2731 results about "Test platform" patented technology

An example operation may include one or more of executing tests on a software application via a test environment of a test platform and logging results of the tests in a log file, identifying a new feature to be added to the software application based on execution of a machine learning model on logged results of the tests stored in the log file, generating source code for the new feature to be added to the software application based on execution of a generative artificial intelligence (GenAI) model on the new feature and a repository of source code, and displaying the generated source code via a user interface of the software application.

The invention provides a servo hydraulic system optimization control method and system for a press machine test platform, and relates to the technical field of press machines, and the method comprises the steps: building a state space expression and building a mathematical model of a servo hydraulic system based on dynamic characteristics by deducing mathematical expressions of all components of the system; building a predictive control algorithm based on the mathematical model, solving a quadratic programming problem by adopting a rolling optimization strategy through building a state space predictive model and determining a multi-objective optimization function to obtain an optimal control sequence, and taking a first element of the optimal control sequence as control input at the current moment; feedforward compensation and pressure feedback compensation are introduced, the feedforward compensation constructs a compensation model based on an inverse system of a press transfer function and pre-corrects a control signal, and the pressure feedback compensation designs a digital filter based on a pressure error, fuses a feedforward compensation signal with a pressure feedback compensation signal and superposes the fused signal with the control signal; and obtaining a final control signal.

The invention provides a frequency converter dynamic fault diagnosis method and system based on a multi-brand load test platform. According to the method, multiple real-time operation parameter sets are acquired, the amplitude attenuation threshold and the frequency fluctuation interval of a voltage waveform fragment are dynamically adjusted according to a load mode configuration file, the dynamic voltage reference parameter corresponding to the current load mode is generated, and then the actual waveform and an expected current phase curve are compared frame by frame; the method comprises the following steps: firstly, calculating to obtain a phase offset, then constructing a multi-dimensional operation characteristic spectrum, then carrying out time sequence cross validation on a sudden change time node of a power factor jump trajectory and an abnormal waveform position in a harmonic distortion incidence matrix, outputting an abnormal mode code, and finally, matching a load adaptation grade constraint condition to generate a diagnosis report; according to the technical scheme provided by the invention, the fault diagnosis precision and the cross-brand system adaptation capability in a complex load scene are remarkably improved, and the problem of misjudgment of a single brand threshold rule in a multi-device scene is effectively solved.

The invention discloses an Internet of Things test platform adaptation method, system and device based on post quantum cryptography. The method comprises the following steps: constructing a quantum threat perception model; establishing a multi-dimensional adaptive decision matrix, and generating a candidate post-quantum cryptography algorithm set; dynamic injection of a cryptographic protocol is executed, and lossless replacement of a communication layer encryption suite is achieved; deploying a runtime performance monitoring engine, and collecting encryption and decryption delay, memory occupancy rate and electromagnetic radiation characteristic data in real time; and constructing an algorithm switching decision tree based on reinforcement learning, and when a quantum attack feature or an equipment performance threshold is detected to break through, triggering cryptographic algorithm dynamic migration. A quantum threat perception driven Internet of Things security adaptation system is constructed, and by introducing a dynamic password switching mechanism, a hardware acceleration optimization scheme and a trusted execution environment, the security upgrading problem of traditional Internet of Things equipment in the post-quantum era is solved. According to the invention, the execution efficiency of the PQC algorithm of the resource-constrained equipment can be improved, and the key updating delay is reduced.

The invention relates to the technical field of semiconductor device testing, in particular to a SiC MOSFET power cycle testing method which comprises the following steps: S1, building a composite environment testing platform, configuring dynamic testing parameters, automatically calculating a physical boundary and collecting sensor data in real time; s2, establishing a finite element simulation model based on the physical boundary and sensor data, and outputting optimized dynamic test parameters and a simulated stress distribution diagram; s3, synchronously applying composite stress according to the dynamic test parameters and the stress distribution diagram, and collecting multi-dimensional test data in real time; when the system is used, through dynamic boundary calculation and real-time data acquisition, the intelligent degree and reliability of the test are improved, the test period is shortened, the failure prediction accuracy is improved, the system is suitable for reliability evaluation of SiC MOSFET devices in the fields of new energy, aerospace and the like, a large number of physical tests are avoided through virtual simulation, and the reliability of the SiC MOSFET devices is improved. And reduction of device loss and resource waste is facilitated.

