387 results about "Frequency characteristic" patented technology

The invention provides a method for extracting electrical characteristic signals of electrical equipment in a complex working condition environment, and belongs to the technical field of electrical equipment detection.The method comprises the steps that a multi-channel ultrasonic sensor array is arranged to collect partial discharge signals, background noise is eliminated through adaptive noise cancellation processing, and an ultra-sparse frequency band energy distribution vector is constructed; the method comprises the following steps: calling a self-adaptive time-frequency analysis model to extract instantaneous frequency, amplitude and phase parameters to form a micro-hour-frequency characteristic matrix, separating independent source signals through independent component analysis, calculating a kurtosis value and a skewness value, fusing multi-domain characteristics to construct a transient stationary comprehensive characteristic vector, matching with a standard discharge characteristic vector library to identify the discharge type and intensity, and calculating the discharge intensity. A corresponding prediction algorithm is selected according to the discharge mode, multi-parameter coupling optimization adjustment is started under a certain condition, an electrical characteristic signal description vector is finally constructed, and the technical problem that the partial discharge signal of the power equipment is difficult to accurately extract under a complex working condition environment is solved.

The invention relates to the technical field of generator set intelligent control, and discloses a generator set intelligent control method and system, and the method comprises the steps: obtaining the sensor data and vibration signals of a generator set; obtaining a corrected frequency characteristic value according to sensor data screening, denoising and frequency characteristic correction; generating and iteratively updating a control decision instruction sequence according to the real-time change of the vibration signal and the corrected frequency characteristic value to obtain a system stability index; and combining system stability index feedback adjustment to obtain a control decision reliability index. The method can solve the problem of noise interference under a dynamic working condition, realizes fault early warning, parameter optimization and system stability, and improves energy efficiency and operation reliability.

The invention discloses a cable high-frequency impedance characteristic analysis method based on bipolar trapezoidal wave excitation, and belongs to the technical field of power equipment state monitoring and fault diagnosis. In order to solve the problems of low test efficiency, insufficient high-frequency parameter modeling precision and weak anti-interference capability in cable high-frequency impedance characteristic analysis of a traditional sine wave excitation method, the method comprises the following steps: generating an odd-symmetry bipolar trapezoidal wave excitation signal with specific frequency and amplitude, and injecting the signal into the head end of a cable to be tested through a coupling device after power amplification; synchronously acquiring a high-frequency response signal of the key position of the cable under the excitation of the bipolar trapezoidal wave by using a data acquisition system; preprocessing the high-frequency response signal, converting the high-frequency response signal into a frequency domain through Fourier transform, calculating input impedance of the cable under different harmonic frequencies, and synthesizing a broadband impedance spectrum; based on the broadband impedance spectrum, the amplitude-frequency characteristic and the phase-frequency characteristic of impedance are analyzed, and cable state evaluation, partial discharge detection, insulation defect diagnosis or fault point positioning are realized. The method is used for an electric power system.

The invention relates to the technical field of heat supply pipe networks, in particular to a small sample learning pipeline leakage identification method based on multi-dimensional acoustic feature fusion, which comprises the following steps of: acquiring sound pressure data based on a main line of a heat supply pipe network, analyzing signal amplitude and frequency features by a sliding window, constructing a multi-dimensional acoustic feature set, screening and aggregating leakage and normal state samples, and identifying leakage and normal state samples. Comparing the difference between the new data and the prototype, quantifying the feature distance, and judging the leakage state according to the minimum attribution principle. According to the method, multi-angle behavior expression is established, a typical category prototype is generated through feature induction, multi-category feature center aggregation and dynamic measurement are combined, the high-reliability judgment capability of the leakage state is improved, compared with a traditional technology, leakage signals are comprehensively represented through multi-dimensional features, and the reliability of the leakage state is improved. The adaptability to environmental noise, sudden interference and a complex pipe network structure is effectively enhanced, misjudgment is reduced, the dependence on a large amount of labeled data is greatly reduced through the small sample learning technology, and the data collection and labeling cost is remarkably reduced.

