385 results about "Analytical Testing" patented technology

The invention relates to the technical field of cable asset management and fault prediction, and discloses a cable fault positioning method based on deep learning clustering analysis test waveform characteristics, and the method comprises the steps: collecting waveform and environment data in a cable operation period, and constructing a historical feature library comprising waveform, environment and position features; a self-adaptive detection model is adopted, and parameters are dynamically adjusted to adapt to different working conditions; multi-dimensional feature fusion and matching analysis are combined; a fault point distance is calculated through a signal propagation model and a time difference positioning algorithm, precise positioning is realized by fusing environment compensation and multi-point cross validation, and a three-dimensional geographic coordinate is generated by combining a laying path; and after multiple verifications, a structured report containing a fault type, a risk level, a prediction position, confidence and operation and maintenance suggestions is generated. According to the system, intelligent monitoring, fault risk prediction, asset optimization management and operation and maintenance decision support of a cable operation state are realized, and scientificity and economy of cable management in a complex environment are improved.

The invention relates to the technical field of storage batteries, in particular to a storage battery monitoring, detection, treatment and evaluation integrated system and a storage battery management method, and the system comprises a plurality of accompanying modules, a collection power distribution control module, a storage battery management capacity checking host and a remote platform; the internal resistance analysis test of the system is based on multi-frequency-point alternating current excitation (0.5 Hz-7. 5kHz), a complex impedance spectrum of not less than 20 frequency points can be constructed, and the internal polarization characteristics of the battery are analyzed; the system adopts a feed network type discharge capacity checking, so that discharge electric energy is fed back to a power grid, and the capacity detection precision is improved to 98%; according to the system, EIS data and an LSTM neural network are fused, and a battery state of health (SOH) prediction model is established; the system is based on a DSP digital power supply technology, and can realize 50A active equalization topology.

The invention relates to the technical field of data storage, and discloses a solid state disk total write-in data volume testing method, which comprises the following steps of: initializing a testing environment and self-adaptive parameter configuration of a solid state disk; creating a plurality of parallel data acquisition threads, acquiring test data through the data acquisition threads, and storing the acquired test data into a database; establishing a preset health degree evaluation model, analyzing the collected test data in real time according to a preset health degree index system, dynamically adjusting a test load based on a dynamic acceleration stress model and according to the real-time state of the solid state disk, executing a corresponding test operation according to an adjustment result, and recording a test result; and analyzing the test result, and automatically generating a test report according to the analysis result. According to the method, the dynamic acceleration stress model is introduced, so that the test load is dynamically adjusted according to the real-time state of the SSD, and the test efficiency and accuracy are improved.

The invention relates to the technical field of network security, and discloses a multi-agent cooperative RESTful API vulnerability test method. Constructing a parameter structured representation by analyzing an API interface specification, generating a test value conforming to service semantics by using a large language model, and establishing a semantic request baseline representing normal service logic; constructing a multi-agent collaborative architecture including vulnerability reasoning, case generation, test execution, test analysis and test management; all the agents are coordinated to carry out iterative vulnerability testing through a signal mechanism and a state transition table, and API service analysis, test strategy customization, use case directional variation and execution, result study and judgment and strategy optimization are achieved; and finally generating a structured vulnerability report. According to the method, the problems of semantic blind areas, shallow analysis layers, insufficient adaptive capacity and the like are solved, security risks such as business logic vulnerabilities and sensitive data leakage in the RESTful API can be deeply detected, and the accuracy and coverage rate of vulnerability detection are remarkably improved.

The invention relates to the technical field of large language models, provides an automatic flight simulator interface code generation method, system and device based on a large language model and a storage medium, and solves the problems of low generation efficiency, poor accuracy and poor system adaptability of flight target interface codes. The method comprises the steps of obtaining interface data of multiple external devices of a flight target, and converting the interface data into structured input data after noise filtering and key information extraction; deeply analyzing the data by using a deep learning and semantic understanding algorithm, extracting key semantic information and generating an interface code template; instantiating the template content in combination with the example data and the interaction rule to generate a target code; generating a multi-scene test case based on a test case algorithm, and verifying code correctness, stability and performance; testing and performance results are comprehensively analyzed, model parameters and training data are dynamically adjusted, and closed-loop automatic code generation is achieved. According to the method, the generation efficiency, accuracy and system adaptability of the flight target interface code are improved.