The invention discloses an interaction test method for gait simulation of a humanoid robot, which is applied to a test platform. Comprising the following steps: controlling a current gait simulation model corresponding to a virtual robot to perform a gait simulation test in a virtual test environment in a current preset time period; the virtual test data is sent to the physical robot; controlling the physical robot to execute corresponding gait operation according to the virtual test data in the actual test environment, and sending the actual test data to the virtual robot; updating the current gait simulation model based on the virtual test data and the real test data; and continuing to perform the gait simulation test based on the updated gait simulation model, and ending the updating operation until the gait simulation test is ended, so as to generate a complete gait scheme. Therefore, by constructing a closed-loop interaction mechanism between the virtual robot and the physical robot, dynamic adjustment of the gait simulation model is achieved, the gait of the physical robot is restored, and the stability and precision of the gait of the physical robot are improved.

The invention discloses an artificial intelligence robot path planning method and system, and the method comprises the steps: 1, carrying out the comprehensive perception of an environment geometric structure, object semantics and dynamic obstacles, eliminating scene differences, and further constructing the topological graph representation of an environment; 2, pre-training a path planning model, designing a scene context encoder, encoding a scene specific rule into a low-dimensional vector, and outputting a scene context code and updated planning model parameters to provide a planning capability adapted to a new scene for the step 3; 3, dynamically adjusting a track according to real-time sensor data by adopting a hierarchical decision-making architecture; step 2, recording success / failure path segments in the new scene, regularly updating a local planning module, regularly feeding back empirical data in the new scene to the step 2, and triggering a conservative obstacle avoidance mode when the confidence coefficient is lower than a threshold value; and 4, constructing a quantitative evaluation system, building an automatic test platform, simulating diversified scenes and dynamic interference, and automatically generating a test case.

The embodiment of the invention provides a security authentication method, device and system for a test platform, and a storage medium, and relates to the technical field of network security. The method comprises the following steps: performing fingerprint acquisition on virtual and real equipment to generate a unique identifier, dynamically slicing based on a software defined network to form an isolated test environment, and injecting a zero-trust access strategy associated with the fingerprint; and based on the zero-trust access policy and the device fingerprint, allocating a minimum permission through an attribute-based access control model, continuously evaluating device behaviors to calculate a dynamic trust score, and adaptively updating the permission according to the trust score. By constructing a full-process security certification system and through multi-dimensional mechanism cooperation, dynamic risk perception and timely strategy adjustment, fine-grained control of virtual and real equipment access in an industrial control scene is realized, the dynamic adaptability and risk resistance of a test platform in a complex network environment are improved, and the test efficiency is improved. Equipment access safety, authority distribution minimization and behavior monitoring continuity are ensured, and the safety risk of the industrial control system is reduced.

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

The invention discloses an intelligent digital rail transit simulation test system based on a digital twinborn technology, which comprises a digital track simulation platform, a digital track internal test platform and a central digital track server, and a visual digital track 3D scene model is constructed by joint design based on the rubber wheel train dynamic model data and the digital track urban construction coordinate graph. The digital track internal test platform comprises a test navigation control unit, and a digital track mathematical model, an electronic map, magnetic coding data and environment perception simulation information are preset in the test navigation control unit. The train equipment state can be monitored, the train equipment state transition can be controlled in real time, the artificial intelligence machine learning technology is introduced, and the test effectiveness is improved; and a real vehicle and a simulation machine can be accessed at the same time to be converted into a test platform before internal product release. The invention further discloses an intelligent digital rail transit simulation test method based on the digital twinning technology.

The invention relates to the technical field of SOC modular unit testing, and discloses an AI SOC modular unit testing method and device of a set top box, and the method can automatically construct a testing platform simulating a real use environment, generate testing cases covering various scenes, achieve parallel testing and real-time interference compensation, and improve the testing efficiency. And multi-dimensional analysis and cross-batch alignment can be carried out on test data. Meanwhile, the method also has an adaptive optimization capability, and can dynamically adjust a test strategy according to a test result, so as to continuously improve the test efficiency and accuracy.