The invention provides a probe frequency response calibration parameter determining method, a probe frequency response calibration parameter measuring system and a storage medium, and the probe frequency response calibration parameter determining method introduces a composite test signal including a steady-state frequency sweep signal and a transient pulse signal. De-embedding calculation is carried out on a data set which is obtained under the two conditions that a probe is not connected to a calibration system and the probe is connected to the calibration system and responds to the same test signal, namely amplitude division is carried out to eliminate link gain deviation, phase subtraction is carried out to strip channel phase deviation, accurate extraction of the independent frequency response characteristic of the probe is achieved, and the accuracy of the independent frequency response characteristic of the probe is improved. Therefore, the frequency response calibration parameter of the probe is determined. According to the invention, system errors introduced by a test environment and a rear-end measurement link are eliminated, the calibration precision of the amplitude-frequency characteristic and the phase-frequency characteristic of the probe in a full working frequency band is improved, and a reliable basis is provided for implementation of accurate real-time anti-distortion compensation in actual signal acquisition of measurement equipment such as an oscilloscope and the like; and the reduction authenticity of the whole measurement system in the high-frequency and broadband signal test is ensured.

The invention discloses a geophysical prospecting signal denoising method based on VMD (variational mode decomposition) combined with an improved wavelet threshold function, and belongs to the technical field of mineral exploration geophysical prospecting signal process.The method includes the steps that firstly, a decomposition mode number K of a signal is determined through VMD in a self-adaptive mode, a plurality of IMFs (intrinsic mode components) are obtained, and then according to the frequency characteristic and noise distribution of each IMF component, a wavelet threshold function is obtained; and carrying out targeted noise suppression by adopting an improved wavelet threshold function containing an adjustment parameter alpha, and finally, carrying out linear superposition reconstruction on all the processed IMF components to obtain a de-noised geophysical prospecting signal. Experimental verification shows that compared with a traditional method, the method has the advantages that the signal-to-noise ratio and the correlation coefficient of the noisy geophysical prospecting signals can be effectively increased, the root-mean-square error can be effectively reduced, the inherent defects of the traditional method are overcome, the geologic features of the geophysical prospecting signals can be effectively reserved, the method is suitable for various mineral exploration scenes, and reliable data support is provided for anomaly recognition in mineral exploration.

The invention discloses a multi-scene statistical channel fingerprint construction method and system based on frequency perception. According to the method, unified tensor modeling is carried out on statistical channel state information, and various typical statistical channel fingerprint construction scenes are uniformly expressed as a tensor recovery problem. On the basis, multi-scale frequency decomposition and reconstruction of the statistical channel fingerprints are realized through a Laplacian pyramid, and multi-scale frequency sub-band features of the statistical channel fingerprints are obtained while the reasoning efficiency is improved; and through a shared mask learning mechanism, carrying out layer-by-layer self-adaptive refinement processing on high-frequency statistical channel fingerprint components under different scales. Besides, in order to expand the characteristic receptive field under the condition that the model parameter quantity is not obviously increased, convolution processing is carried out on different frequency components in a wavelet transform domain, and decoupling extraction and efficient modeling of the statistical channel fingerprint multi-frequency characteristics are achieved. According to the method, the construction precision and the calculation efficiency can be considered in various statistical channel fingerprint construction scenes.

The invention discloses a shafting fault diagnosis method based on ship motor howling identification, and the method comprises the following steps: collecting a sound signal of a ship motor and multi-source monitoring data; preprocessing the sound signals to extract time-frequency characteristics of the sound signals; inputting the time-frequency characteristics into a pre-trained recognition model to obtain a judgment result of motor squeal; probability smoothing and threshold judgment are carried out on the judgment result, and when a set condition is met, shafting diagnosis is triggered; after the shafting diagnosis is triggered, performing data fusion on the multi-source monitoring data and the time-frequency characteristics, and judging and positioning a shafting fault based on a fusion result to obtain a diagnosis result; and displaying the diagnosis result on an intelligent monitoring platform in real time, and triggering graded alarm and remote uploading. The method and the system provided by the invention have the advantages of strong real-time performance, high anti-interference capability, reliable diagnosis result, low operation and maintenance cost and the like.

