2097 results about "Test platform" patented technology

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 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 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 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 belongs to the technical field of space inertial sensors, and particularly relates to a phase synchronization monitoring and adjusting method for multichannel excitation signals. Comprising the steps that S1, a test platform is built, and the test platform comprises a sensitive probe and capacitance sensing electronics; s2, enabling the center of the electrode cage to have small displacement relative to the center of the detection polar plate in the X-axis direction of the detection polar plate, and transmitting different excitation signals to each excitation polar plate by capacitive sensing electronics; s3, iteratively adjusting the initial phase of each excitation signal based on an optimization algorithm; and S4, when the measured induced voltage output by the to-be-measured induction pole plate pair after the initial phase is adjusted for two adjacent times meets an iteration stop condition, completing the phase synchronous monitoring and adjustment of the multichannel excitation signal. According to the invention, the influence of the structural design of the sensitive probe of the capacitive displacement sensor, line delay and other factors on multichannel excitation signal phase delay can be offset, and the sensitivity is improved.

The invention discloses a multi-mode perovskite and laminated cell comprehensive test system and method. The system comprises a darkroom, a test platform, an LED light source module, a CCD camera, a laser, an adjustable constant current source, an electronic load and an upper computer. The darkroom is used for shielding external ambient light and providing a dark test environment; the test platform is installed in the darkroom, and a to-be-tested battery is placed on the test platform; the LED light source module is used for providing a test light source; the CCD camera is used for capturing an optical signal generated by the battery to be tested in the testing process; the laser is used for emitting a laser beam to excite the to-be-detected battery to generate a specific optical response; the adjustable constant current source and the electronic load module can be electrically connected with a to-be-tested battery on the test platform, the adjustable constant current source is used for supplying current to the to-be-tested battery, and the electronic load module is used for simulating different load conditions; and the upper computer is used for realizing intelligent control of the test process and processing and display of test data.

The invention provides a performance testing method and device for a large language model and related equipment. The performance testing method comprises the steps that multiple testing platforms for testing, testing scene configuration parameters and a structured testing data set for testing are determined; on the basis of the test scene configuration parameters and the structured test data set, synchronous constraint parameters are generated and distributed to the multiple test platforms, and then a preset load generator is used for controlling the multiple test platforms to concurrently execute reasoning test tasks about the large language model; and when the test is executed, collecting multiple dimension performance indexes of each test platform in real time for data analysis, and generating a reasoning performance comparison evaluation report of the large language model in the multiple test platforms according to a data analysis result. According to the method, the cross-platform performance evaluation period is greatly shortened, and the waste of computing resources is reduced. Manual operation errors are avoided, comparability of multi-platform performance indexes is guaranteed, and more accurate and reliable multi-platform performance test results can be obtained.

The invention provides an energy efficiency optimization and predictive regulation and control method for a building electromechanical system based on digital twinning. The method comprises five layers of architectures including a physical entity layer, a data acquisition and interaction layer, a digital twinning model layer, an energy efficiency analysis and optimization layer and a predictive regulation and control layer. The dynamic digital twinborn body interacting and synchronizing with the physical electromechanical system in real time is constructed, fundamental transformation from passive lag control to prospective predictive control is achieved, a high-fidelity virtual model is used as a nondestructive testing platform, countless operation strategies can be safely and rapidly simulated and evaluated in a virtual space, and therefore accurate optimization is achieved, and the real-time dynamic digital twinborn body is obtained. The overall energy efficiency of the system is remarkably improved, the dilemma that the traditional method makes consideration and loses others is eliminated, and the leap-type improvement of the comprehensive operation quality is achieved.