The invention provides a method for testing the stability of an electronic product, and the method comprises the steps: obtaining the propagation characteristic data of a transient current in a grounding network, building a multi-point grounding network model in combination with the potential distribution data of each node, inputting the potential of the nodes and the transient current data, and predicting the fluctuation trend of the ground potential through the multi-point grounding network model; according to the predicted ground potential fluctuation trend, extracting a coupling path of an interference signal in the grounding network when common-mode interference exists, and determining a main node and a propagation direction of interference signal propagation to obtain a sensitive circuit; calculating node potential distribution data of the grounding network after node layout, judging whether the potential difference between key nodes is within a preset range or not, and if the potential difference exceeds the preset range, refining network division, increasing equipotential connection or locally reducing grounding resistance; and determining a matching design scheme of the grounding network and the sensitive circuit according to the anti-interference capability, building a test platform, and testing stability data of the grounding system in different electromagnetic environments.

The invention relates to the field of power distribution network cable main insulation fault detection and management, and discloses a power distribution network cable main insulation fault detection and management integrated test platform construction method comprising the following steps: a) data acquisition: installing a plurality of sensors including a partial discharge sensor, a current and voltage sensor, a temperature sensor and a vibration sensor; acquiring real-time operation data of the power distribution network cable; b) data transmission: transmitting the acquired cable monitoring data to a data processing system in a wired or wireless communication mode; and c) data preprocessing: denoising, missing value interpolation, standardization or normalization processing is carried out on the transmitted original data so as to improve the quality of the data. The real-time operation state of the power distribution network cable is monitored through various sensors, and various advanced data processing methods are combined, so that the accuracy of fault detection is effectively improved, and identification deviation caused by data noise or sensor errors in a traditional fault detection method is avoided.

The invention belongs to the technical field of fuel cells, and particularly relates to a fuel cell centrifugal air compressor irreversible loss prediction method and system, and the method comprises the steps: collecting performance data based on a fuel cell centrifugal air compressor comprehensive performance test platform, and building and verifying a multi-physics coupling CFD simulation model; defining an irreversible loss type and related structure parameters, constructing an integrated CFD simulation framework, generating a parameter combination table through an orthogonal test, and performing simulation calculation; an RL-GHEM method is provided, the weight and combination strategy of a base model are optimized, linear and nonlinear combination modes are dynamically switched, and irreversible loss prediction models under different working conditions are constructed. The hybrid integrated model based on reinforcement learning guidance is provided, the model combination strategy is dynamically optimized through the reward mechanism, the base model with the optimal performance is optimized, the prediction precision, stability and robustness are improved, precise prediction of the irreversible loss of the air compressor is achieved, and the problem that in the prior art, the prediction precision is insufficient under variable working conditions is solved.

The present invention discloses a computer motherboard automated integrated test and intelligent diagnosis system and method, which relates to the field of computer motherboard test diagnosis technology, including a test platform building module, multi-interface adaptation and automatic motherboard identification, including a high-precision signal source and acquisition card, a modular architecture and high-speed bus interconnection; a test project execution module, which carries out multiple functional tests and simulates multiple scenarios to adjust the load; a data acquisition and storage module, which synchronously acquires multiple types of data through multiple channels, and has distributed storage and redundant backup; an intelligent diagnosis and analysis module, big data and machine learning algorithm diagnosis, a report generation and output module, a template engine generates reports and optimizes layout; a system self-check and calibration module, which starts each self-check module. The present invention realizes efficient and accurate testing of computer motherboards, reliable data acquisition and storage, modular design facilitates upgrading, and convenient remote functions, improves test and diagnosis efficiency and quality, helps motherboard production, maintenance and research and development, and enhances industry competitiveness.

The invention discloses a sealing dynamic performance experiment test platform which comprises an environment box, an experiment sleeve, a hydraulic oil pump, a high-speed reciprocating device and a leakage detection device, a temperature control device I and a base are arranged in the environment box, a temperature sensor probe is arranged in the base, and the experiment sleeve comprises a left guide sleeve, a shaft sleeve and a right guide sleeve. A left guide sleeve and a right guide sleeve are arranged between the shaft barrel and the base, a seal is arranged between the left guide sleeve and the right guide sleeve, a coaxial through hole is axially formed between the left guide sleeve and the right guide sleeve, a to-be-tested sealing piece is arranged between the shaft barrel and the base, an oil supply pipeline and an oil return pipeline are arranged between the shaft barrel and the base and provided with a seal, and the oil supply pipeline and the oil return pipeline are both communicated with a hydraulic oil pump containing a temperature control device II. The lower portions of the left guide sleeve and the right guide sleeve are respectively provided with an inverted funnel structure and a middle inclined notch. The device can provide single or multi-working-condition combined simulated use working conditions such as high temperature, high pressure, high speed, pulse, low temperature and reciprocation, measure the leakage rate in real time, and realize data measurement and performance evaluation of hydraulic reciprocating dynamic sealing.

