6768results about "Vibration testing" patented technology

The application provides a fault prediction method and apparatus, an electronic device and a storage medium. The method comprises: obtaining a vibration signal collected by a sensor installed on a target component of a target device, and cleaning and segmenting the vibration signal to obtain a target vibration signal; inputting the target vibration signal into a target anomaly judgment model to obtain an output result, and according to the output result, determining whether the target vibration signal is abnormal to obtain an anomaly judgment result; when the abnormal judgment result shows that the target vibration signal is abnormal, inputting the target vibration signal into a target fault prediction model to obtain a fault prediction result, wherein the target fault prediction model is obtained by combining an encoder of the target anomaly judgment model and a newly added full connection layer. The application solves the problem in the prior art that a faulty device cannot be timely maintained because the fault can only be monitored when the device fault is quite obvious.

The invention provides an equipment supervision data real-time analysis method and system, and the method comprises the steps: calculating an energy value of a frequency band corresponding to a sub-band signal, determining the energy characteristics of the surface roughness and dust deposition distribution uniformity of a blade in each sub-band in a square sum form, and generating energy distribution vectors which are arranged according to a frequency band sequence; performing time-frequency analysis on the vibration signal by using the acquired real-time rotating speed information of the gas turbine, identifying a frequency component corresponding to the eccentric distance value of the rotor and the vibration frequency offset, and determining the amplitude of the frequency component; according to the classification result and the real-time rotating speed information, the comprehensive influence index of the material density change rate and the ash deposition layer thickness difference is calculated, the fault early warning level is determined through a weighted average method, and an early warning signal is generated; and according to the change trend of the early warning signal and the blade edge wear degree, a random forest algorithm is adopted to predict a development curve of the vibration frequency offset in the future target time, and real-time equipment supervision analysis data are obtained.

The invention provides a valve actuator full life cycle intelligent test system and method. The system comprises a combined load generation module used for generating an initial dynamic proportion of axial thrust and radial disturbance force according to a test protocol instruction, simulating a comprehensive stress state of an actuator under the impact of a pipeline medium, and outputting mechanical data containing thrust fluctuation characteristics in real time; the environment coupling module is used for dynamically adjusting an environment stress condition according to the test protocol instruction; the digital twinborn analysis module is used for comparing the actual displacement track of the actuator with the theoretical model track through a space-time alignment algorithm according to the mechanical data and environmental stress conditions to obtain a deviation feature vector; and the intelligent diagnosis module is used for carrying out dynamic time warping matching on the basis of the deviation feature vector and a preset historical fault database, outputting a fault type identification code and confidence, and generating a test report. According to the scheme, the accuracy of accurate evaluation of the full life cycle state of the valve actuator is improved.

The invention relates to the field of building structure safety detection, and discloses a building structure anti-seismic performance monitoring method and system. The method comprises the following steps: acquiring multi-source response data such as acceleration, displacement, strain and inclination angle; obtaining a structure standard response based on wavelet denoising and standardization processing; adopting a multi-order modal recognition algorithm to extract structural dynamic characteristic parameters; performing structural damage evaluation based on the modal change index, and combining the yield strength, the load index and the displacement margin to calculate the residual bearing capacity of the structure; and finally, outputting an anti-seismic grade early warning signal. The system comprises a structure response acquisition module, a modal identification and damage evaluation module and a residual bearing capacity calculation and early warning module. According to the method, real-time quantitative analysis of the performance of the structure under the earthquake or load effect can be achieved, the evaluation precision is high, the applicability is high, and the wide engineering popularization value is achieved.

The invention discloses a vibration table test device and a test method for seismic dynamic response of a fault-crossing mountain tunnel. The test device comprises an earthquake simulation vibration table, a laminated shear model box, surrounding rock, a fault fracture zone, a tunnel model and a monitoring and measuring system. Wherein the earthquake simulation vibration table inputs earthquake waves and provides earthquake power; the bottom of the laminated shear model box is fixed on the earthquake simulation vibration table, and the laminated shear model box is filled with surrounding rocks and fault fracture zones; the fault dip angle is 90 degrees, and left and right surrounding rock elevations are inconsistent; the tunnel model comprises a non-shock-absorption layer and a shock-absorption layer which are buried in the surrounding rock in the model box in parallel and perpendicularly intersect with a fault fracture zone. The monitoring and measuring system is used for measuring tunnel acceleration and strain, surrounding rock acceleration, fault acceleration and the like in the seismic oscillation process. The test device can simulate the dynamic response process of the fault-crossing mountain tunnel under the action of an earthquake, and time evolution and spatial distribution characteristics of tunnel earthquake response are determined.

