60 results about "Test optimization" patented technology

The invention relates to an efficient test optimization method, system and device for chip test equipment, and the method comprises the steps: obtaining the equipment state data and test management information of the chip test equipment, carrying out the test unit division of the equipment state data based on the test management information, and obtaining the regional test information; acquiring real-time operation data of the chip test equipment, and performing matching analysis on the real-time operation data and the regional test information to obtain a real-time test task group; acquiring chip performance data acquired by the chip test equipment, performing load prediction on the regional test information to obtain a test load trend, and performing resource planning analysis with a real-time test task group to obtain an initial test scheme; performing exception identification on the chip performance data to obtain chip exception information; and performing global optimization on the initial test scheme according to the priority test sequence to obtain a global test strategy. According to the invention, fine management of different test tasks can be realized.

The invention discloses a test case generation method and device, equipment and a medium, and relates to the technical field of software test optimization. According to the scheme, the multiple initial test cases are obtained, and the test reports corresponding to the initial test cases are generated through the first preset test tool, so that the time for manually compiling the test cases is effectively shortened; when it is determined that a to-be-supplemented test case of which the corresponding code coverage rate index does not meet a preset requirement exists according to each test report, code uncovered information of the to-be-supplemented test case is determined, and test case optimization parameters are configured in combination with project requirements; and based on the parameter, calling a second preset test tool and a large language model to supplement the to-be-supplemented test case to obtain a complete test case. According to the scheme, the availability of the test case is improved through combination of multiple tools; workflows of test cases covering complex environments such as a function calling relation and a control flow structure are generated by utilizing the inference capability of a large language model, and the code coverage rate of the test cases is remarkably increased.

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 invention discloses a vehicle environment calibration test method based on a plateau environment in a low-temperature scene, and the method comprises the steps: carrying out the basic calibration of a test vehicle through calibration equipment, modifying the exhaust system of the calibrated test vehicle, monitoring the air-fuel ratio and temperature parameters of the modified test vehicle in real time, and carrying out the calibration of the test vehicle. And dynamically testing the modified test vehicle in the plateau low-temperature environment, recording test data, judging whether the test data is starting failure data or not based on the air-fuel ratio and the temperature parameter, and if so, performing parameter optimization on the vehicle calibration data to obtain low-temperature test optimization data. The low-temperature plateau calibration verification link is added in the whole vehicle development stage, so that the product meets the use reliability of scenes at all altitudes and all temperatures, and the cold start problem in the low-temperature environment in the plateau area is solved. And full-temperature scene coverage from the lowest temperature to the highest temperature in the high-altitude area is carried out, so that the reliability of the product in the full scene in the plateau area is ensured.

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 discloses an automatic test failure repairing method and device, and relates to the technical field of computer error diagnosis, and the method comprises the steps: obtaining failure test data when an automatic test task fails; preprocessing the failed test data to extract at least one test feature; and inputting the at least one test feature into a pre-trained structural causal model to output a reasoning result of the automatic test task, and repairing a test process of the automatic test task based on the reasoning result to carry out automatic test, thereby solving the problems of complex root cause of positioning test failure caused by changes of a software system and a test case and high test efficiency. The technical problems of time and labor consumption, increase of diagnosis cost, false alarm and missing alarm and lack of dynamic sensing capability are solved, and the purposes of quickly and accurately positioning the root cause of the test failure, automatically generating a repair scheme, reducing manual intervention, shortening the test period, improving the test efficiency, reducing the risk of false alarm and missing alarm and improving the test efficiency are achieved. And the technical effect of test optimization in a complex scene is supported.

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 relates to a test optimization method and system for a high-capacity 3D flash memory, and the method comprises the steps: carrying out the reliability testing of a random storage unit in a target flash memory chip for multiple times through grouping based on a reference temperature and a target temperature; the method comprises the following steps: respectively collecting test data of reliability test of a target chip at a reference temperature and a target temperature, and constructing a data sample set according to the test data; based on the data sample set and a few-sample training method, training a discriminator model used for judging whether the flash memory chip has a fault or not; and obtaining test data of the target flash memory chip under the reliability test at the target temperature, and inputting the test data into the discriminator model to obtain a test result of the target flash memory chip. According to the invention, the characteristic storage unit and the discriminator are selected to predict the test result at the target temperature to optimize the test process of the high-capacity 3D flash memory chip, a small amount of test data is analyzed to obtain the test result, the test time is greatly shortened, and the test efficiency is improved.

