3811results about "Vibration testing" patented technology

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 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 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 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 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 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 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 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.

The invention discloses a fault detection method and system for a fan frequency converter based on big data, and relates to the technical field of fault detection, and the method comprises the steps: arranging a sensor group, and obtaining the real-time operation data of the fan frequency converter; performing entity identification on the historical fault description data to obtain associated parameters of fault types; assigning an initial weight to the associated parameter of each fault type; calculating a real-time deviation ratio, a fault prediction accuracy error and a statistical deviation; calculating a dynamic adjustment coefficient obtained by real-time feedback of each sensor parameter; calculating an error index of each parameter, and optimizing a dynamic adjustment coefficient through a gradient descent algorithm; and calculating a comprehensive fault index by adopting the optimized dynamic adjustment coefficient, and establishing a hierarchical early warning mechanism. The technical problems that potential faults of the frequency converter are difficult to accurately and timely detect in the prior art, so that the operation efficiency of a fan is reduced, even serious consequences are generated, and normal production and operation are influenced are solved.

The invention relates to the technical field of vibration monitoring, in particular to a self-powered transmission line fitting aeolian vibration damage diagnosis system and method, and the system comprises a sensing collection module, a signal decoupling module, a damage identification module, a damage association module and a risk assessment module. According to the method, stress wave velocity and acceleration data are synchronously collected, time alignment is implemented, feature coupling precision is enhanced, wave crest offset and energy density are respectively extracted by using moving average filtering and wavelet transform, effective data segments are dynamically screened, and environmental noise interference is suppressed. A stress wave propagation change rate is quantified based on a path attenuation model, a continuous energy abnormal node is matched to realize damage positioning, a breeze response abnormal region is identified by combining vibration direction change and a signal envelope offset degree, multi-dimensional features are coded and subjected to risk judgment through a neural network, a damage positioning and risk assessment closed-loop framework is formed, and the risk assessment accuracy is improved. And the spatial resolution and evaluation precision of aeolian vibration damage identification under complex working conditions are significantly improved.

The invention discloses an L-shaped wind wave flow-earthquake simulation system and method suitable for a high gravity field, the simulation system comprises a model box, a wind generation system, an L-shaped wave generation system, a flow generation system and a vibration seabed model, and the model box is used for accommodating and installing each system and is arranged on a rotating arm of a centrifugal machine in an up-and-down swinging manner; the wind generation system is used for forming horizontal airflow circulation, the L-shaped wave generation system is used for generating waves, the flow generation system is used for generating flow, and the vibration seabed model is used for researching interaction between a maritime work structure and seabed soil under various sea conditions. The simulation system can reproduce sea wind, wave, ocean current and earthquake scenes in a high gravity field.

The invention provides a fatigue life testing device for fan blades, and relates to the technical field of material performance tests.The fatigue life testing device comprises a detection bin, a driving mechanism is fixedly installed at the rear end of the detection bin, the detection bin comprises a detection supporting frame, a detection air bin is transversely and rotationally installed in the detection supporting frame, and a detection sliding groove is formed in the top of the detection air bin; air vents are formed in the two sides of the detection air bin, an air inlet is fixedly formed in one of the air vents in the detection air bin, and a plurality of temperature detectors are fixedly installed at the bottom of the detection air bin. Through cooperation of the spherical swing clamp and the adjusting ring, the fatigue life of the fan blade when the fan blade is vibrated in different directions can be detected; according to the invention, the influence of different wind directions on fan blade vibration during working of the fan blade can be simulated through the detection wind bin, so that the fatigue life of the fan in different wind power environments can be detected.

The present application discloses a displacement sensing apparatus and displacement sensing method for a building structure, and a storage medium. The displacement sensing apparatus comprises: a fixing module comprising a fixing base and a fixing support, wherein the fixing base is configured to be coupled with a monitoring point for a structure under measurement to form a whole structure; and a projection module and a camera module, wherein the camera module is arranged in front of the projection module by means of the fixing support at an angle perpendicular to the field of view, and is configured to collect a laser image formed on the projection module by a laser emission module which is provided at a fixed point.