The invention relates to the technical field of data processing, and discloses an operation state monitoring method and system for vibration test equipment. The method comprises the following steps: generating a multi-dimensional physical characteristic data stream through vibration waveform calibration according to operation parameters collected by each sensor of vibration test equipment; performing frequency response analysis on the data stream to obtain physical response characteristics; based on this, a test calibration reference is established; outputting test state parameters according to the reference analysis real-time response characteristics; and performing performance attenuation analysis according to the parameters, and generating an equipment quality evaluation report. According to the comprehensive analysis method based on the multi-dimensional physical characteristic data flow, real-time monitoring, multi-parameter joint evaluation and performance attenuation trend analysis of the dynamic characteristics of the equipment are achieved, so that the accuracy, comprehensiveness and predictability of state monitoring of the vibration test equipment are improved, and the reliability and consistency of test results are ensured.

The invention discloses a bridge expansion joint damage detection and positioning method based on multi-modal signal fusion, and the method comprises the following steps: S1, building a detection platform, and collecting the multi-source data of a vibration signal, a sound signal and a video signal; s2, the vibration signals, the sound signals and the video signals are preprocessed respectively, and respective features including time domain features, frequency domain features and time-frequency domain features are extracted; s3, carrying out sound-vibration fusion on the vibration signal and the sound signal, and carrying out audio-video fusion on the sound signal and the video signal to realize integration of multi-modal features; and S4, outputting a damage identification and positioning result, and providing decision support for maintenance and management of the bridge expansion joint. According to the method, through multi-modal fusion signal analysis, the health condition of the bridge expansion device is monitored in real time, and damage is found in time, so that potential safety risks are prevented, safe operation of the bridge is ensured, and a new technical means is provided for health monitoring and maintenance of the bridge.

A performance testing device for the piston rod sealing assembly includes a bracket, a support apparatus, a drive apparatus and a leakage detection apparatus, where the support apparatus includes a cylinder body that is internally provided with a movable channel, and the movable channel is configured to allow a piston rod equipped with a sealing component to pass therethrough; the drive apparatus is provided on the bracket and configured to be connected with the piston rod; the leakage detection apparatus includes a limit member and an oil receiver, the limit member is provided with a detection channel and an oil channel and connected to the cylinder body, the detection channel is communicated with the movable channel and configured to allow the piston rod to pass therethrough; one end of the oil channels is communicated with the detection channel and the other end thereof is communicated with the oil receiver.

The invention discloses a valve vibration impact test method and system based on digital twinning, and belongs to the technical field of industrial equipment test and evaluation. The method comprises the following steps: firstly, deploying a multi-source sensor network, constructing a physical entity layer of a valve vibration impact test, collecting and preprocessing various physical monitoring data, and constructing a digital twinborn body layer; secondly, real-time data assimilation with a physical test bed is realized through parameter calibration and updating of a digital twinborn model based on various physical monitoring data and the digital twinborn layer; and finally, executing a virtual vibration impact test, realizing prediction and evaluation of global response and key part information of the physical entity according to a test result, and finally realizing interaction and performance prediction. And the valve vibration impact test is realized through the valve vibration impact test system. According to the method, the fault diagnosis capability, the early damage identification capability and the valve state prediction and evaluation capability can be remarkably improved, and the defect of insufficient field monitoring information is overcome.

The present invention discloses a defect detection method, device and equipment for a high-altitude fall prevention system, wherein the method includes: regionalizing the high-voltage electric control components and multi-layer composite insulation structures in the high-altitude fall prevention equipment; determining the high-voltage pulse parameters of each functional area and applying pulses according to environmental parameters and electromagnetic interference data; applying progressively increasing mechanical tension to the suspected stratified area; applying multiple thermal stress excitations to the target area; performing high-resolution acoustic imaging scanning to generate defect location information. The technical solution of the present invention can effectively cope with complex electromagnetic interference and extreme climatic conditions in high-altitude environments, and through a multi-dimensional and multi-stage detection process, accurately identify and locate microscopic stratified defects in high-altitude fall prevention systems, providing important guarantees for the safety of high-altitude operations.