The invention provides a rock mineral analysis test management method and system, and the method comprises the steps: collecting rock mineral sample multi-modal data, and constructing a digital twinborn model; constructing a geological knowledge map, and injecting and fusing the two knowledge to generate a virtual test data set; performing self-supervision pre-training by using the data set to obtain a self-adaptive mineral phase recognition model; deploying the model to a block chain-Internet of Things double-chain traceability system to obtain an identification result and an optimization instruction; and executing a sample preparation process and removing unqualified samples. According to the method, diffusion steps are adjusted through adaptive noise scheduling and a space-time alignment algorithm, data are integrated, a high-reality-sense virtual test data set is generated, and a self-supervised pre-training and knowledge distillation technology is combined, so that the model has space-time feature extraction and dynamic optimization capabilities; and finally, full-process closed-loop control is realized through a double-chain traceability system and a modular robot, and the recognition precision of a complex scene is improved.

The invention provides an automatic management interaction method, system and device of a whole vehicle software version and a medium, and relates to the technical field of vehicle software engineering.According to the method, functions of version monitoring, change analysis, test management and version management are provided through an integrated main interface, and a user can check the software version state and tasks to be done in real time; and performing multi-dimensional version comparison and risk assessment to generate a detailed change and risk report. In addition, the method supports configuration of a test strategy, execution of an automatic test and generation of a test report and a defect positioning list, and the test efficiency and accuracy are effectively improved. And in the aspect of version management, the whole process operation from creation to release is realized, the timeline and historical report of the whole life cycle can be displayed, and the transparency and traceability of version control are ensured. On the whole, the method effectively improves the efficiency and reliability of whole vehicle software version management, simplifies the operation process, and enables the version control to be more efficient, more accurate and easier to manage.

The invention relates to the technical field of wireless network testing, and discloses a wireless router complete machine one-stop testing method and system and electronic device.The wireless router complete machine one-stop testing method comprises the steps that a typical network application characteristic flow mode library is constructed, and different flow modes are dynamically combined through the Markov decision process; creating a novel attack mode by using the generative adversarial network; constructing a multi-agent cooperative attack system; dynamically adjusting the test intensity according to the real-time response of the router; constructing a multi-dimensional evaluation index system and analyzing a test result; according to the invention, by combining artificial intelligence and network security technologies, the performance and security protection capability of the wireless router in a complex and changeable network environment and attack scene are comprehensively tested, potential stability problems and security holes are found in advance, and the product quality and the user experience are effectively improved.

The invention relates to the technical field of network security, in particular to an adaptive penetration test method and system based on reinforcement learning, and the method comprises the steps: constructing a state space model, defining an action space, designing a reward function, optimizing a strategy model, and analyzing a test result. According to the method, a reinforcement learning mechanism is combined with target environment feedback, so that multi-step attack path planning and adaptive strategy adjustment are realized, and the intelligence and coverage depth of penetration testing are remarkably improved. And meanwhile, through backtracking analysis of the state transition sequence, the potential threat path is comprehensively identified, and accurate guidance is provided for security protection.

The invention relates to the technical field of memory test, and provides a test system for a parallel interface NOR FLASH memory, which comprises the following steps of: acquiring verification information of test data of a test data block in a storage area and verification operation in a test process of the NOR FLASH memory, and judging whether the test data block has an error or not; dividing the test data blocks with errors, and determining secondary to-be-analyzed test data blocks; the method comprises the following steps: marking target test data, identifying high-frequency error test data, dividing a secondary to-be-analyzed test data block needing to be adjusted into a tertiary to-be-analyzed test data block, and repeatedly judging and dividing until the data block cannot be continuously divided or the judgment result of the data block is that the data block is not divided, thereby realizing the setting of a block verification mode of a full-step method. And evaluating the durability of the NOR FLASH memory of the parallel interface by using a one-step method. According to the invention, a block verification mode can be adaptively set, and the accuracy of a durability test result is improved.