The invention provides an aircraft detection method and system based on eddy current induced optical fiber micro-vibration, and relates to the technical field of aircraft detection.The aircraft detection method comprises the steps that alternating magnetic field data of aircraft eddy current is collected, and time and frequency dimension change features are analyzed and extracted to serve as a magnetic field feature benchmark; the magnetostrictive sensing rod of the magnetoelectric sensing unit is combined with the fiber bragg grating, and magnetic field change generated by the eddy current magnetic field effect of the aircraft is converted into a voltage signal. And decomposing the time-frequency characteristics of the voltage signals according to the magnetic field characteristic reference, generating electric signal components of different frequency band magnetic field energy evolved along with time, screening characteristic magnetic field change components, and matching the characteristic magnetic field change components with a standard magnetic field mode in a preset database to identify types. Motion characteristic parameters are selected according to identification types, motion states are analyzed and flight trajectories are predicted in combination with time sequence characteristics, graded early warning signals are generated according to the position relation between the trajectories and preset safety areas, and detection and safety early warning of the aircraft can be achieved.

The invention relates to the field of aeronautical material detection, and discloses an aeronautical material detection method and system.The method comprises the steps that an ultrasonic detection signal is obtained, and frequency characteristic analysis is conducted on the ultrasonic detection signal to obtain a frequency spectrum; based on the frequency spectrum, the system can judge the source information of the ultrasonic detection signals, so that the ultrasonic detection signals with background tendency and the ultrasonic detection signals with defect tendency are distinguished; aiming at signals from different sources, the invention innovatively adopts a differential gain processing strategy: low gain is applied to the signals with background tendency to effectively inhibit the intensity of the signals; high gain is applied to signals with defect tendency so as to ensure that even weak real defect signals can be fully amplified and identified; performing defect judgment on the ultrasonic detection signal subjected to gain processing; the problems that misjudgment is introduced by the signal gain compensation module due to probe sensitivity attenuation and normal background signals and real defect signals are difficult to distinguish can be effectively solved.

The invention relates to the cross technical field of elevator fault diagnosis and signal processing, in particular to an elevator shaft breakage early fault detection signal denoising method. The method comprises the following steps: acquiring an original low and medium frequency discrete signal of elevator shaft body vibration, and filtering by adopting a four-order Butterworth band-pass filter to obtain a filtered signal; performing complementary set empirical mode decomposition on the filtering signal to obtain a plurality of IMF components and a residual component, and screening effective IMF components from all the IMF components; the center frequency of each effective IMF component is calculated, and Gaussian weight distribution is carried out on each effective IMF component based on the center frequency of each effective IMF component; performing signal reconstruction on all the effective IMF components and the residual components according to the weight of each effective IMF component to obtain a reconstructed signal; and smoothing residual noise in the reconstructed signal by adopting self-adaptive moving smoothing filtering to obtain a de-noised signal. According to the method, the 30-60Hz low and medium frequency characteristic signals generated in the elevator spindle microcrack propagation stage can be accurately extracted, so that fault judgment is facilitated.

The invention discloses a wind power plant broadband oscillation suppression method and system based on amplitude-phase characteristic remodeling. The method comprises the following steps: respectively establishing a frequency domain impedance model of each wind turbine generator set and performing dynamic order reduction, analyzing amplitude-frequency and phase-frequency characteristics of wind power plant multi-machine parallel coupling based on the order reduction model, determining an interaction rule of a module value and a phase angle, designing additional damping control and active damping control, and determining a wind power plant multi-machine parallel coupling amplitude-frequency and phase-frequency characteristic of the wind power plant multi-machine parallel coupling amplitude-frequency and phase-frequency characteristic. A weak position of a system is positioned based on an s-domain node admittance matrix method, a function is set by taking improvement of amplitude-phase characteristics as a target and optimizing and setting control parameters for a target wind turbine generator corresponding to the position, the optimized parameters are applied to the target generator, and effective suppression of broadband oscillation is realized. According to the application, the broadband oscillation problem caused by high-proportion new energy grid connection can be systematically solved by synergistically remodeling the frequency domain amplitude-phase characteristics of the wind power plant.