The invention discloses a multi-dimensional controllable fault-crossing tunnel seismic response modular test device and method, and the device comprises a modular box model which comprises an upper disc box and a lower disc box, the upper disc box is installed on a vibration table, and the lower disc box is installed on a linear sliding table; the two fault dip angle adjusting systems are arranged, and the two fault dip angle adjusting systems are symmetrically arranged between the upper wall box body and the lower wall box body; the number of the positioning modules is two, and the two positioning modules are detachably arranged on the upper disc box body and the lower disc box body correspondingly; the two ends of the tunnel model are installed on the two sets of positioning modules respectively; the monitoring system is arranged in the tunnel model; and the terminal system is connected with the monitoring system. According to the method, the failure mode evolution law of tunnel linings with different section forms is researched by changing the geometrical morphology of the fault, and a basis is provided for the anti-seismic optimization design of a cross-fault tunnel lining structure.

The invention relates to the technical field of blade monitoring, in particular to a long flexible blade real-time monitoring and fault early warning method which comprises the steps that vibration signals of a long flexible blade in the running state are collected, and the vibration signals are subjected to the aerodynamic load, gravity and centrifugal force multi-factor coupling effect; constructing an overdetermined equation set containing a multi-source excitation characteristic based on the blade dynamic model; decomposing the vibration signal by adopting a sparse decomposition algorithm to obtain a signal decomposition result; based on the signal decomposition result, solving the overdetermined equation set to obtain modal parameters of each coupling vibration source; and determining a state monitoring result of the long flexible blade according to the modal parameters of the coupling vibration sources.

The invention discloses a high-speed train body health monitoring system and method based on a distributed IMU, and belongs to the technical field of mechanical vibration testing, and the method comprises the steps: obtaining a preset structure topology model of a high-speed train body, recognizing a key structure region, and constructing a physical topology grouping mapping table; deploying a plurality of inertial measurement unit nodes to the key structure area and carrying out relevance division to obtain a physical topology group; the method comprises the following steps: receiving a real-time operation condition signal from a train control system, performing feature extraction on vibration data acquired by inertial measurement unit nodes in a physical topology group, generating a region collaborative feature vector, performing space-time anomaly analysis, positioning a damage generation region, and generating a residual life evaluation parameter according to the vibration feature variation of the damage generation region. According to the method, physical topology grouping mapping and working condition self-adaptive feature extraction technologies are adopted, space-time transmission consistency verification and an aging dynamic correction mechanism are combined, and accurate positioning of a damaged area and reliable evaluation of the residual life can be achieved.

The invention discloses a multi-mode rainy day area road flatness detection method by means of Carla training, and relates to the technical field of road flatness detection, and the method comprises the steps: collecting real rainy day road surface images and vehicle parameters, and constructing a real data set; a rainy day scene is simulated in Carla, and terrain, wet and slippery materials and weather are configured; the method comprises the following steps: acquiring multi-modal data such as simulation point cloud and acceleration through a laser radar and a vibration sensor, and constructing a simulation data set; fusing real and simulation data to train a multi-modal neural network; extracting and fusing point cloud and acceleration features; road height variances and ranges are predicted to assess flatness. According to the method, the problem of scarcity of real data in a rainy day environment is solved by using Carla to generate synthetic data, the real acquisition cost is reduced, the detection precision is remarkably improved, various rainfall intensities and terrains can be covered, data complementation of the laser radar and the vibration sensor is realized, and the robustness in a rainy day is improved through dynamic weighting of an attention mechanism.