The invention discloses a metallogenic prediction method and device based on fluid parameters and fluid field modeling, a medium and a product, and relates to the field of metallogenic prediction. The method comprises the following steps: firstly, carrying out lithofacies research on a fluid inclusion sample in a target area to determine a metallogenic stage; analyzing and testing the fluid inclusion samples at different mineralization stages to obtain a plurality of fluid parameters; exploratory data analysis is conducted on the multiple fluid parameters, and key fluid parameters closely related to the content of the main metallogenic elements are screened out; modeling the numerical relationship between the key fluid parameters and the main metallogenic elements by adopting a machine learning or deep learning algorithm, and determining an optimal numerical model; processing the key fluid parameters by adopting different spatial interpolation algorithms, and establishing a three-dimensional fluid field model; according to the three-dimensional fluid field model and the optimal numerical model, three-dimensional metallogenic prediction is carried out in combination with the metallogenic geological elements, and a prospecting target area is determined; the fluid parameters are introduced as predictive variables, so that the precision of metallogenic prediction is improved.

The invention relates to a field effect transistor channel mobility determination method and device and computer equipment. The method comprises the following steps: acquiring a transfer characteristic curve of a target field effect transistor; determining a target effective electric field intensity interval corresponding to the grid voltage of the target field effect transistor according to the transfer characteristic curve of the target field effect transistor; determining the transistor body mobility of the target field effect transistor according to the body mobility model; based on the target effective electric field intensity interval, the coulomb scattering mobility, the phonon scattering mobility and the surface roughness scattering mobility of the target field effect transistor are determined according to a target coulomb scattering mobility model, a target phonon scattering mobility model and a target surface roughness scattering mobility model; and determining the channel mobility of the target field effect transistor based on a channel mobility model. According to the scheme, the performance of the device can be quickly and effectively evaluated, complex analysis testing is avoided, and the development speed of the device process is increased.

The application provides a MEMS differential thermal analysis sensor and a DTA / DSC testing method, the sensor comprising a detection thermocouple, a reference thermocouple, an ambient resistance and a shielding ring, wherein the detection thermocouple and the reference thermocouple each comprise a single crystal silicon substrate, a heat insulation cavity, a plurality of single crystal silicon thermocouple pairs and a supporting film, the heat insulation cavity is located in the single crystal silicon substrate, the plurality of single crystal silicon thermocouple pairs are connected in series and are supported by the supporting film to be suspended above the heat insulation cavity to achieve thermal isolation, and the single crystal silicon thermocouple pair comprises an N-type single crystal silicon thermocouple and a P-type single crystal silicon thermocouple connected in series, the temperature and power sensitivity of the sensor are significantly improved, reach 28 mV / K and 100 V / W, and the noise equivalent temperature difference and the noise equivalent power reach 0.5 mK or 0.2 muW. Based on the output signal of the sensor, differential thermal analysis testing and differential scanning calorimetry testing on physical or chemical processes of material heat absorption and release can be realized, the sample consumption is small, and the testing precision is high.

The invention discloses a high-end memory chip asynchronous test system based on a distributed architecture, which relates to the technical field of chip testing, and comprises a state modeling module, a master control end initialization and test end access, memory chip test task pool construction, test end state analysis in combination with historical test load and historical fault information, and memory chip asynchronous test. Generating an optimized scheduling strategy; the scheduling module is used for performing task division and asynchronous scheduling on the memory chip test task pool by adopting an intelligent scheduling algorithm based on an optimized scheduling strategy to generate an asynchronous data flow queue; according to the issuing module, the test end receives the asynchronous data flow queue in an asynchronous mode to carry out protocol unpacking and task mapping, and a memory chip function test task is obtained and issued; according to the method, the test throughput rate and the resource utilization rate are improved by asynchronously sequencing and scheduling tasks, the task scheduling delay is reduced, the load of each test end is balanced, and meanwhile, the horizontal expansibility and the fault-tolerant capability are enhanced.

Cloud computing architecture is described for implementing test modules in a communication-controlled cloud environment with access to private data. The test modules perform synchronous tests on the private data and export test results to an analytic environment subject to data export policies. An analytic application is used to asynchronously analyze the test results in the analytic environment. The cloud computing architecture alternatively or additionally includes an interface for deploying investigation-bound cloud environments in restricted subnets. A collection of software is instantiated in the investigation-bound cloud environment, and the investigation-bound cloud environment may be accessed with remote access credentials using a remote access protocol for testing the collection of software. Information about the investigation-bound cloud environment displayed in the analytic application, and the analytic application and the restricted subnet are forcibly deleted when the investigation is complete.