The invention discloses a wiring harness dynamic load and electromagnetic interference coupling test method, and relates to the technical field of wiring harness testing, and the method comprises the steps: S1, defining a plurality of environment parameter groups, and constructing a test platform; s2, dynamic current pulse and multi-axis vibration excitation are synchronously loaded; s3, applying broadband electromagnetic interference signals and monitoring signal crosstalk amplitude and bit error rate changes; s4, the sensor nodes are dynamically configured according to the topological structure of the wire harness; s5, generating a feature vector; s6, outputting a wire harness performance index; s7, outputting a wire harness fault probability prediction value; s8, obtaining prediction data; s9, triggering a high-speed data recording mode, and storing original sensor data 60 seconds before the fault; and dynamically adjusting the gradient step length and the loading sequence in the environment parameter group. Performance evaluation, fault prediction and service life management can be carried out on the wire harness under complex working conditions, and the reliability and safety of an automobile electrical system are improved.

The invention provides an abnormal sound test bench capable of rapidly switching modes. The abnormal sound test bench comprises a base, a first test unit, a second test unit and a power device arranged between the first test unit and the second test unit. The power device comprises two vibration exciters arranged in the y direction. The first test unit can make a to-be-tested part generate single-degree-of-freedom vibration in x, y and z directions, and the second test unit can make the part generate pitching and side-tipping composite-degree-of-freedom vibration. The first test unit and the second test unit can be respectively driven by the same group of power device, only the tested part needs to be transferred in a short distance during mode conversion, the same group of power device is used in the two test modes, and the test efficiency is greatly improved during the test of the rear half part. The relevant parameters between the tested part and the power device are acquired in the first half part, so that the debugging time between the part and the power device is greatly saved, and the testing efficiency is improved.

The invention discloses a wire drawing machine operation state evaluation method and system based on deep learning, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: deploying a multi-source sensor at a preset part of a wire drawing machine, and forming a multi-dimensional operation data flow; the deep learning evaluation model is trained based on the standardized time series data set, model parameters are optimized through a cross entropy loss function, the model learns the characteristic difference between a normal working condition and an abnormal working condition, and the deep learning evaluation model is trained based on the standardized time series data set. And inputting a multi-dimensional operation data flow collected in real time into the trained deep learning evaluation model to generate a dynamic evaluation report. According to the wire drawing machine operation state evaluation method and system based on deep learning provided by the invention, a visual operation state score can be output, detailed fault type probability distribution is given, and intelligent support is provided for equipment maintenance decision.

The invention relates to the technical field of mechanical vibration testing, in particular to a method for testing dynamic rigidity and damping characteristics of an engine support, which comprises the following steps of: 1, simulating a boundary; step 2, double-source excitation loading is carried out; step 3, dynamic response acquisition: arranging vibration measurement points in the main shaft direction of the rigidity of the support to acquire acceleration signals in three directions, synchronously acquiring excitation force signals, and recording all the signals at a set sampling rate after anti-aliasing filtering; 4, constructing a frequency response matrix: performing time-frequency transformation on the exciting force signal and the acceleration signal, and calculating a cross-point frequency response function matrix; 5, parameter decoupling calculation is carried out, wherein parameter decoupling is achieved through cross iterative optimization; and 6, outputting parameters. Through the decoupling calculation of the low frequency band and the high frequency band, the cross iteration optimization method can effectively reduce the calculation error, improves the parameter decoupling precision, and guarantees the reliability of the test result under different frequency bands.

The invention provides a pipeline optical cable laying state monitoring method and system based on artificial intelligence, and the method comprises the steps: obtaining an optical cable vibration signal, and generating a vibration feature data set based on the optical cable vibration signal; constructing a mechanical equilibrium equation based on the vibration characteristics of the vibration characteristic data set, and calculating the stress states of the optical cable in different pipeline environments; obtaining the current laying tension, generating a control strategy, and adjusting the laying tension to obtain an updated tension value; constructing an anomaly detection model of the spatial-temporal characteristics to generate an anomaly score, and identifying whether the optical cable is abnormal or not in real time; and generating an updated laying strategy and a construction quality report based on the corrected tension control signal. The problems of abnormal stress, monitoring lag, lack of intelligent optimization and the like in the prior art can be effectively solved, and the safety, stability and construction efficiency of optical cable laying are improved.

