112 results about "Frequency response analysis" patented technology

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 relates to the technical field of audio testing, and discloses an intelligent audio testing system frequency response analysis method, device and equipment, and the method comprises the steps: carrying out the audio parameter initialization of an intelligent audio testing system, and obtaining a testing parameter matrix and an excitation signal; performing dual-channel acquisition and time-frequency feature extraction to obtain a time-frequency feature data set; executing double-branch processing of time domain noise reduction and frequency domain enhancement to obtain a purified feature data set and a feature weighting matrix; performing segmented recursive calculation and feature aggregation to obtain a frequency response feature vector; decomposing the frequency response feature vector according to a test frequency band, and performing environment compensation and nonlinear calibration to obtain a standard frequency response data set; and inputting the standard frequency response data set into the deep neural network for feature recognition and mode classification to obtain a frequency response curve and a phase characteristic curve, thereby improving the test precision, the anti-interference capability, the automation degree and the adaptability of the intelligent audio test system.

The invention belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of a primary and secondary fusion circuit breaker, which comprises the following steps: acquiring state data of the circuit breaker, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprints through nonlinear segmented harmonic analysis, constructing a multi-dimensional permeation characteristic matrix, and establishing a micro-scale electrothermal coupling map; performing impedance distortion analysis to obtain a nonlinear region situation table, performing multi-frequency response analysis to obtain a harmonic penetration curve, and constructing a high-frequency harmonic penetration path spectrum; a micro-region diagnosis algorithm is established, nonlinear impedance calibration is carried out, and a multi-level protection instruction sequence is generated; adjusting the operation state of the circuit breaker to obtain a circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; according to the invention, accurate identification and early warning of the abnormal-state area in the circuit breaker are realized, and the safe and stable operation capability of the primary and secondary fusion circuit breaker is improved.

The invention relates to the technical field of defect diagnosis, in particular to a production defect diagnosis method and system for a quartz crystal resonator. The method comprises the following steps: extracting a micro-acoustic response signal of each processing stage based on an ultrasonic excitation and response monitoring device, and carrying out acoustic time-frequency structure analysis and response track trend analysis and extraction to obtain a multi-stage crystal voiceprint behavior track sequence; deploying a multi-angle structured light interferometer array to carry out acoustic monitoring and synchronous visual acquisition, carrying out light stripe form response deviation calculation, and extracting a light stripe form response deviation section; and sound-light behavior frequency response analysis is carried out on the multi-stage crystal voiceprint behavior track sequence and the light texture form response deviation section, acousto-optic mismatch index fitting is carried out, and an acousto-optic fusion feature deviation database is constructed. Through accurate and efficient defect diagnosis and positioning, the production yield of the quartz crystal resonator is improved, and waste and energy consumption of a production line are reduced.

The invention discloses a dynamic monitoring and precision compensation system for an industrial robot. The dynamic monitoring and precision compensation system comprises a multi-clamping-jaw wear state monitoring module, a clamp holder fine control module and a combined wear limit judgment module. The multi-clamping-jaw abrasion state monitoring module collects abrasion state information of clamping jaws in real time through a micro-deformation monitoring unit and a frequency response analysis unit and evaluates the abrasion degree of the clamping jaws. The clamp holder fine control module calculates clamping correction parameters according to the abrasion information and the workpiece clamping data, and the clamping force and the clamping position are adjusted. And the combined wear limit judgment module monitors the wear state through a single clamping jaw threshold value judgment and overall mean value judgment unit, and outputs an early warning and provides a maintenance suggestion when the wear state exceeds a threshold value. According to the method, the wear limit threshold is corrected by inputting the clamping jaw and workpiece characteristics, the wear monitoring precision and the real-time compensation capability are improved, and the precision and the reliability of the industrial robot tail end clamp holder are improved.

The invention provides a high-proportion new energy power system dynamic regulation demand quantitative evaluation method. The high-proportion new energy power system dynamic regulation demand quantitative evaluation method comprises the following steps: step (1), constructing a frequency response model of a high-proportion new energy power system; step (2), constructing a power system frequency stability demand evaluation model; and step (3), processing the maximum frequency deviation constraint. According to the high-proportion new energy power system dynamic regulation demand quantitative evaluation method provided by the invention, nonlinear constraints such as a frequency modulation dead zone are considered, a system frequency response analysis model under high-proportion new energy access is constructed, and a frequency response result is obtained through solving; and a high-proportion new energy power system dynamic adjustment demand quantitative evaluation model is established, and system adjustment demand evaluation considering multi-resource collaborative participation is realized.