The invention discloses a semiconductor chip test information automatic analysis system and method, and relates to the technical field of information analysis, and the method comprises the steps: calculating a parameter reference value according to a standardized test data set, carrying out the multi-dimensional discrimination feature extraction based on the parameter reference value, generating a test feature vector, and carrying out the analysis of the test feature vector; injecting the test feature vectors into the parameter influence network model, analyzing a dynamic interaction relationship among test parameters through an anomaly propagation simulation algorithm, performing root cause sorting and influence path tracking based on the dynamic interaction relationship, generating an anomaly analysis report, calling an intelligent diagnosis mechanism according to the anomaly analysis report, and performing fault diagnosis on the test parameters according to the intelligent diagnosis mechanism. Generating a structured conclusion through historical case library matching, and synchronously activating a visualization function to perform interactive presentation on the structured conclusion; according to the method, comprehensive representation of multi-dimensional discrimination information is realized through multi-dimensional feature extraction, the defect that an existing method is limited to single-parameter statistics is overcome, and the test feature vector expression capability is improved.

The invention discloses a water quality measuring device and method, and belongs to the technical field of analytical testing, the water quality measuring device comprises a light source, a first signal receiver and a buffer pool, the buffer pool is provided with a liquid inlet and a liquid outlet, the liquid inlet of the buffer pool is used for continuously inputting a to-be-tested sample, and the liquid outlet is used for continuously outputting the to-be-tested sample; the buffer pool is arranged in the buffer pool, water flow at a liquid outlet of the buffer pool forms a stable liquid column, the light source is arranged on the first side of the liquid column, the first signal receiver is arranged on the second side of the liquid column, light emitted by the light source penetrates through the liquid column and is received by the first signal receiver, and the first signal receiver is used for measuring the light intensity of the received light. Parameters to be tested in a water sample are tested in a non-contact mode, light emitted by the light source penetrates through the liquid column, and the change of a signal is detected through the first signal receiver and can be converted into the content / value of the parameters to be tested in the water sample, so that long-term reliable, accurate and stable water quality testing in various scenes can be met; the key technical problem urgently needing to be broken through in the current water quality monitoring field is solved.

The invention discloses a high-end memory chip asynchronous test system based on a distributed architecture, which relates to the technical field of chip testing, and comprises a state modeling module, a master control end initialization and test end access, memory chip test task pool construction, test end state analysis in combination with historical test load and historical fault information, and memory chip asynchronous test. Generating an optimized scheduling strategy; the scheduling module is used for performing task division and asynchronous scheduling on the memory chip test task pool by adopting an intelligent scheduling algorithm based on an optimized scheduling strategy to generate an asynchronous data flow queue; according to the issuing module, the test end receives the asynchronous data flow queue in an asynchronous mode to carry out protocol unpacking and task mapping, and a memory chip function test task is obtained and issued; according to the method, the test throughput rate and the resource utilization rate are improved by asynchronously sequencing and scheduling tasks, the task scheduling delay is reduced, the load of each test end is balanced, and meanwhile, the horizontal expansibility and the fault-tolerant capability are enhanced.

The present application relates to a kind of method and kit for detecting methylation cysteine total amount, belong to the field of biotechnology and analytical test.Utilize nucleic acid aptamer with high response to free Hcy, with moderate corresponding state Hcy to construct evanescent wave optical fiber sensor.Complementary strand and tHcy of fluorescently labeled are combined with the nucleic acid aptamer fixed on optical fiber with competition.Fluorescence signal drop value is positively correlated with tHcy concentration in serum.According to the percentage of fluorescence reduction, the tHcy concentration in serum is calculated.The present application detects tHcy only needs 1 microliter serum, after diluting 1000 times, detection is carried out, and the detection result is consistent with commercial enzyme cycle method.Compared with enzyme cycle method, the present application has the advantages of low price, optical fiber can be reused more than 30 times, detection speed is fast, fastest 5 minutes, does not need enzyme, equipment miniaturization, simple operation, etc., has excellent clinical application value.

The invention discloses a CAN network fault-tolerant automatic test system and method for an electric steering system, and relates to the technical field of CAN network testing, and the system comprises an upper computer module and a test tool. The test tool comprises an MCU and a switch array. The switch array comprises a plurality of controlled chip switches and relay switches. The test tool receives a test sequence message of the upper computer through the CAN bus and controls the switch array to act so as to inject a fault into the EPS or recover communication; and the upper computer module also receives a reply message of the EPS and generates a fault-tolerant test result. A CAN fault-tolerant test tool is formed by a switch array composed of a plurality of controlled chip switches and relay switches, a test sequence message of an upper computer test script is received to carry out various fault tests, whether a test result is qualified or not is analyzed according to a feedback EPS message, multiple fault-tolerant ability tests including Busoff fast and slow recovery time can be automatically carried out, and the fault-tolerant ability test efficiency is improved. And the development and test cost is reduced.