The utility model provides a liquid cooling heat dissipation testing device and system. The liquid cooling heat dissipation testing device comprises a liquid cooling machine, a liquid cooling pipeline, a plurality of flow regulating valves and a plurality of first flowmeters. The liquid cooling machine comprises a liquid cooling outlet and a liquid cooling return port, and the liquid cooling outlet is communicated with the liquid cooling return port through a liquid cooling pipeline; the liquid cooling pipeline comprises a plurality of first liquid cooling branches which are arranged in parallel, and a liquid cooling plate is connected in series in each first liquid cooling branch; each flow regulating valve is arranged in one first liquid cooling branch; and each first flow meter is arranged in one first liquid cooling branch. In an entity liquid cooling heat dissipation testing device, a liquid cooling machine and a plurality of flow regulating valves are used for simulating a required liquid cooling heat dissipation scheme, and a plurality of first flow meters are used for collecting the liquid cooling flow in a plurality of first liquid cooling branches arranged in parallel, so that the actual liquid supply flow of different branches of a liquid cooling pipeline is obtained; accurate data support is provided for test optimization of a liquid cooling heat dissipation scheme, and the accuracy of a test result is improved.

The invention discloses an intelligent software development auxiliary system, which belongs to the technical field of software development and comprises a code writing auxiliary module, a code quality control module, a project understanding navigation module, a test optimization module and a learning knowledge sharing module. According to the invention, manual input is reduced through the code writing auxiliary module, and a framework is quickly built; the project understanding navigation module assists developers in positioning key codes, and the early-stage preparation time is shortened. Through the code quality control module, error correction can be carried out instantly, styles are unified, and later maintenance cost is reduced. And case writing is simplified through the test optimization module, defects are early warned in advance, and the online quality is guaranteed. The learning knowledge sharing module helps green hands to integrate into a team, precipitate knowledge and improve the team technical level. Besides, by means of a deep learning model dynamic updating mechanism, innovative technology fusion and an optimization strategy of each module according to the environment, the auxiliary system closely follows the technical frontier, adapts to the change of software development requirements, and provides powerful support for development work.

The invention provides a rapid executable program generation method, and relates to the technical field of software development, and the method comprises the steps: creating an initial VR editor in a preset development engine based on a VR generation demand, and deploying and integrating related plug-ins to obtain the VR editor; encapsulating VR complex logic based on the writing script, and providing a preset template and a drag-and-drop component library for simplified editing to obtain a VR prefabrication result; integrating a VR editor into a preset development engine based on VR packaging and prefabricating results, and generating a Windows platform executable program to obtain an initial executable program; and performing test optimization on the initial executable program based on a preset test optimization scheme, thereby performing construction and publishing based on a test optimization result. By analyzing the VR generation demand, the related plug-ins are deployed and integrated, and the VR plug-ins are prefabricated and integrated in combination with VR complex logic to obtain the Windows executable program of the VR, so that the development cost can be greatly reduced, the manufacturing difficulty can be reduced, and the compiling efficiency of the executable program can be improved.

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 a low-voltage transformer area ground fault accurate positioning system and method, and belongs to the technical field of low-voltage transformer areas, and the system comprises a data collection module which is used for collecting the monitoring real-time data of a low-voltage transformer area; the data processing module is used for processing the monitoring real-time data of the low-voltage transformer area; the model training module is used for constructing a low-voltage transformer area grounding fault accurate positioning model; the test optimization module is used for carrying out test optimization on the low-voltage transformer area grounding fault accurate positioning model; and the fault positioning module is used for accurately positioning the grounding fault of the low-voltage transformer area and determining an accurate positioning result of the grounding fault of the low-voltage transformer area. According to the invention, the problem of poor management effect of the low-voltage transformer area caused by incapability of accurately identifying and positioning the grounding fault of the low-voltage transformer area in the prior art is solved. According to the invention, the grounding fault of the low-voltage transformer area can be accurately identified and positioned, the grounding fault of the low-voltage transformer area can be timely found and maintained and managed, and the management effect of the low-voltage transformer area can be improved.

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.