The invention provides an anti-interference system for micro-vibration detection. The system comprises a signal acquisition assembly and an anti-interference assembly connected with the output end of the signal acquisition assembly, and the anti-interference assembly comprises a hardware configurable filter network, an interference feature library and a control logic unit. The hardware configurable filter network receives an original vibration signal collected by the signal collection assembly as an input signal, and the control logic unit monitors the amplitude and / or frequency characteristics of the input signal in real time. And querying the interference feature library in which the mapping relationship between the interference source features and the filter configuration parameters is stored according to the monitored amplitude and / or frequency features of the input signal, so as to generate a control instruction corresponding to a query result based on the query result, thereby enabling the hardware configurable filter network to dynamically configure a filtering strategy. And filtering the environmental interference signal in the analog signal domain based on the configured filtering strategy.

Oscillator. The present invention provides an oscillator in which external heat is less likely to be transmitted to a vibrating element, and which has stable frequency characteristics. The oscillator has: an outer package; an inner package housed in the outer package and fixed to the outer package via a heat-insulating member; a vibrating element housed in the inner package; a temperature sensor; a first circuit element including an oscillation circuit that causes the vibrating element to oscillate and generates an oscillation signal that is temperature-compensated based on the temperature sensor, the first circuit element being housed in the inner package; and a second circuit element fixed to the outer package and including a frequency control circuit that controls the frequency of the oscillation signal.

This invention relates to a method for measuring the stability margin of a constant-temperature hot-wire anemometer based on in-situ open-loop frequency characteristics, belonging to the field of fluid measurement and automatic control technology. The method disclosed in this invention includes the following steps: S1. Connecting an ultra-low frequency low-pass filter to the closed-loop circuit to form an in-situ open-loop system with a DC closed loop and an AC open loop; S2. Injecting a sweep frequency excitation signal E at the bias circuit. stimu And measure the output response E of the amplifier circuit. a By comparing the amplitude ratio and phase difference of the two, the open-loop frequency response G of the system under actual operating conditions of the hot wire is obtained. open (jω); S3. According to G open (jω) Obtain the phase margin of the system and determine its stability. This invention proposes a new method for measuring the stability margin of a constant-temperature hot-wire anemometer, transforming the complex system stability problem into a measurable and analyzable open-loop frequency characteristic stability margin problem, providing a direct and reliable engineering basis for the circuit design of constant-temperature hot-wire anemometers.

The invention relates to the technical field of industrial heat treatment equipment control, in particular to a heat treatment furnace safety control system based on a cloud platform. The multi-dimensional state sensing module is used for collecting real-time physical field data of an industrial controlled object; the signal orthogonal decomposition module is used for decoupling the original state data set into a low-frequency control signal flow and a high-frequency characteristic signal flow, and transmitting the high-frequency characteristic signal flow to a remote computing platform; the state reconstruction module is used for resolving a theoretical state value at the current moment and constructing a virtual sensor observation state; the dynamic envelope generation module is used for calculating a residual error between a theoretical state value and real-time physical field data and generating a dynamic security envelope threshold value and a confidence coefficient attenuation coefficient; and the self-adaptive safety judgment module is used for generating a final safety execution threshold value and executing safety interlocking control on the industrial controlled object. According to the method, the sensitivity of capturing the abnormal working condition in the heat treatment process is improved, and the problem that the static threshold value easily generates false alarm or missing alarm under the complex variable working condition is solved.