The application relates to the technical field of substation operation and maintenance, and is a substation secondary test equipment on-site operation and maintenance system and method, which comprises the following steps: a control platform outputs an operation and maintenance command to secondary online detection equipment in a substation in combination with detection items, and receives and analyzes test result data; a cloud server transmits and stores data between the control platform and the secondary online detection equipment; the secondary online detection equipment performs online detection on a measured device of the substation in combination with the operation and maintenance command; a transmission network is connected with the secondary online detection equipment and the measured device respectively, and transmits related data information; and the measured device transmits detection information and autonomous digital message information back to the secondary online detection equipment in combination with information transmitted by the secondary online detection equipment. The application realizes remote full-automatic test on secondary equipment, greatly reduces labor cost, realizes intelligent, digital and remote operation of substation secondary equipment detection, and realizes 24-hour intelligent operation and maintenance of electric power.

A method of non-linear acoustic non-destructive testing of a testpiece (3) comprising (i) determining a resonance frequency of a testpiece (3) by applying at least one excitation vibration to the testpiece (3) and analysing a vibrational response of the testpiece (3) to the at least one excitation vibration, (ii) applying at least one excitation vibration to the testpiece (3) at the determined resonance frequency and / or over a range of frequencies that includes the determined resonance frequency, and (iii) determining if the testpiece (3) has one or more flaws by analysing a vibrational response of the testpiece, to the at least one excitation vibration in step (ii), for non-linear behaviour. An apparatus (1) for non-linear acoustic non-destructive testing of a testpiece (3) according to the method.

The utility model relates to an optical storage inverter power supply automatic test system, which is used for testing the performance of an optical storage inverter power supply, and comprises an upper computer, ATE test equipment and a control processing assembly, the ATE test equipment comprises an oscilloscope, a PV source, a bidirectional DC source, an AC load, a power analyzer and a universal meter; each test interface of the ATE test equipment is correspondingly connected with an input / output port of the optical storage inverter power supply, the control processing assembly is connected to the upper computer and the ATE test equipment, and parameter adjustment and input / output control of the optical storage inverter power supply are realized through the upper computer. Meanwhile, the working state and parameter setting of each test instrument in the ATE test equipment are controlled, and voltage and current data collected by each test instrument in the ATE test equipment are received and analyzed. According to the invention, the power supply of the optical storage inverter is rapidly measured automatically, manual intervention during automatic testing is avoided, the testing efficiency is improved, and the measurement result is accurate.

The invention belongs to the technical field of new energy, and discloses a new energy station frequency modulation system dynamic performance and continuous step response test method, which comprises the following specific steps: S1, connection and calibration of a test system; s2, testing signal parameter configuration; s3, executing a dynamic performance test; s4, a continuous step response special test is carried out; s5, data and video conjoint analysis; s6, quantitatively evaluating a test result; s7, performing off-line reproduction of the fault scene; s8, maintaining and verifying the testing device; and S9, generating and filing a test report. According to the invention, through high-precision calibration and multi-mode signal configuration, the accuracy and reliability of test data are ensured; a dual-channel synchronous acquisition and dynamic compensation algorithm is adopted, the response characteristics of the system are accurately captured, and the measurement precision in a small frequency deviation scene is improved; and in combination with video conjoint analysis and quantitative evaluation, the adjustment performance and the anti-interference capability are deeply revealed, and a complete dynamic performance evaluation closed loop is formed.

The invention discloses a two-cavity type gas analyzing and testing cabin suitable for an MEMS sensor array, and relates to the technical field of smell distinguishing instruments, the two-cavity type gas analyzing and testing cabin comprises a detection cabin, a buffer cabin, a butterfly valve and a related gas entraining pipeline; a sensor is detachably connected in the detection cabin, a buffer cabin is arranged on one side of the detection cabin, a butterfly valve is arranged between the buffer cabin and the detection cabin, the butterfly valve is electrically controlled, and a negative pressure air entraining pipeline is arranged at the bottom of the buffer cabin and connected to a vacuum pump. The buffer cabin and the detection cabin are independently and sectionally heated, so that the sensor is ensured to be in an optimal working temperature state.

