and the method comprises the steps: extracting scarce element performance data and scarce element types in target element replacement scene information, and carrying out first-order multi-dimensional screening to obtain a to-be-verified rich element combination set; performing virtual representation reverse fine tuning to obtain a fine tuning rich element combination set to be verified; obtaining a to-be-verified fine-tuning rich element combination sample set and a sputtering experiment result set; and performing test evaluation according to a preset performance test type, and determining a target fine-tuning rich element combination. The technical problems that in the prior art, the test efficiency of replacing scarce elements with rich elements is low, the research and development loss is high, the combination performance of the rich elements is difficult to guarantee, and differentiation is insufficient are solved, replacement test optimization of the scarce elements with the rich elements is achieved, the research and development efficiency is improved, and the test cost is reduced. The research and development loss is reduced; and the combination performance and differentiation potential of rich elements are guaranteed.

The invention discloses an automatic test optimization method and device based on reinforcement learning and a storage medium. According to the optimization method, a strategy model based on a neural network is utilized, corresponding first test action information is generated according to state information, and the state information comprises first feedback information currently fed back by an application program or an operating system; testing the application program according to the first test action information, and obtaining second feedback information corresponding to the test action information; generating reward information corresponding to the first test action information and the second feedback information; according to the state information, the first test action information and the reward information, track information used for optimizing a strategy model is constructed; and optimizing the strategy model by using a reinforcement learning method according to the track information. Intelligent and dynamic allocation of mobile application test resources is realized, so that the test resources are projected to functional modules with relatively high defect risks more accurately, and the overall efficiency and quality of automatic testing are improved.

The invention relates to the technical field of unmanned driving testing, in particular to a testing and evaluating method and system for airport unmanned driving equipment. The method comprises the following steps: calling a scene specificity parameter library according to airport operation data, obtaining a test scene and a quantitative index, and establishing a virtual-real test environment; triggering a multi-layer test request, and testing the equipment basic capability, the automatic driving basic capability, the equipment operation execution scene and the collaborative operation in sequence; obtaining layered test data, performing four-dimensional quantitative evaluation, and outputting a standard reaching condition according to an evaluation result; updating a scene specificity parameter library and a test parameter standard based on the evaluation result and the airport operation demand change, and precipitating data assets to form a reusable database; the system comprises a test preparation module, a hierarchical test execution module, a test result evaluation module and a test optimization iteration module. Through the mode, the operation precision is improved, the collaborative conflict is reduced, and the core demand of an airport for high-safety and high-efficiency operation is met.

The invention discloses a new energy automobile HIL double-engine cooperative automatic test method and system, and relates to the technical field of new energy automobile power testing, and the method comprises the steps: uploading collected configuration data, carrying out the automatic simulation configuration through an in-loop HIL simulation method, generating a test task, and distributing the test task to an HIL rack of each region, battery parameters and double-engine control parameters are obtained; according to the battery parameters and the double-engine control parameters, synchronous simulation of the battery and the double engines is conducted through an in-loop HIL simulation method, and real-time energy interaction data between the battery and the double engines is obtained; summarizing and analyzing according to the double-engine collaborative test data, and generating optimization suggestions of the double-engine collaborative automatic test. Through the dynamic power distribution method, power distribution of the motor and the internal combustion engine can be automatically adjusted according to the battery SOC and the double-engine control parameters collected in real time, cooperative work of the motor and the internal combustion engine is dynamically optimized, energy efficiency is improved in real time, and energy waste is reduced.

The invention provides a KPI comprehensive evaluation and test optimization method of an ADAS system. The method comprises the steps of obtaining a work log in an ADAS test process; based on the work log, calculating a KPI index used for evaluating the ADAS system function; evaluating the KPI index according to a preset judgment rule so as to identify a security attention event and a performance weakness event in the ADAS system; for each identified security attention event and performance weakness event, automatically intercepting data in a preset time window before and after occurrence of the events, and marking the data as attention events; and performing fault judgment on the concerned event, and generating a test case optimization suggestion. The technical problems that in the prior art, troubleshooting and test case optimization are disjointed, only single fault positioning can be carried out on recognized problems, and association logic among fault sources, scene elements and test cases is not established, so that quick tracing is difficult when sensing data exceptions occur in the test process are solved.

The invention provides a test case dynamic scheduling method and system based on an ant colony algorithm, and relates to the technical field of software test optimization. The method comprises the steps that core variables and parameters are initialized; analyzing the dependency relationship of the test cases; estimating the execution time of the test case according to the dependency relationship of the test case; selecting a to-be-executed test node according to the test case execution time; selecting a test case to be executed according to the task-node distribution table; according to the to-be-executed test case, updating a node operation state; according to the task execution result, the total completion time and the pheromone matrix, updating a test case execution state and the pheromone matrix; and obtaining an optimal scheduling scheme according to the current number of iterations or the total completion time fluctuation of continuous multiple iterations. According to the method, a load balancing problem is converted into an integer programming problem through mathematical modeling, optimal task allocation is realized by utilizing a heuristic search mechanism of the ant colony algorithm, and the efficiency and stability of a test system facing uncertain factors are remarkably improved.