The invention discloses a refrigeration equipment fault prediction and diagnosis method, device and system, and the method comprises the steps: collecting a vibration signal and a working condition signal of refrigeration equipment, carrying out the preprocessing of the original data of the vibration signal and the working condition signal, and obtaining the vibration characteristic data and the working condition data; aligning the vibration characteristic data with the working condition data, dividing working conditions according to the working condition data, and classifying the vibration characteristic data under each working condition to obtain a plurality of groups of fault diagnosis data sets; on the basis of each working condition, historical healthy vibration data of the refrigeration equipment are obtained, a fault diagnosis model is constructed and trained, abnormal diagnosis is conducted on the vibration characteristic data through the trained fault diagnosis model, and abnormal fault points are obtained; and fault positioning analysis is carried out by adopting a spectrum analysis method, fault positioning information corresponding to each working condition is obtained, and a maintenance work order of the refrigeration equipment is generated and displayed. According to the method, accurate fault pre-judgment diagnosis can be carried out on the refrigeration equipment, and maintenance is convenient.

The invention discloses a road network abnormal event identification and risk evaluation early warning method based on vibration perception, and relates to the technical field of urban road safety monitoring. Comprising the steps of collecting road vibration data of a road network through a sensor; preprocessing the road vibration data through Kalman filtering and multi-dimensional feature extraction; abnormal event recognition is carried out on the processed road vibration data through a differentiation algorithm, wherein abnormal events comprise vehicle overload, illegal construction and road structure damage; and carrying out risk scoring on the abnormal events through dynamic weight distribution, dividing the risk scores according to the risk levels, and carrying out graded response. According to the invention, through differential algorithm design, a mixed model architecture and a hierarchical response mechanism are adopted, abnormal event identification, risk level quantitative evaluation and differential early warning processing are realized, the safety state of an urban road network is monitored in real time, and early warning information is provided.

The invention relates to the technical field of automatic equipment control, in particular to an automatic equipment control system and method and a storage medium. The method comprises the following steps that a high-frequency laser scanner is used for scanning the surface of a target polishing part, B-spline surface fitting is carried out, and a surface fitting surface model is generated; controlling the polishing operation of the polishing industrial robot based on the surface fitting curved surface model, and performing polishing contact state detection to generate contact state point cloud data; based on the contact state point cloud data, grinding expected pose error analysis is carried out, reverse impedance error compensation is carried out, and a reverse impedance compensation amount is obtained; and the joint angle of the polishing industrial robot is corrected through the reverse impedance compensation amount, so that reverse impedance control over the automatic polishing equipment is achieved. By compensating the reverse impedance error of the automatic polishing equipment, accurate control over the automatic polishing process is achieved.

An experimental model for simulating seismic soil evolution for a long-span bridge, comprising a vibration table (1), a long-span bridge model (2), damping control devices (3), vibration mechanisms (4), and cooperative control systems (6), wherein the long-span bridge model (2) comprises a plurality of bridge pier bases (21); the damping control devices (3) are fixedly connected between the bridge pier bases (21) and the vibration table (1); the vibration mechanisms (4) cooperatively drive the vibration table (1) to vibrate in the space; each cooperative control system (6) comprises a processor (61), an acceleration sensor (62) and a displacement sensor (63). A test method for dynamic response simulation of the experimental model comprises the following steps: the vibration table simulates an earthquake process, the damping control devices simulate soil evolution or geology of different sites, and the cooperative control systems acquire and collect acceleration and displacement data information of the damping control devices in real time and analyze structural responses of a long-span bridge. The experimental model can simulate seismic responses of a bridge under seismic site effects and non-uniform excitations, and has high authenticity and accuracy, a wide application range and low experimental cost.

A road state recognition method and apparatus, a computer device, a storage medium, and a computer program product. The road state recognition method comprises: acquiring acceleration data and working condition data, wherein the acceleration data is acquired by a plurality of acceleration sensors arranged in a road surface; performing feature extraction on the acceleration data on the basis of a convolutional neural network in a road state recognition model to obtain an acceleration feature; performing data splicing on the acceleration feature and the working condition data to determine a target feature vector; and on the basis of the target feature vector and a multilayer perceptron in the road state recognition model, determining a road surface damage classification result.