The invention provides a physical-numerical hybrid scale model test method for a floating fan, and belongs to the technical field of offshore wind power generation. The test method comprises the steps that the floating fan is modeled into a physical model and a numerical model, and besides the physical model and the numerical model, a test platform further comprises a measuring system and a loading system; real-time interaction is carried out on actual measurement signals of the measurement system and calculation results of the numerical model through the computer, loading of the signals is achieved through the loading system, and building and closed-loop control of the hybrid test platform are achieved. And finally, required information is extracted through visual interface monitoring. According to the method, the dynamic response performance of the key structure can be accurately captured, and a series of problems of scale effect, scale criterion incompatibility caused by the scale effect, difficulty in indoor test simulation of the offshore floating fan and the like can be solved.

The invention belongs to the field of gas explosion test technology development, and relates to a reinforced full-size residential building structure gas leakage explosion multi-parameter test platform and method, which can be used for simulating the whole process of a gas leakage explosion accident in a real residential building scene. The gas leakage explosion evolution mechanism and disaster-causing consequence research under multiple ignition sources, multiple gas types, multiple pressure relief conditions and multiple obstacle environments can be realized. The test platform can simulate a resident house type, and through local reinforcement design and coupling test technology development of the test platform, a high detonation pressure, high simulation and multi-parameter gas explosion repeated test is realized.

The invention discloses a VR-HIL multi-sensor closed-loop test platform for remote driving, and particularly relates to the technical field of remote driving analogue simulation control, and the VR-HIL multi-sensor closed-loop test platform comprises a time calibration module, a scene disturbance module, a fusion judgment module, a response management module and a closed-loop driving module. Through multi-source time alignment, three-dimensional environment disturbance simulation, multi-channel fusion judgment and control instruction dynamic scheduling, high-precision closed-loop interaction among perception, control and disturbance is realized, the reproduction and response capability of a system to positioning abnormity and perception uncertainty in a complex urban environment is enhanced, and the overall authenticity and stability of a test platform are improved; according to the method, high-precision time alignment of multi-source sensing data is realized, the reproduction capability to a city complex interference environment is enhanced, adaptive optimization of fusion precision and stable control response rhythm are realized through a fusion-feedback-strategy linkage mechanism, and the closed-loop reliability and sensing control collaboration of a test platform are improved.

The application provides a large-span bridge substructure vehicle-fire wind force real-time hybrid test platform and implementation method, the platform comprises a physical loading and transmission system, a T-shaped wind-fire coupling simulation system, a modularized prying integrated system, an intelligent control and calculation system and a multi-dimensional high-precision monitoring system. The method realizes real-time pre-test of the boundary displacement / force of the test piece through the construction of a numerical substructure fast calculation model based on LSTM and converts the boundary displacement / force into a loading instruction to drive the through core jack to realize thermal force coupling interactive loading; the T-shaped wind-fire coupling simulation system reproduces the real vehicle fire scene under the influence of the environmental wind. The test platform supports independent loading of any component of the cable system, can execute open space self-defined fire test and closed space standard fire test, and accurately analyzes the cable failure mode, critical temperature threshold and damage evolution law under fire through the multi-dimensional high-precision monitoring system, thereby providing a high-fidelity test platform and analysis method for fire resistance design of large-span bridges.

The invention provides a power electronic component thermal resistance transient overload test method and system, and the method comprises the following steps: building a test platform, carrying out the initialization calibration of a test environment, and enabling the test platform to be integrated with a power drive module; the high-frequency sampling and dynamic adjusting technology is adopted, temperature, voltage and current data are collected at the sampling rate not lower than 10 kHz, the sampling interval is adjusted according to the thermal time constant, the advanced sensor and calibration technology is combined, coupling changes of temperature and electrical parameters are accurately captured, and the testing precision is improved; meanwhile, by means of a hardware synchronous clock and a rapid data processing technology, full-time tracking of rapid fluctuation of thermal resistance in the transient overload process is achieved, key characteristic parameters such as a thermal resistance peak value and response time are accurately extracted, and a reliable basis is provided for performance evaluation of components; in addition, various transient power waveforms and combinations thereof are supported, abundant transient overload working conditions are preset, a complex overload scene is simulated, and the practicability and reliability of the test are enhanced.