The invention discloses a sequential fastening and testing integrated device and method during multi-point fastening part testing. The problems that in the prior art, the fastening sequence of multi-point fastening parts lacks an optimized verification mechanism, and fastening and testing are separated are solved. The device comprises an integrated test platform, a grouping type elastic positioning compression bar system and a cleaning and positive pressure leak detection system. Each pressing rod assembly adopts a double-spring segmented design and comprises a threaded pressing rod, a first spring, a first partition sleeve, a second spring, a second partition sleeve and a pressing rod head from top to bottom. By configuring rigidity parameters of the first springs and the second springs in different groups, programmable control over the fastening sequence is achieved, and multi-point fastening can be automatically completed according to the preset time sequence in the unified downward pressing action. According to the method, spring parameter configuration is adjusted in a targeted mode in the testing stage, the fastening effect is verified in combination with cleaning and air tightness testing, closed-loop control of fastening scheme design, execution, testing and optimization is formed, and finally the optimal fastening sequence is determined to guide production and assembly.

The invention discloses a current transformer electromagnetic compatibility test optimization method and device and a computer program product, and the method comprises the steps: carrying out a test in a pre-constructed lightning stroke simulation scene, and collecting simulation test data; the current offset degree is calculated based on the time sequence and the sliding window analysis technology, the dynamic response type of the mutual inductor is identified, and a peak report containing the immunity is generated; synchronously adjusting the initial average thickness and the nearest point distance of the metal shielding layer by using a full-factor design method, constructing a two-dimensional parameter matrix, and repeating the lightning stroke simulation test; and comparing each group of parameter test results with a shielding-layer-free reference result to calculate an interference suppression ratio, screening an optimal parameter combination by adopting a multi-objective optimization algorithm, and outputting a test report. According to the method, the coupling rule of shielding geometric layout and electromagnetic interference is quantified, the technical spanning from qualitative protection to quantitative optimization is realized, the test accuracy and the engineering applicability of an optimization scheme are improved, and the operation requirements of a smart grid on the current transformer are met.

The invention relates to the technical field of integrated circuit testing, in particular to a test optimization method for a three-dimensional stacked integrated circuit, which comprises the following steps of: constructing a theoretical total cost model, setting algorithm parameters, initializing a population, executing differential evolution global search and self-adaptive multi-strategy local search. According to the method, the theoretical total cost model for correcting the discarding cost deviation is constructed, and the hybrid enhanced differential evolution algorithm fusing dynamic reverse learning and adaptive multi-strategy local search is designed, so that the direct test cost is reduced, the potential discarding risk caused by manufacturing parameter fluctuation is effectively controlled, and the method is suitable for popularization and application. Therefore, the total cost of the comprehensive theory of the three-dimensional stacked integrated circuit is reduced, the global exploration and local development capabilities of the algorithm are balanced by using a hybrid enhancement strategy, and the search process is effectively prevented from falling into local optimum; and efficient and robust optimization of the three-dimensional integrated circuit test process under complex constraints is realized.

The invention discloses a test optimization method and device for a high-precision chip and a storage medium, and relates to the technical field of chip testing, and the method comprises the following steps: collecting the test time and the test passing condition of each test item in a CP test, and obtaining the basic test data of each test item; performing project correlation analysis according to the basic test data of each project to obtain related project data of each project; performing project necessity analysis based on the basic test data of each project and the related project data to obtain test project stable data; optimizing the test items of the CP test according to the test time of each test item and the test item stable data; the method and the device are used for solving the problem that the chip test time and the chip test cost cannot be reduced while the chip test time is shortened and the chip test cost cannot be reduced by analyzing test items on the premise of ensuring the chip quality when the CP test is optimized by the existing chip test technology.

The application provides a two-thirds wiring GIS protection transformation linkage test optimization method, and belongs to the technical field of power system relay protection device acceptance. The method first completes the test precondition confirmation, and then adopts a two-stage layered architecture to carry out the test: the indirect verification test without switch passes through the monitoring of the operation box action contact and the terminal conduction state, verifies the integrity of all protection circuits, and does not need the actual opening and closing of the circuit breaker; the direct verification test with switch is only carried out on the core necessary verification circuit, ensures that the two sets of trip / coil of the circuit breaker are operated once, and the new protection device is operated with the switch at least once; the test whole process follows the standardized process control, if unqualified, the corresponding fault is checked and then retested, if qualified, the test report is formed after the pressure plate is restored. The application greatly reduces the number of circuit breaker operations, shortens the test period, reduces the comprehensive cost, realizes the full coverage verification of the protection circuit, and improves the test efficiency, accuracy and safety.