The invention relates to the field of power simulation optimization, in particular to a new energy charging simulation optimization method and device based on a charging and discharging test platform. The method comprises the following steps of performing new energy charging pile charging simulation based on a charging and discharging test platform, performing adjustable power time period analysis, and generating a plurality of adjustable power windows; performing timing sequence energy flow trend change mining and dynamic power distribution fitting according to the plurality of adjustable power windows, and constructing a dynamic power path distribution map; performing minimum power drift point detection according to the dynamic power path distribution map, and performing power fluctuation compensation inversion to obtain power fluctuation compensation configuration parameters; and performing local dynamic power regulation according to the power fluctuation compensation configuration parameters, and constructing a local window dynamic power regulation strategy. Through dynamic charging simulation, the power stability of new energy charging is improved, and the power response balance is optimized.

The invention provides an arc fault detection method based on an improved empirical mode decomposition algorithm, and the method comprises the steps: collecting an arc fault signal through building a benchmark test platform, carrying out the preprocessing, and carrying out the decomposition of the signal through employing a completely adaptive noise set empirical mode decomposition algorithm, according to the method, useful intrinsic mode functions containing main characteristics and information of arc fault signals are screened out, then the signals are reconstructed, spectrum characteristics are extracted, and finally, a DBSCAN clustering algorithm is used for carrying out clustering analysis on characteristic vectors so as to judge whether the arc faults occur or not. The modal aliasing phenomenon and the endpoint effect are effectively avoided, and the accuracy of arc fault detection is improved. Meanwhile, through adaptive spectrum segmentation and feature extraction, arc fault signals can be accurately identified under strong noise interference.

The invention discloses a method and device for controlling grabbing of dynamic strips based on visual servo guidance and a test platform. According to the method for grabbing the dynamic strip-shaped object based on visual servo guidance control, the mechanical arm is guided and controlled to grab the dynamic strip-shaped object by adopting an image-based visual servo method, and real-time tracking of the dynamic pose of the strip-shaped object and immediate response of the action of the mechanical arm are realized through continuous sensing, processing and tight coupling of execution links; therefore, a more accurate, stable and efficient grabbing effect can be achieved in a highly dynamic and uncertain working environment; a test platform capable of simulating dynamic swing of a real strip-shaped object is also built, and a prediction control method and a visual servo control method are combined, so that effective verification and optimization of the high-precision and real-time grabbing process of the dynamic strip-shaped object are realized; the platform can be used for systematically researching the grabbing capability under various disturbance conditions in a laboratory environment, and a solid technical foundation is laid for automatic and intelligent operation in practical application.

The invention relates to the technical field of rubber material performance detection, in particular to a dynamic test platform and method for evaluating the bonding effect and fatigue life of rubber and a rubber cord fabric. The dynamic test platform comprises a driving mechanism, a test platform, a clamping mechanism, a monitoring system, a data acquisition module, a control system and a data analysis module. The driving mechanism can adjust the frequency, the displacement amplitude and the acceleration of loading deformation; the test platform supports normal loading pressure to realize simulation of different load working conditions; the clamping mechanism is a two-way adjustable clamp, and free displacement is achieved through a sliding rail mechanism; the monitoring system integrates a force sensor, a displacement sensor and a temperature sensor. The data acquisition module records loading process data; the control system sets parameters through a touch interface and monitors the test in real time; and the data analysis module generates an adhesion performance, fatigue life and damage form evaluation report based on an algorithm. The device can accurately reproduce the adhesive property change under the dynamic working condition, comprehensively analyzes the adhesive strength and fatigue life, provides a scientific basis for research and development and quality control of rubber products, and is suitable for testing the adhesive property of composite materials such as tires and transmission belts.

The invention discloses a low-temperature CMOS carrier MFP and microscopic parameter extraction method and system, which are corresponding schemes, in the scheme, a carrier MFP extraction model for eliminating a microscopic unknown quantity is constructed by utilizing a geometric scaling rule of quasi-ballistic transport and an existing effective mobility extraction technology, and an MFP extraction model for eliminating the microscopic unknown quantity is constructed by utilizing the geometric scaling rule of quasi-ballistic transport and the existing effective mobility extraction technology; the MFP extracted by the carrier MFP extraction model is ensured to be a pure experiment observation value on the basis that effective quality, Fermi velocity and scattering time do not need to be predicted based on the self-consistency of macroscopic current and voltage data along with the change of channel length; meanwhile, on the basis, the microcosmic parameters are decoupled, so that the decoupled microcosmic parameters are extracted one by one; compared with an existing scheme, the method can be directly applied to a standard wafer-level test board in the industry, MFP distribution of hundreds of devices can be rapidly counted, and a feasible engineering scheme is provided for low-temperature process monitoring.