The invention relates to the technical field of underground engineering and geotechnical mechanics, and provides an ABAQUS secondary development-based underground engineering blasting simulation method, which comprises the following steps of: 1, establishing a geometric model and dividing a calculation region into an Euler domain and a Lagrange domain; step 2, calling and realizing a JH-2 constitutive model through a UMAT user subprogram interface of the ABAQUS; step 3, modeling in an Euler domain by adopting a JWL state equation; step 4, applying a coupling Euler-Lagrange method; 5, setting boundary conditions and blasting loading parameters of the geometric model; and step 6, performing transient dynamics calculation, and outputting a result for analyzing a blasting effect. According to the scheme, a high-precision numerical test platform can be provided for underground engineering blasting design and safety control, engineering risks are reduced, blasting parameter configuration is optimized, and remarkable engineering application value and popularization significance are achieved.

The invention belongs to the technical field of industrial equipment health monitoring and predictive maintenance, and discloses a machine tool feed shaft precision degradation predictive maintenance method based on a continuously optimized Mamba network. According to the method, a vibration signal of a machine tool feed shaft is collected through a three-way vibration sensor, and a low-dimensional feature vector is constructed after baseline correction, filtering noise reduction and feature extraction of an auto-encoder. The method comprises the following steps: pre-training a Mama network model by using full life cycle data of a test platform bearing, capturing a state evolution law in combination with a dynamic parameter generation mechanism, and discretizing a state-space equation through a zero-order retention rule to realize efficient time sequence modeling. In actual monitoring, the model predicts a future feature sequence based on part of input data, calculates health indexes and compares the health indexes with multi-stage thresholds, and four-stage state judgment of health / sub-health / initial degeneration / serious degeneration is achieved. A continuous learning mechanism is further introduced, model parameters are dynamically updated through experience playback and small learning rate fine adjustment, and working condition changes and novel fault modes are adapted.

The invention provides an intelligent test platform, which comprises a test demand analysis module used for carrying out demand analysis on input test demand information based on a demand analysis agent to obtain a plurality of test demand items; the test case generation module is used for calling a case generation agent to generate a plurality of test cases corresponding to a plurality of selected target test demand items in response to a selection operation on the plurality of test demand items; the test script generation module is used for calling a script generation agent to generate at least one test script corresponding to at least one checked target test case in response to check operation on the test cases; the test data demand analysis module is used for calling a data demand agent to perform demand analysis on the test case to obtain a plurality of test data demands; and the test data generation module is used for calling a data generation agent to generate test data corresponding to the test data demand. According to the invention, the test efficiency and the test reliability are improved.

The invention discloses an electric field analysis and optimization method for a transformer withstand voltage and partial discharge test platform, and the method comprises the steps: building a digital model of the test platform, obtaining a preparation technology standard and historical manufacturing measurement data of a target test platform, defining an influence variable which influences the distribution of an electric field, simulating the distribution of the electric field under different preparation differences, and carrying out the optimization of the electric field. Establishing an electric field simulation database; identifying test platform electric field sensitive areas under different preparation differences by adopting a spectral clustering algorithm based on the electric field simulation database, constructing a knowledge graph, constructing a sensitive area identification model based on a graph neural network, and performing model training through the knowledge graph; structural features and preparation features of the to-be-analyzed test platform are obtained, a local sensitive area of the to-be-analyzed test platform is recognized in the sensitive area recognition model, and if the local sensitive area exists, an optimization scheme is formulated for test platform optimization assistance, so that the design reliability and operation safety of the transformer test platform are improved.