The invention discloses a method and device for measuring flow-induced vibration of a plate-type fuel assembly, and belongs to the field of nuclear power. The flow-induced vibration measurement method for the plate-type fuel assembly comprises the following steps: firstly, carrying out a flow-induced vibration test on a fuel plate of which the two ends are clamped and fixed, and carrying out measurement to obtain strain data and displacement data of a measurement point location on the fuel plate; establishing a simulation model of the fuel plate, simulating a flow-induced vibration behavior, verifying a calculation result and measurement data, and iterating the simulation model according to a verification result to obtain a calibration model with an error smaller than a given threshold value; a plate-type fuel assembly test piece with a plurality of fuel plates is used for carrying out a flow-induced vibration test, strain data of corresponding measurement points of the fuel plates are measured, and corresponding flow-induced vibration displacement data are given according to the strain data by using a calibration model. The invention further provides a plate type fuel assembly flow-induced vibration measuring device.

The invention relates to a roadbed compaction quality detection method and system based on multi-dimensional data, and the method comprises the steps: obtaining sensor data of a roller of a road roller in real time, and obtaining pavement images and positioning data of a plurality of continuous time points; when the road surface is flattened, the roadbed structure is gradually stable, so that the corresponding pressure data and vibration data are gradually stable. By analyzing the stability of the pressure data and the vibration data, the stability of the pressure data and the vibration data is determined. According to the method, vibration data, stable data and temperature data of a road section at a stable time point are extracted, and then a target data reference range corresponding to a corresponding temperature grade and a roadbed material is found from a pre-constructed data model, so that the target data reference range can verify the vibration data and the stable data at the stable time point; therefore, whether the road roller performs the road rolling operation in a reasonable range or not is judged. In addition, the road surface is detected by using the road surface image.

The invention provides an abnormal sound test bed for a steering pull rod. The abnormal sound test bed comprises a base, a positioning table and an excitation mechanism, the positioning table and the shock excitation mechanism are fixedly connected with the upper side of the base, and the shock excitation mechanism is arranged on the x-direction side edge of the base; the vibration excitation mechanism comprises a fixing frame, a vibration frame, a driving assembly and a plurality of elastic connecting pieces, the driving assembly comprises a transmission end capable of vibrating in the x direction, the transmission end is fixedly connected with the vibration frame, and each elastic connecting piece comprises an elastic piece, a first connecting part and a second connecting part. The first connecting part and the second connecting part are connected with the fixing frame and the vibrating frame respectively and enable the elastic piece to be arranged perpendicular to the x direction, the vibrating frame is provided with an installation base face arranged perpendicular to the x direction, and a butt joint is fixedly connected to the installation base face. According to the invention, the elastic connecting piece is arranged to limit the vibration frame, so that the vibration frame can only vibrate in the x direction, and the accuracy of abnormal sound test is ensured.

The invention discloses a frequency converter performance detection device, and relates to the technical field of frequency converters, the frequency converter performance detection device comprises a detection box, a heat-conducting fin is arranged in the detection box, and the heat-conducting fin is of a four-side square structure and forms a sealed cold and hot channel on the edge of an inner cavity of the detection box; the multiple damping shock absorbers are arranged at the bottom of the detection box; the vibration generator is arranged at the lower part of the detection box and is used for providing a vibration source for the detection box; the output end of the humidifier is communicated with the inner cavity of the detection box; and the output end of the cold-hot generator communicates with the cold-hot channel. The vibration generator, the humidifier and the cold and heat generator are arranged, the detection box is matched, multifunctional simulation of vibration, high-humidity, high-temperature and low-temperature environments in the peripheral environment is achieved, stability detection of the frequency converter under the extreme environment is achieved, and the cold and heat channel in a circulating circulation state is formed in the inner edge of the detection box; cold and hot air covers the detection box for multi-surface circulation, so that the distribution uniformity of the cold and hot air is improved.

A power tool device (102) is controlled to emit sounds that can identify the power tool device and / or be used to encode data for acoustic data transmission. Modulating the switching frequency of electronic components (370) (e.g., transistors, semiconductor switched devices) of the power tool device (102) can create an acoustic signature detectable by a microphone-equipped device (104), such as a cell phone, tablet, security camera, or the like. In this way, power tool identification and / or acoustic data transmission can be realized with existing power tool device circuitry and hardware components.