The invention discloses a frequency converter maintenance test system with a protection function, which belongs to the technical field of frequency converter testing and comprises a detection seat, a simulation unit for simulating actual working conditions of a frequency conversion control panel is arranged on the detection seat, and a detection mechanism for detecting a diode in the frequency conversion control panel is further arranged on the detection seat. Through dynamic cooperation of the polarization assembly and the rotary simulation disc, the vibration direction of the vibration source can be flexibly adjusted, so that a multi-dimensional vibration scene possibly encountered in actual work of the frequency conversion control panel is covered, and the problem that vibration source simulation is lacked in a traditional frequency converter testing process is solved; an elastic supporting environment of actual installation is simulated through the air bag spring suspension, vibration energy emission distortion caused by rigid fixation is avoided, the accuracy of a large-capacitance vibration fatigue test is improved, automatic step-by-step wiring operation of detection is achieved through cooperation of the detection driving assembly and the universal test meter, and the overall detection wiring efficiency is improved.

The invention relates to the technical field of insertion and extraction force testing, and discloses a detection device and method for automobile exterior trimming part assembling, and the device comprises a bottom frame, a tension testing assembly, a vibration mechanism, and an extrusion mechanism, the vibration mechanism comprises a gear-missing column, a moving plate, a first electric push rod, a placing plate, and a vibration spring, and the bottom frame is provided with a sliding groove. The moving plate is slidably connected into the sliding groove, the first electric push rod is fixedly installed in the sliding groove, the output end of the first electric push rod is fixedly connected with the side wall of one end of the moving plate, one end of the vibration spring is fixedly connected to the bottom frame, the placing plate is fixedly connected to the other end of the vibration spring, and a mounting block is arranged on the bottom frame. According to the device, the vibration mechanism and the extrusion mechanism are matched, so that the bumper support on the placement plate continuously shakes, various road surface vibrations borne by an automobile in the driving process are simulated, and the reliability of the buckle under long-term vibration is accurately evaluated.

The invention provides a free boundary supporting system for a horizontal modal test of a large rocket. The free boundary supporting system at least comprises a rack car, a pressure container, a free membrane type air spring and a control assembly. The rack car at least comprises a bottom truss and a top truss, and the bottom truss is provided with a moving device; the pressure container is specifically a gas storage container located between the bottom truss and the top truss, and the top of the pressure container is provided with a sealing flange connector. The free membrane type air spring is arranged on the upper end face of the top truss, the bottom of the free membrane type air spring communicates with the pressure container through the sealing flange connector, and a bracket used for supporting a rocket is arranged on the top of the free membrane type air spring. The control assembly at least comprises an acquisition module, a controller and an execution module which are in communication connection in sequence; freedom degrees of translation, rotation and torsion of the rocket in a modal test are provided by the free membrane type air spring.

The present invention relates to the technical field of intelligent out-of-distribution fault detection for construction machinery, and discloses an out-of-distribution fault detection method and system based on energy propagation and graph learning, and the method includes: acquiring vibration acceleration signals in typical fault states, carrying out similarity calculation to obtain an adjacency matrix composed of the maximum mutual information coefficients, and taking the adjacency matrix as input in a graph neural network; carrying out feature extraction on the adjacency matrix through adopting a GraphSage graph convolution method, and generating each node representation; calculating an energy score of each node, and distinguishing between in-distribution data and out-of-distribution data; and enhancing out-of-distribution data confidence estimation for each node, and carrying out out-of-distribution data identification and out-of-distribution data detection under different working conditions of a rolling bearing.

The invention discloses a ship equipment vibration test method and system based on frequency domain kurtosis mapping and non-Gaussian signal generation. The ship equipment vibration test method comprises the following steps: collecting an actual ship impact vibration signal and extracting a target power spectral density curve; the method comprises the following steps: identifying an impact energy concentration frequency band based on spectrum energy distribution, carrying out frequency band division by adopting an elliptical filter bank with a second-order section structure, and calculating an envelope kurtosis value of each frequency band to establish a kurtosis-frequency mapping model; after the initial Gaussian driving signal is generated, a non-Gaussian driving signal is generated through a phase randomization and amplitude dynamic scaling algorithm based on a mapping model; a multi-target optimization controller based on Pareto leading edge search is adopted, a power spectral density error and a kurtosis error are taken as optimization targets, synchronous optimization is carried out through fast non-dominated sorting and an adaptive hybrid variation strategy, and a driving signal is output. According to the invention, the broadband and non-Gaussian impact vibration environment of the ship equipment in the actual severe sea condition can be reproduced in a high-fidelity manner, and the authenticity of the test and the fault mode coverage capability are remarkably improved.