The invention relates to the technical field of digital simulation, and discloses a hardware-in-the-loop simulation test method for a control and protection system of an energy storage power station. The method comprises the following steps: acquiring operation data of an energy storage power station, and establishing an SOC-power coupling constraint mechanism by adopting a state space decomposition algorithm; establishing a current-voltage-SOC three-dimensional protection criterion based on the battery state parameters; calculating power balance distribution of the multiple energy storage power stations by adopting a distributed coordination control algorithm; configuring a hardware interface signal synchronization protocol to establish a test platform; and loading a multi-scene fault working condition to execute automatic verification and outputting a performance evaluation result. The technical problem that the energy storage power station control and protection system lacks a high-precision, multi-scene and hardware-in-the-loop integrated simulation test verification method is solved, and the precision, efficiency and safety of test verification of the energy storage power station control and protection system are improved.

The invention relates to the field of electronic design automation (EDA), and provides an AMS circuit automatic design method using a large language model. The method aims at solving the problem that an existing AMS circuit design is insufficient in automation degree, and mainly comprises the steps that a schematic circuit diagram and text description are extracted from literatures, and a data set containing the schematic circuit diagram, a netlist and annotation information is constructed; performing connectivity detection on the schematic circuit diagram, and extracting a netlist; carrying out annotation processing to obtain annotation information; constructing a knowledge graph for storing circuit information; obtaining a design strategy by using a large language model, and describing a circuit architecture; according to the design strategy and the local annotation, relevant circuits and test platforms are retrieved, a complete circuit topology is assembled, and simulation is carried out; size optimization is carried out based on constraints, and a Bayesian optimization algorithm is used for solving; and if the initial topological structure cannot meet the performance target, carrying out topological reconstruction. According to the invention, the automation level and efficiency of analog and mixed signal circuit design are improved.

The invention relates to the technical field of flow chart automatic testing, and provides a flow chart automatic testing method, system and device of a control system and a storage medium so as to solve the problems of low testing efficiency and poor accuracy. The method comprises the following steps: acquiring a film thickness and transverse tension fluctuation curve by using an intelligent textile sensor array, generating a tension compensation factor based on a phase difference to correct the film thickness, and establishing a thickness distribution topology model; performing non-contact scanning by using a terahertz wave emission array, and activating a defect mark cluster when Doppler frequency shift is detected; transmitting the thickness distribution model and the defect characteristics to a test platform, reconstructing a control logic and generating a test script, and realizing a virtual-real synchronous test through a communication protocol; and generating a process parameter correction factor according to a test result, and feeding back the process parameter correction factor to the distributed control system to optimize the tension closed-loop control module, and generating a matched terahertz verification map. According to the technical scheme provided by the invention, the efficiency and accuracy of automatic testing of the flow chart can be improved.

The invention discloses a cross-platform software compatibility testing and optimizing method, belongs to the technical field of software testing, and aims to solve the problem of existing cross-platform software compatibility testing. Firstly, software is installed on different test platforms, and function, interface and performance tests are carried out; the function test simulates user operation, calculates an average response delay time difference and a success rate, and marks functional abnormality key points; dividing detection points in interface testing, analyzing color, definition and coordinate values, and marking interface abnormal key points; the performance test monitors the number of flash quit times and the completion duration, and marks performance abnormity key points; then, the abnormal key points are sent to a positioning display module, different mark circles and colors are set in a problem display model according to abnormal types and severity, and priority ranking is carried out; maintenance personnel can optimize the software according to the data in the problem display model, so that the root of the problem is quickly positioned, the development efficiency is improved, and the quality and stability of the software on different platforms are ensured.

The invention provides a simulation ablation test platform and test method for a filter bank circuit breaker, and relates to the technical field of circuit breaker contacts, and the test platform comprises a simulation breaking ablation module which is connected in series with a to-be-tested test circuit breaker, and simulates the opening operation to carry out the accelerated ablation of the contact of the test circuit breaker; the switching erosion simulation module is used for being connected in series with a to-be-tested test circuit breaker and simulating switching-on operation to perform accelerated ablation on a contact of the test circuit breaker; and the dynamic contact resistance test module is used for being connected to two ends of the test circuit breaker to be tested and monitoring the voltage of the contact, the current flowing through the contact and the stroke signal in the opening or closing process of the test circuit breaker so as to determine the dynamic change of the contact resistance of the contact. According to the scheme, accelerated ablation can be carried out on the circuit breaker by simulating the opening and closing working conditions of the circuit breaker, and then the service life state of the circuit breaker is tested and evaluated.