The application discloses a lightning impulse grounding grid frequency characteristic analysis method, system, device and medium, including: obtaining initial sample data; using the sample and a preset test frequency set to construct at least two different structure rational function interpolation models, and calculating the output residual thereof in the test frequency band; determining the target frequency point with the maximum modeling uncertainty according to the residual, calling the moment method to supplement high-precision response samples at the point; based on the updated sample set, constructing a diagonal or near-diagonal form rational interpolation model, and judging whether the prediction error of the model at the target frequency point is lower than a preset convergence threshold; if the convergence condition is not met, returning to the multiple model construction step, reiterating using the current sample set until the error meets the standard, and finally outputting the grounding grid frequency response characteristics covering the lightning impulse frequency band. The application realizes efficient analysis of the grounding grid frequency characteristics under lightning impulse, and effectively reduces the time used for analyzing the grounding grid frequency characteristics under lightning impulse.

The invention relates to the technical field of construction site management, in particular to a highway construction site Internet of Things positioning and tracking system which comprises a fundamental frequency calculation module, a parameter generation module, a central frequency generation module, a central frequency calculation module and a central frequency calculation module. The fundamental frequency calculation module collects engine rotating speed and angular speed signals and calculates engine vibration fundamental frequency by combining ignition factors. The dynamic filtering module is used for configuring the weighting coefficient as a difference equation parameter, blocking bandwidth energy through convolution filtering and generating a purification angular velocity; the trajectory tracking module is used for calculating the purification angular velocity and a zero deviation value, calling a Runge-Kutta algorithm for integral generation of a course angle, and generating a position coordinate in combination with a driving speed. According to the method, the vibration fundamental frequency is inversely calculated by collecting the rotating speed of the engine, the blocking bandwidth is dynamically constructed according to the interference frequency, the frequency characteristic is mapped to be a difference equation coefficient, vibration noise is accurately stripped, course drift is eliminated, and it is ensured that the positioning coordinates matched with the actual track are output.

The invention provides a method for improving PT residual voltage frequency measurement accuracy based on rotation vector characteristics, and relates to the technical field of generator set rotation speed measurement. The method comprises the following steps: acquiring a three-phase voltage alternating current signal through a generator end PT; processing the three-phase voltage signal to obtain projections of a voltage rotation vector on alpha and beta static coordinate axes; frequency characteristics are extracted based on projection and voltage amplitude and can be realized through direct calculation or a phase locking link; performing low-pass filtering on the frequency characteristic direct current quantity; a generator speed is calculated based on the filtered frequency and provided to a governor. According to the method, the limitation that a traditional PT residual voltage method only depends on zero crossing point information is broken through, frequency characteristics are extracted through a complete voltage sequence, alternating current signal filtering distortion is avoided through direct current filtering, high measurement precision and high anti-interference capacity can still be kept under the low-speed working condition, the problems that an existing speed measurement method is insufficient in precision and weak in anti-interference capacity are effectively solved, and the method is suitable for popularization and application. And reliable guarantee is provided for safe and stable operation of a unit.

The application discloses a kind of cable identification device and method based on dual-mode current detection, it is related to cable identification technical field.The technical problem to be solved is that existing cable identification method needs to operate on both sides of cable, and it is difficult to implement and inefficient on site.The device of the present application comprises characteristic signal generator, current signal acquisition module and automatic control system;Characteristic signal generator is used to apply adjustable frequency sinusoidal wave characteristic signal to one side of cable;Current signal acquisition module is used to collect the response signal generated by the signal excitation;Automatic control system is communicatively connected with the two, controls signal output and analyzes response signal data, and identifies target cable by judging whether the corresponding frequency characteristics are contained in response signal.The present application can complete identification only by operating on single side of cable, greatly improving the safety and efficiency of identification work.

The application provides a cable accessory fault positioning method and system. The method comprises the following steps: collecting reflection signals of a linear frequency modulation signal reflected at multiple impedance discontinuous points in a cable accessory; arranging all the reflection signals into a reflection signal sequence; selecting a first reflection signal in the reflection signal sequence as a selected signal; identifying bubble migration caused by insulation interface discharge at a reflection position corresponding to the selected signal according to amplitude-frequency characteristics of a nonlinear component in the selected signal; correcting an air gap of a next reflection signal in the reflection signal sequence based on the bubble migration, taking the air gap corrected signal as a new selected signal, repeating the above steps until the last reflection signal in the reflection signal sequence is corrected; and tracing and positioning a fault accessory on the cable according to the linear frequency modulation signal and each air gap corrected reflection signal. The method can eliminate the interference of the gas generated by the discharge at the insulation interface on the reflection signal.