The invention discloses a wheel lateral rigidity test optimization method and device, and belongs to the field of detection equipment. The device provided by the invention is composed of an axis positioning mechanism and a locking scale mechanism which are connected through a central shaft. The axis positioning mechanism utilizes a slide rail, a slide block and a positioning claw to cooperate with a slide rail mounting disc and a bottom plate to realize axis positioning of a to-be-measured wheel center hole, and realizes rapid and accurate positioning of the center of the mounting hole of the to-be-measured wheel. The locking scale mechanism ensures that excitation points are uniformly distributed through an angle dial and a length scale, and the connecting line of the two pairs of excitation points passes through the circle center of the center hole of the wheel to be measured. The device provided by the invention can be operated by a single hand, is simple in structure and convenient to operate, effectively solves the problem of measurement deviation caused by traditional visual point selection, and remarkably improves the accuracy and working efficiency of wheel lateral rigidity testing.

The present invention discloses a vehicle environmental calibration test method in a low-temperature scenario based on a plateau environment, comprising: performing basic calibration on a test vehicle using calibration equipment, modifying the exhaust system of the calibrated test vehicle, real-time monitoring of the air-fuel ratio and temperature parameters of the modified test vehicle, performing dynamic testing on the modified test vehicle in a plateau low-temperature environment and recording test data, judging whether the test data is startup failure data based on the air-fuel ratio and temperature parameters, and if so, performing parameter optimization on the vehicle calibration data to obtain low-temperature test optimization data. The present invention proposes to add a low-temperature plateau calibration verification link during the vehicle development stage, so that the product meets the reliability requirements of various altitude and temperature scenarios, thereby solving the cold start problem in low-temperature environments in plateau areas. All temperature scenarios from the lowest temperature to the highest temperature in high-altitude areas are covered, thereby ensuring the reliable performance of the product in all scenarios in plateau areas.

The 2.5D integrated circuit test path optimization method based on decomposition multi-objective evolutionary algorithm belongs to the field of integrated circuit test optimization, and aims to solve the problems that the traditional optimization method cannot efficiently solve the multi-objective optimization problem and the effect of balancing test time and test hardware overhead is not ideal because the gradient information of the problem is usually required. The method comprises the following steps: step one, initialization, generating an initial population for the test path configuration scheme of the 2.5D integrated circuit, and evaluating the initial population index according to the multi-objective evolutionary algorithm, and selecting the optimal fitness index as the ideal point of the initial population; step two, generating a new solution by using a crossover and mutation operator, and evaluating the new solution according to the multi-objective evolutionary algorithm and updating the ideal point; step three, environment selection, including updating the neighborhood solution and the elite solution set; step four, executing the iteration process of steps two and three for multiple times until the iteration is completed, and outputting the elite solution set.

The present invention discloses a reliability evaluation and optimization method for a parallel test ignition test system, which mainly relates to the field of aerospace pyrotechnics ignition test. The method comprises the following steps: S1, regarding the ignition test system of each test point as a multi-stage task system, performing parallel test redundancy analysis on the ignition test system, and performing module backup; S2, building a reliability model of the parallel test system using a dynamic Bayesian network based on the backup parameters of each module in each stage obtained by the analysis in step S1; S3, constructing a parallel test optimization problem for the ignition test system, establishing a mathematical model for the highest efficiency and the best reliability for the parallel test task, and then obtaining the optimal solution through a parallel test reliability optimization method based on an ant colony algorithm. The present invention can solve the problem of low efficiency of a single test point when the traditional method is used for large-scale test tasks, and complete large-scale test tasks more quickly and accurately.

The invention relates to the technical field of semiconductor manufacturing, and discloses a wafer test optimization system and method based on big data analysis, and the system comprises a data collection module which is used for obtaining the test data of a wafer test device in a current test period and the production environment data of a wafer in the current test period in real time, the wafer testing equipment is used for performing wafer testing on the wafer; the data analysis module is connected with the data acquisition module and is used for predicting defect modes of different positions of the wafer and defect probabilities of the defect modes of the different positions through a prediction model according to the test data and the production environment data; the dynamic optimization module is connected with the data analysis module and the wafer testing equipment and used for dynamically adjusting a testing scheme according to the defect mode and the defect probability and controlling the wafer testing equipment to conduct wafer testing on the wafer in the next testing period according to the adjusted testing scheme, and the testing scheme comprises testing parameters and testing paths.