A multi-scale simulation modeling method for transformer vibration noise is disclosed. In the method, transformer parameters are collected to establish a two-dimensional axisymmetric model of the winding and a three-dimensional finite element model of the iron core and the oil tank. The two-dimensional axisymmetric model and the three-dimensional finite element model are used to construct a vibration coupling model including the iron core and the winding via a shared boundary. The sound pressure on the sound pressure contour surface of the two-dimensional axisymmetric model is extracted. After coordinate transformation, the sound pressure on the sound pressure contour surface of the two-dimensional axisymmetric model is mapped to the sound pressure on the sound pressure contour surface in the three-dimensional model. Based on the sound pressure on the sound pressure contour surface in the three-dimensional model, the magnetostriction of the iron core is simulated and calculated to obtain the time-domain calculation result of the magnetostriction. The time-domain calculation result of the magnetostriction is subjected to a fast Fourier transform to obtain the iron core deformation displacement distribution at different frequencies. The frequency response analysis of the two-dimensional axisymmetric model and the three-dimensional finite element model is carried out to calculate the winding vibration and the sound pressure distribution in the oil caused by the vibration of the iron core transmitted to the winding.

The invention discloses a method and a system for testing vibration characteristics of a metal harmonic oscillator. The method comprises the steps that a frequency response analyzer excites a metal harmonic oscillator to generate vibration, displacement change data of vibration of the metal harmonic oscillator and frequency response data of the metal harmonic oscillator are acquired, and the resonant frequency and the quality factor Q value of the metal harmonic oscillator are calculated based on the displacement change data and the frequency response data; and / or by changing the excitation position for exciting the metal harmonic oscillator, resonant frequency information of different excitation positions is measured, the resonant frequency information of the different excitation positions is analyzed, and the frequency domain image features corresponding to the excitation positions are compared; and / or direct current voltage is applied to the metal harmonic oscillator in different axial directions of the metal harmonic oscillator, and the influence of the direct current voltage on frequency cracking of the metal harmonic oscillator is tested. The technical problem that in the prior art, the metal harmonic oscillator testing process is complex is solved.

The invention relates to the field of fault monitoring, in particular to an electric energy metering box fault monitoring system based on the Internet of Things. The system comprises the following steps: a state analysis module is used for collecting multi-dimensional monitoring parameters of a plurality of electric energy metering boxes in an area, carrying out operation state analysis, and constructing an operation trend model of each metering box; the abnormal state inference module is used for carrying out residual comparison analysis on the operation trend model, carrying out abnormal state inference and marking an abnormal state metering box; the signal setting module is used for setting a lightweight excitation signal based on the abnormal state metering box to obtain an optimized excitation signal; and the excitation test module is used for carrying out signal excitation test based on the optimized excitation signal, carrying out comprehensive time-frequency response analysis and generating dynamic time-frequency response characteristics. The fault reason of the electric energy metering box is rapidly and accurately analyzed and judged, the service life of the electric energy metering box is prolonged, and the electricity utilization safety is improved.

The invention provides a CNN-LSTM-based power transmission line fault type and position identification method, and relates to the technical field of power transmission line fault detection, and the method comprises the steps: calculating a frequency response curve of a health state and each fault through measuring the voltage and current related to the health state and each fault; evaluating the action and state of the system by using a frequency response analysis method; collecting a frequency response curve, using the frequency response curve as an input data set, and assigning a category number for each fault; a CNN-LSTM fault recognition model is constructed; training the CNN-LSTM fault recognition model by using the input data set to obtain a trained CNN-LSTM fault recognition model; and using the trained CNN-LSTM fault identification model to identify the fault type and position of the power transmission line. According to the method, the fault type and position identification precision can be improved, and the requirements of the power transmission line for real-time monitoring and quick response are met.