The invention belongs to the technical field of aero-engine vibration tests, and particularly relates to an aero-engine vibration assessment test method and system. Comprising the following steps: determining the worst vibration environment of accessories; determining the staying rotating speed of an engine rotor and the staying time of the staying rotating speed; according to the staying rotating speed of the engine rotor and the staying time of the staying rotating speed, a vibration assessment test run spectrum is formulated; based on the worst accessory vibration environment, carrying out an engine complete machine test by referring to the vibration assessment test run spectrum; generating an engine rotating speed and vibration curve graph according to the whole engine test measurement data, and making an accessory vibration limit value; an accessory vibration assessment test is carried out on a complete engine, and the complete engine used in the accessory vibration assessment test simulates the possible maximum vibration environment and test temperature of accessories in a full operation cycle and a full rotation speed range; and the installation and vibration environment is more in line with the engineering practical situation.

The invention discloses a steering column performance test bench and a test method thereof, and relates to the technical field of steering column performance test. The steering column performance test bench comprises a detection bench, a servo motor and a driving assembly, and is used for driving the upper surface of the detection bench to rotate. A first hydraulic rod is hinged to the mounting frame, a same connecting plate is hinged to the other end of the first hydraulic rod and the lower position of the outward side of the mounting frame, two clamping pieces are arranged on the upper side and the lower side of the outer side of the connecting plate, and the upper clamping piece and the lower clamping piece on the same side are used in cooperation and used for clamping a steering column; and the moving assembly is used for driving the mounting frame, the first hydraulic rod above the mounting frame, the clamping piece and the steering column to do horizontal reciprocating motion. According to the invention, multiple performance tests can be carried out on the same steering column in sequence, the automation degree is high, the overall test time is shortened, and the test efficiency is improved.

The invention relates to the technical field of slope simulation tests, in particular to a high and steep embankment slope soil engineering simulation test device and method.The high and steep embankment slope soil engineering simulation test device comprises a multi-degree-of-freedom vibration table, a slope assembly, an airflow assembly and a driving assembly, the slope assembly is installed on the multi-degree-of-freedom vibration table, and the airflow assembly is installed on the driving assembly; the airflow assembly is located above the side slope assembly, and the driving assembly is connected with the multi-degree-of-freedom vibration table, the side slope assembly and the airflow assembly; the shifting piece is connected with the frame unit and is used for driving the inclination of the frame unit to change; the data acquisition system is used for monitoring the motion characteristics and collapse deformation of the slope model in the simulation process in real time and collecting data information generated in the test process; the problems that a traditional slope test device cannot dynamically simulate gradient gradual change caused by earthquake collapse, and the multi-disaster coupling effect of rockfall impact and hydrological airflow disturbance is difficult to reproduce are solved.

The invention relates to a hydroelectric main shaft all-condition simulation test system and method, and the system comprises a fixed rack, one side of the fixed rack is provided with a tripping starting detection device, the fixed rack is provided with a hollow three-axis platform, a three-axis excitation system and a rotation driving part, the moving end of the three-axis platform is connected with a hollow floating rack, and a bearing is disposed in the floating rack. The rotation driving part comprises a power part and a main shaft connected to the torque output end of the power part, the main shaft is in transmission connection with the rotating disc, a hydroelectric large shaft used for a simulation test is installed on the rotating disc, and the three-shaft excitation system is used for applying X-direction, Y-direction and Z-direction high-frequency sine excitation loads to the hydroelectric large shaft of the rotating disc. The device is used for overcoming the defects that an existing testing device mainly focuses on vibration loading of a static mechanical device, simulation and performance testing cannot be carried out on dynamic behaviors under the composite working conditions of rotation, vibration and impact of a hydroelectric large shaft, and safety testing and rating cannot be carried out on a hydroelectric generating set sensor and a tripper overspeed protection device.