The invention provides a lubricating system fault early warning method based on data analysis, which relates to the technical field of data analysis, and is used for comprehensively analyzing vibration data and pressure data in operation data of a lubricating system, judging whether an oil way blockage phenomenon occurs in the lubricating system or not, and judging the specific blockage position and degree. Therefore, the problem that in a high-speed bearing lubricating system, due to the fact that metal abrasive dust, oil sludge and external impurities in lubricating oil accumulate and deposit in an oil way, oil way blockage is caused, poor lubrication is caused, and the bearing is damaged due to overheating can be solved.

The invention provides a weather-proof test system for an abnormal sound vibration test. The weather-proof test system comprises an environment box and abnormal sound test equipment, the environment box comprises a base table and a box body, a temperature adjusting chamber is formed in the box body, the base table is provided with a carrying base face located on the lower side of the temperature adjusting chamber, the base table is provided with a heat insulation chamber sunken relative to the carrying base face, and the heat insulation chamber is separated from the temperature adjusting chamber through a heat insulation plate; the abnormal sound testing equipment comprises a driving mechanism, a transmission mechanism and a bearing mechanism, the driving mechanism comprises a vibration exciter, the vibration exciter is arranged in the isolation chamber, and the transmission mechanism and the bearing mechanism are arranged above the carrying base plane. Different parts of the abnormal sound testing equipment are separated by arranging the temperature adjusting chamber and the heat insulation chamber, the transmission mechanism and the bearing mechanism of the mechanical part are arranged in the temperature adjusting chamber, and the driving mechanism of the electrical part is arranged in the heat insulation chamber, so that the requirement of a weather-proof test can be met, and the working stability of the vibration exciter can be ensured.

The invention provides a compound degree-of-freedom excited abnormal sound test bench. The compound degree-of-freedom excited abnormal sound test bench comprises a base, a supporting frame, an objective table, a first limiting piece, a second limiting piece and a driving mechanism, the supporting frame is provided with a first mounting part, the bottom of the objective table is provided with a second mounting part and two driving connecting parts, and one side edge of the objective table is provided with a third mounting part; the first limiting piece comprises a rod body and two first elastic parts, and the first mounting part and the second mounting part are connected with the two ends of the rod body through the first elastic parts correspondingly; the second limiting piece comprises an extension arm and a mounting seat, the mounting seat comprises a second elastic part, and the two ends of the extension arm are connected with the second elastic part and the third mounting part respectively; the driving mechanism comprises two driving end heads, and each driving end head is connected with one driving connecting part. The first limiting piece and the second limiting piece are used for supporting, limiting and guiding the objective table, composite degree-of-freedom excitation can be achieved only through z-direction exciting force, operation is convenient, and the testing effect is good.

The invention provides a motor magnetic steel sheet defect detection method based on vibration analysis, and relates to the technical field of motor fault diagnosis, and the method comprises the steps: carrying out the vibration feature extraction of a plurality of vibration data sets, inputting a plurality of vibration feature sets into a defect feature recognition library, carrying out the similar traversal comparison, and outputting a plurality of initial defect features; and collecting temperature distribution characteristics and sound wave characteristics of the target motor in a predetermined period, carrying out credible probability analysis on the plurality of initial defect characteristics, and outputting the initial defect characteristic with the maximum probability as a motor magnetic steel sheet defect detection result. According to the method and the device, the technical problems that a traditional motor magnetic steel sheet defect detection method cannot quickly and accurately identify the defect characteristics of the motor magnetic steel sheet during the operation of the motor, and the defect detection timeliness and accuracy are insufficient can be solved; and the efficiency, the accuracy and the reliability of defect detection of the magnetic steel sheet of the motor can be remarkably improved.

The invention relates to the technical field of vibration test, and discloses a micro-seismic environment simulation vibration test board and a test method thereof, which realize high-fidelity simulation of multiple types of micro-seismic scenes through a multi-source composite signal generation and waveform reconstruction technology. The dynamic adjustment capability of the control strategy is improved by using disturbance compensation and an adaptive control mechanism, real-time analysis and early warning feedback are performed on the response state in the test process based on the vibration characteristic evaluation result, and an auxiliary decision basis is provided for the vibration control strategy. Besides, a hierarchical closed-loop regulation and control mechanism is logically formed based on local output regulation among multiple axes and a global control strategy, and closed-loop linkage of the control strategy, execution response, state evaluation and control correction is realized, so that the overall regulation and control precision, response sensitivity and test precision are remarkably improved; accurate simulation and stable control of a three-dimensional vibration field are realized.