The invention belongs to the technical field of structure topological optimization, and particularly relates to a viscoelastic structure broadband topological optimization method based on a high-order Krylov subspace method. According to the method, aiming at the nonlinear frequency response problem of the viscous-elastic material, a reduced-order subspace is constructed through high-order Taylor expansion and moment matching orthogonalization, and the solving precision and the frequency band range are remarkably improved. And based on the reduced-order model, combining the displacement square sum objective function and the volume constraint, and utilizing a gradient optimization algorithm to realize efficient topological optimization. According to the method, high-precision frequency response analysis is realized through high-order Taylor expansion and a correction term, the calculation cost is greatly reduced by more than 80% under a small amount of basis vectors, collaborative optimization is carried out through a multi-frequency-point logarithmic weighting target function, the broadband dynamic performance is remarkably improved, and the method is suitable for complex engineering scenes such as submarines and MEMS devices.

The invention relates to the technical field of equipment state monitoring, in particular to an electronic component monitoring system based on big data, which comprises a multi-frequency response analysis module, a frequency domain feature reconstruction module, a stress deviation trend module, a coupling correlation structure module and a grade mapping generation module. According to the invention, through continuous data acquisition and analysis based on multi-frequency response information, electrical parameter changes of components are tracked in real time, change trends under various frequencies are continuously monitored and accurately identified, and through analysis and extraction of frequency domain data features and combination of stress deviation trend analysis, tiny changes caused by external environment changes are identified. According to the electrical parameter change of different time slices, the long-term health state of the component is comprehensively reflected, a dynamic evolution model of the component is constructed, a multi-dimensional data association analysis method is adopted, and the component degradation process is accurately evaluated by judging the relevance among different electrical parameters. And scientific and accurate decision support is provided for component maintenance and replacement.

The invention discloses an alkaline electrolytic cell model for power system frequency analysis, and belongs to the field of power system modeling. The model is firstly based on an electrochemical semi-empirical formula of the electrolytic cell, and a first-order equivalent circuit model containing ohm voltage, inverse voltage and activation voltage is established; secondly, according to an equivalent circuit model, deriving an analytic relation between activation voltage and current of the electrolysis cell, and converting the analytic relation into a transfer function of a Laplacian domain; and finally, a PI control link is adopted to replace an inverter control link, the initial power, the power change value and the operation electrolysis power are used as input, the cell voltage is used as output, and a complete electrolytic cell frequency analysis model is constructed. According to the method, by simplifying the electrochemical process and performing frequency domain linearization processing, the application limitation of a traditional nonlinear model in frequency response analysis is overcome while the key dynamic characteristics of the electrolytic cell are reserved, and a practical and reliable tool is provided for frequency analysis and operation management of a power system.

The embodiment of the invention provides an MPV servicing vehicle body dynamic stiffness analysis method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring a first system matrix of a reordered MPV servicing vehicle body and a reordered first external steady-state excitation vector; converting the first system matrix into a second system matrix through a constructed projection model; converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the position of a non-zero element in the first external steady-state excitation vector; calculating a residual vector based on the second system matrix and a second external steady-state excitation vector; calculating a global residual vector based on the residual vector; based on the global residual vector, dynamic stiffness analysis of the MPV servicing vehicle body is completed, in this way, efficient scheduling and solving of large-scale residual vector tasks under hundreds of working conditions are achieved, and the overall calculation efficiency and the resource utilization rate of frequency response analysis are remarkably improved.

The invention discloses a precision current transformer measurement and data analysis method, particularly relates to the field of current detection and dynamic signal analysis, and comprises a precision magnetic core design scheme based on a nanocrystalline strip and a dynamic magnetic performance test and frequency response analysis method. A nanocrystalline strip with high magnetic conductivity and low loss characteristics is selected as a magnetic core material, and a high-performance magnetic core suitable for multiple frequency ranges is designed; the magnetic stability and response characteristics of the magnetic core material under different working conditions are evaluated by combining high-frequency current source excitation with dynamic magnetic performance test; a signal acquisition and frequency decoding technology is adopted, an output voltage signal is analyzed in real time, and the linearity and precision of a measurement system are optimized through a mathematical model; according to the method, accurate measurement and data analysis of complex current signals under high-precision and high-frequency conditions are realized, and the applicability and reliability of the current transformer are improved.