The invention provides an automatic testing method and device and a storage medium. According to the embodiment of the invention, the case log generated by the test case is acquired and analyzed in real time in the process of executing the test task, the type of the exception occurring in the test environment can be identified in time, and the exception can be repaired based on the preset repair strategy and the generated exception context information containing the structured data. And dynamically executing a repair operation aiming at the abnormal type so as to recover the execution process of the influenced test case after successful repair. According to the embodiment of the invention, continuous monitoring and accurate diagnosis of the test environment are realized, and the test environment is dynamically repaired during the operation of the test task, so that test interruption caused by the abnormality of the test environment is reduced, and the continuity of the test process and the reliability of the test result are enhanced.

The invention discloses a preparation method of an iron ore concentrate powder scanning electron microscope sample, and belongs to the field of material analysis and testing. The preparation method comprises the following steps: (1) adding iron ore concentrate powder to be detected into absolute ethyl alcohol, and fully and uniformly shaking to obtain a sample solution; (2) adding a dispersing agent into the sample solution, and uniformly oscillating by using an ultrasonic method to obtain a solution after ultrasonic oscillation; and (3) pouring the solution subjected to ultrasonic oscillation into a sprayer, uniformly spraying the solution to the surface of a conductive adhesive tape fixed on an objective table of a scanning electron microscope through the sprayer, and naturally drying to obtain the iron ore concentrate powder scanning electron microscope sample. The method is simple in sample preparation process, uniform in iron ore concentrate particle dispersion and easy to operate, the problem of iron ore concentrate powder agglomeration is solved, meanwhile, a scanning electron microscope sample chamber is not polluted, and the observation result is real and reliable.

The utility model relates to the technical field of gold ore analysis and test pretreatment, and discloses solid sample and reagent rapid mixing equipment which comprises a tank body, a first threaded mounting seat is arranged at the top of the tank body, a tank cover is in threaded connection in the first threaded mounting seat, a fixing pipe is fixedly connected in the tank cover, and a fixing sleeve is fixedly connected to the bottom of the fixing pipe. A fixed sleeve is arranged in the tank body, a sliding sleeve is connected to the outer wall of the fixed sleeve in a sliding manner, a lifting pipe is fixedly connected to the bottom of the sliding sleeve, and a second threaded mounting seat is arranged at the bottom of the lifting pipe. The solid sample is placed in the circulating flow channel in the tank body, so that the dissolution rate between the solid sample and the solvent is increased through rapid flowing between the solvent and the solid sample, meanwhile, uniform dissolution of the solid sample in the solvent is achieved through circulating flowing of the solvent, and the practicability of the equipment is improved.

The invention discloses a multi-interval protection device test system and method based on a data parallel mechanism, and the method comprises the steps: testing a multi-interval protection device, collecting test information, including digital quantity and analog quantity, generated in a test process, and processing the digital quantity and the analog quantity through different processing mechanisms; designing a multi-data parallel processing mechanism to transmit test information; analyzing interaction information between the test system and the relay protection device, and classifying the interaction information; determining the test tasks and the priorities of the test tasks based on the test information according to the types of the interaction information and the implementation functions of the test tasks; and according to the priorities of the test tasks, constructing a scheduling algorithm for dynamically adjusting task allocation and load balance. According to the invention, the problems of data loss, interference, uneven resource allocation and the like when a plurality of protection devices are simultaneously accessed to the test system can be solved, and the test efficiency and the reliability of the system are improved.

The application discloses a passenger car four-channel chassis component durability test device and relates to the field of durability tests, which comprises a test frame main body, a tractor one installed at the bottom of the test frame main body, a tractor two installed at the left side of the test frame main body, a tractor three installed at the right side of the test frame main body and a control module installed on the front of the test frame main body, wherein the tractor one, the tractor two and the tractor three are used for fixing the tested components and conducting horizontal, vertical and torsional fatigue tests; a prediction model is constructed, the test state of a future period is predicted and obtained based on the test data of the current test project, the mapping relationship between the initial period damage state of the test component and the future period fission and deformation state is analyzed, and then the long-term test performance of the tested object can be quickly obtained through short-term actual tests.