The invention discloses a multi-axis multi-field coupling fatigue test device, and belongs to the technical field of material testing. The device comprises a rack, a multi-axis loading unit, an environment simulation unit, a dynamic sealing interface and a cooperative control system. The core of the device is that the test sample can simultaneously bear the coupling effect of multi-axis mechanical stress (pulling, pressing and twisting) and various environmental fields (such as high and low temperatures, corrosive media, illumination and electric fields) through a highly integrated design; and the dynamic sealing problem of the actuator rod in the environment box is solved through an innovative dynamic sealing interface (such as labyrinth-magnetofluid composite sealing). According to the invention, accurate linkage control of multiple channels is realized through the cooperative control system, the service environment of key parts under actual complex working conditions can be truly simulated, and a reliable test platform is provided for failure analysis and life prediction of products under multi-field coupling.

The invention discloses a face gear planetary transmission system dynamic uniform load test platform and test method, and belongs to the field of gear transmission, and the test platform comprises a rack, a drive motor, a step-up gear box, a face gear planetary transmission system, a magnetic powder brake, a torque sensor, a slip ring, a stress strain test system and the like. The face gear planetary transmission system comprises an input face gear, a planet wheel, a planet carrier, a fixed face gear and the like. According to the dynamic uniform load test, stress values at the tooth root of the face gear and the tooth root of the planetary gear are measured mainly through strain gauges, and the corresponding relation between the tooth root stress and the meshing force at the gear meshing point is obtained through finite element simulation. And calculating the dynamic uniform load coefficient according to the dynamic meshing force root-mean-square values and the average values obtained at the tooth roots of the face gear and the planetary gear. By testing and analyzing the dynamic uniform load coefficient, the load distribution characteristic of the face gear planetary transmission system can be accurately revealed, a scientific basis is provided for structural parameter optimization, meshing performance improvement and reliability design of the face gear planetary transmission system, and then accurate and high-performance design of the transmission system is achieved.

The invention discloses a chip testboard-oriented vibration noise adaptive suppression system, and particularly relates to the technical field of chip testing. Comprising a chip testboard multi-modal sensing module, a multi-modal data feature extraction module, a vibration noise adaptive suppression decision module, a chip testboard active vibration suppression execution module and a system state monitoring and feedback module. The chip testboard multi-mode sensing module comprises a vibration sensor, an acoustic sensor and a motion state sensor, data collected by the three sensors are preprocessed through a time synchronization protocol and standardized operation, and a preprocessed chip testboard multi-mode data set is obtained; according to the invention, the DRL intelligent agent is used as a decision module, network parameters can be finely adjusted on line through a reward signal of the system state monitoring and feedback module, a new working condition can be automatically adapted, the optimal vibration suppression performance can be maintained, and extremely high robustness can be shown.

The invention relates to the technical field of extracranial strike testing, in particular to digitally-controlled extracranial strike construction equipment of a traumatic brain injury model. Comprising a test platform, a sliding rail installed on the test platform and arranged in the length direction of the test platform, an animal fixing platform slidably connected with the test platform through the sliding rail, an impact structure arranged on one side of the test platform and a driving structure used for driving the animal fixing platform to move towards the impact structure. The impact structure is fixedly connected to the test platform, the output end of the impact structure faces the animal fixing platform, an experimental animal is installed on the animal fixing platform, the driving structure drives the animal fixing platform to enable the experimental animal to actively impact, and the impact structure enables the experimental animal to impact a fixed acting point at a certain initial speed. The system is more in line with the injury mechanism of a patient with clinical actual craniocerebral trauma, and a tester can accurately control and monitor parameters according to the moving speed and the moving distance of the animal fixing platform.