The invention relates to a frequency response analysis method for a wind power grid-connected system through MMC-HVDC (modular multilevel converter-high voltage direct current) based on H2 and H infinity norms. The method comprises the following steps: firstly, based on a small signal linearization theory, deducing a power frequency transfer function between active power variations of DFIG, MMC-HVDC and frequency modulation units of a synchronous generator containing a control system detailed model and frequency variations of a receiving end power grid, and establishing a system detailed frequency response model; obtaining a transfer function between the system frequency variation and the load disturbance quantity; secondly, analyzing the influence of the comprehensive inertia control parameters Kp and Kd, the virtual inertia time constant Hmmc of the converter station and the difference adjustment parameter R of the synchronous machine on the system frequency response characteristic of the detailed frequency response model of the established system based on the H2 and H infinity norm theory;

The invention discloses an MEMS gravity sensor air pressure and temperature decoupling compensation method and system based on frequency response analysis. Placing the MEMS gravity sensor in a preset air pressure and temperature environment, obtaining a plurality of groups of corresponding resonant frequencies and quality factors Q, and constructing a mapping relation between the Q and the air pressure and the temperature; in the operation process of the sensor, the sum Q is measured in real time, and the variable quantity of the ambient air pressure and the temperature is obtained through inversion of the mapping relation; and introducing the variation of the ambient air pressure and the temperature into a compensation correction model, and decoupling and correcting the gravity output of the sensor. According to the method, an external sensor is not needed, inconsistency caused by space position difference is avoided, the system structure is more compact, hardware complexity and power consumption are lower, the long-term stability and measurement precision of the MEMS gravimeter in a complex environment can be remarkably improved, and miniaturization, low power consumption and array application are facilitated.

The application relates to a wind turbine frequency modulation method, and belongs to the technical field of wind power generation. The method comprises the following steps: obtaining a real-time operation condition of a wind turbine, and calculating maximum available frequency modulation energy of the wind turbine; dividing a whole frequency modulation process under power system power disturbance into time periods, and constructing a power system frequency response analysis model corresponding to each time period; calculating a corresponding relationship between a frequency minimum point and frequency modulation consumed energy of the whole frequency modulation process based on the power system frequency response analysis model; constructing an optimization model of frequency modulation control parameters, taking the maximum frequency minimum point as an objective function and taking the constraint condition that the frequency modulation consumed energy does not exceed the maximum available frequency modulation energy; solving the optimization model to obtain optimal wind turbine frequency modulation control parameters, and performing frequency modulation control on the wind turbine based on the frequency modulation control parameters. The wind turbine frequency modulation method can effectively improve the system frequency minimum point under power disturbance and optimize the wind power frequency modulation control effect.

The invention discloses a robot screw turning control method based on end excitation and feature fusion. According to the method, firstly, high-frequency excitation is applied through an end tool, circular scanning is carried out, and the normal vector and the local rigidity of the screw hole are accurately sensed by combining contact force frequency response analysis and weighted least square fitting; secondly, in the process of leading-in along the normal direction, damping and rigidity parameters of an impedance controller are adjusted in a self-adaptive mode based on real-time excitation-response phase difference identification, and smooth guidance is achieved. Then, in the screwing-in stage, disturbance caused by attitude deviation and the like is estimated through an extended state observer, and compensation motion is generated through a self-adaptive impedance controller; and finally, fusing the rigidity, the phase margin and the friction coefficient characteristics obtained in the previous steps, carrying out feedforward initialization, and dynamically adjusting torque-angle double-closed-loop control parameters to realize precise tightening. According to the invention, sensing and control integration is realized, and the precision, adaptability and reliability of robot tightening operation are obviously improved.

The present application belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of primary-secondary fusion circuit breaker, comprising: obtaining circuit breaker state data, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprint through nonlinear segmented harmonic analysis, constructing a multi-dimensional penetration feature matrix, and establishing a micro-scale electric-thermal coupling atlas; obtaining a nonlinear region situation table through impedance distortion analysis, obtaining a harmonic penetration curve through multi-frequency response analysis, and constructing a high-frequency harmonic penetration path spectrum; establishing a micro-region diagnosis algorithm, performing nonlinear impedance calibration, and generating a multi-level protection instruction sequence; adjusting the operating state of the circuit breaker, obtaining the circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; the present application realizes accurate identification and early warning of abnormal regions inside the circuit breaker, and improves the safe and stable operation ability of the primary-secondary fusion circuit breaker.

This application provides a method for calculating vehicle vibration and noise caused by electric air conditioning compressor excitation, including the following steps: conducting a compressor excitation test bench test to obtain the excitation force of the compressor on the vehicle body; establishing a vehicle finite element model; performing finite element frequency response analysis based on the vehicle finite element model and the excitation force to obtain the support reaction force at each compressor bracket system connection point, and obtaining the noise transfer function from each compressor bracket system connection point to the noise target point inside the vehicle; combining the support reaction force and the noise transfer function to perform transmission path analysis to obtain the vibration and noise at the noise target point inside the vehicle. This embodiment uses bench testing and CAE methods to simulate the characteristics of vehicle vibration and noise caused by compressor excitation in the early stages of vehicle development, accurately assessing the impact of electric air conditioning compressor excitation on vehicle vibration and noise. This allows for early detection and optimization of problems in the early stages of the project, avoiding difficulties in structural modifications later in the development process, and improving the NVH optimization effect of the electric vehicle air conditioning system.

The invention aims to provide a relative calibration method suitable for an RCS (radar cross section) test in a high-temperature environment, and belongs to the technical field of radar cross section test. According to the method, a conventional metal calibration body is selected to carry out RCS testing, a logarithmic function fitting method is introduced by testing frequency domain response data of the calibration body at different temperatures, a fitting function of scattering characteristics of the standard calibration body along with temperature changes is obtained through fitting, and frequency response of the standard calibration body at the temperature required by testing is calculated; and in combination with the frequency response of the to-be-tested target at the test required temperature, analyzing to obtain the RCS value of the to-be-tested target. According to the method, under the condition that the temperature resistance of the standard calibration body is limited, the RCS value of the to-be-tested target at the temperature required by the test can be accurately obtained, the test error caused by oxidation deformation of the standard calibration body due to the high temperature is reduced, and the high material cost and the high processing cost brought by using a high-temperature-resistant metal material as the standard calibration body are also saved.

A present measurement assistance device is a measurement assistance device that inputs a measurement signal used for a frequency response analysis of a servo system to the servo system, the measurement assistance device including a generation unit configured to generate a first signal determined to eliminate a shift between a first position of a load of the servo system at a start of an excitation with respect to the servo system of a speed command signal that changes with time to include a large number of frequency components and a second position of the load at an end of the excitation of the speed command signal, a synthesizing unit configured to generate a synthesized signal in which the first signal is superimposed on the speed command signal, and an excitation execution unit configured to input the synthesized signal to the servo system.

The present invention belongs to the technical field of structural topology optimization, and specifically relates to a wide-band topology optimization method for viscoelastic structures based on the high-order Krylov subspace method. This method addresses the non-linear frequency response problem of viscoelastic materials by constructing a reduced-order subspace through high-order Taylor expansion and moment matching orthogonalization, significantly improving the solution accuracy and frequency band range. Based on the reduced-order model, combined with the displacement squared sum objective function and volume constraint, a gradient optimization algorithm is used to achieve efficient topology optimization. The present invention achieves high-precision frequency response analysis through high-order Taylor expansion and correction terms, significantly reducing the computational cost by more than 80% with a small number of basis vectors, and co-optimizing with a multi-frequency point logarithmic weighted objective function to significantly improve the wide-band dynamic performance, which is applicable to complex engineering scenarios such as submarines and MEMS devices.

The invention discloses a new energy unit-station level frequency modulation parameter measurement and identification method based on frequency response analysis, and the method comprises the steps: enabling an obtained model to give consideration to the frequency modulation control precision and the adaptability to a plurality of operation conditions through constructing a closed-loop design of offline modeling-online correction-regular updating; a systematic technical path is provided for improving the frequency modulation performance of a new energy station, so that the frequency safety of a novel power system is guaranteed; comprising the following steps: off-line constructing a frequency modulation model of a first-layer unit level of a new energy station through principle analysis; constructing a second-layer station-level frequency modulation coordination control model of the new energy station; establishing a multi-dimensional frequency response deviation quantitative index system; designing a frequency modulation parameter correction optimization model in combination with measurement data of a field frequency test or an online frequency response event to obtain online measurement and discrimination parameters of the new energy unit-field station level frequency modulation model; and a regular updating mechanism is established, and frequency modulation parameters are re-identified and corrected.

The invention discloses a vehicle control unit shell random vibration reliability prediction method based on multi-physics field coupling, and the method comprises the steps: constructing a controller shell three-dimensional model, optimizing the grid transition form of the three-dimensional model through employing a variable density method, and generating a finite element model; loading the finite element model into Ansys software to create an analysis working condition, setting a boundary condition and a load, and defining material and unit attributes at the same time; carrying out free mode and constraint mode analysis on the controller, and identifying a dynamic rigidity weak region of the structure; a Harmonic Response module is used for carrying out frequency response analysis; creating a non-stationary random vibration field of the controller in nCode software, and calculating power spectrum density values in X, Y and Z directions; the frequency response result in the step (4) is imported into a Design Life module, and the power spectrum density value in the step (5) is added; dynamic response evaluation and data post-processing under random excitation are implemented; and determining a weak area of high-cycle fatigue failure of the controller under the extreme working condition and optimizing a reinforcement scheme.

The application discloses a kind of multi-machine frequency response analysis method, device, equipment, medium and program product, it is related to the multi-machine frequency response modeling analysis technical field of enhanced SVG and distributed phase modifier, including: inputting preset disturbance power in the multi-machine frequency response model of target multi-machine grid-connected system, obtains the grid frequency variation of target multi-machine grid-connected system;Wherein, multi-machine frequency response model is based on the first equivalent frequency response model of phase modifier cluster access grid and the second equivalent frequency response model of enhanced SVG access grid is constructed, and is configured to reflect the functional relationship between disturbance power injected into grid and grid frequency variation, phase modifier cluster includes multiple distributed phase modifier;Based on grid frequency variation, the frequency stability of target multi-machine grid-connected system is analyzed.The application can realize the systematic frequency response analysis of enhanced SVG and distributed phase modifier multi-machine grid connection.

The invention provides an optical anti-shake parameter determination method and device based on a neural network, a medium and equipment, and the method comprises the steps: carrying out the frequency response analysis test of different camera module motors at different characteristic frequencies under each group of historical anti-shake parameters, and obtaining a first test result; performing anti-shake performance test on different camera modules to obtain a second test result; according to the first test result and the second test result, a training data set is determined to train a pre-constructed neural network until training conditions are met, and a trained neural network prediction model is obtained; predicting a to-be-detected optical anti-vibration parameter by using the neural network prediction model; therefore, the first test result and the second test result cover the actual performance of the motors with different characteristics under different anti-shake parameters, and the anti-shake parameters adaptive to the motors with various characteristics can be predicted by the neural network prediction model obtained by training the pre-constructed neural network by taking the mapping data as the training data set. And the anti-shake effect of the camera module is ensured.

The invention provides a measurement assistance device capable of suppressing position deviation of a load in frequency response analysis performed by inputting a speed command into a servo system. This measurement assistance device inputs a measurement signal for frequency response analysis of a servo system to the servo system, and is provided with: a generation unit that generates a first signal, the first signal is determined so as to cancel a deviation between a first position of a load of the servo system at the start of the oscillation of a speed command signal to the servo system and a second position of the load at the end of the oscillation of the speed command signal, and the speed command signal varies with time so as to include a plurality of frequency components. A combining unit that generates a combined signal in which the first signal is superimposed on the speed command signal; and a vibration execution unit that inputs the combined signal to the servo system.

The invention relates to the field of new energy automobile electric driving systems, in particular to an equivalent stiffness and damping analysis method for a vehicle-mounted motor rotor assembly. According to the method, accurate analysis and evaluation of the equivalent stiffness and damping of the rotor assembly can be realized through modal identification and frequency response analysis technologies without depending on whole vehicle and bench type test resources, a quantitative basis is provided for structural optimization and process improvement of the motor rotor assembly, the development period can be effectively shortened, and the cost can be reduced.