The invention discloses a method for analyzing time-frequency characteristics of collision vibration by using a segmented B-spline wavelet collocation method, which comprises the following steps of: (1) establishing a dynamic equation for wavelet discretization, discretizing a dynamic control equation of a collision-vibrator system by using a 4-order B-spline wavelet basis function, and establishing a nonlinear algebraic equation set about a wavelet coefficient; (2) carrying out segmented iterative solution on the time domain, dividing the whole time domain into a plurality of sub-time periods which are connected in sequence, and carrying out iterative solution on the nonlinear algebraic equation set in each sub-time period to obtain a global wavelet coefficient; and (3) analyzing the time-frequency characteristics, and directly calculating energy distribution based on the wavelet coefficient to realize time-frequency joint characterization. The invention aims to provide a method which can fuse solution of system response and extraction of time-frequency characteristics in a unified mathematical framework, and realizes high-precision time-frequency joint characterization by directly solving wavelet coefficients, thereby overcoming inherent defects of an existing two-step method.

In a wireless power transfer apparatus, a characteristic adjuster has a frequency characteristic that causes, in a power transfer mode from at least one power transmission unit to a power receiving apparatus, a resonant power transmission circuit to have a resonance frequency that substantially matches an operating frequency. The reactance of a power transmission coil has a reference value in the power transfer mode. The frequency characteristic of the characteristic adjuster causes, in a power non-transfer mode from the at least one power transmission unit to the power receiving apparatus, a reactance of a power transmission coil to become an adjusted value that is higher than the reference value.

The application discloses a kind of garden plant health condition detection and early warning system based on spectral analysis, including adjustable frequency excitation light source, fluorescence detector, quadrature phase-locked demodulation module, phase frequency characteristic analysis module, early warning control unit and early warning output terminal, adjustable frequency excitation light source emits broadband sweep frequency modulation perturbation excitation light, quadrature phase-locked demodulation module executes operation filtering natural background stray light to the electric signal collected, phase frequency characteristic analysis module extracts characteristic relaxation frequency parameter when absolute phase delay parameter reaches forty-five degrees phase angle, early warning control unit sends instruction lock frequency and applies saturated light flash pulse, system calculates dynamic apparent electron transfer rate parameter, and according to temperature drift compensation baseline, executes double tolerance threshold comparison determination plant physiological stress state.The application avoids the defect of detection frequency band misplacement, eliminates the interference of strong background light and air temperature fluctuation, realizes the multi-dimensional joint early warning of early physiological stress.

A control system includes a storage that stores a computational model of a reference response profile representing a frequency characteristic of a reference state of a control target corresponding to a first command, and circuitry configured to calculate a first actual response profile representing a frequency characteristic of an actual state of the control target having responded to the first command. The circuitry is further configured to acquire an error between the reference response profile and the first actual response profile, and cause a controller to output, to the control target, a second command that is based on a frequency at which the error is greater than a threshold. Additionally, the circuitry is configured to calculate a second actual response profile representing a frequency characteristic of an actual state of the control target having responded to the second command, and update the computational model based on the second actual response profile and the reference response profile.

The invention relates to a method for detecting a hairspring or a hairspring blank arranged as a hairspring, the hairspring having to have at least one preset oscillation frequency, the method comprising the following steps: a. applying a time-varying vibration excitation to the hairspring or the hairspring blank to cover a preset frequency range; b. determining at least one characteristic of the oscillation frequency of the hairspring or the hairspring blank, such as a resonance peak, during the vibration excitation in the preset frequency range; c. providing the oscillation frequency characteristic determined in step b to a prediction machine to determine the stiffness of the hairspring or the hairspring blank and / or to determine whether a dimensional correction of the hairspring or the hairspring blank is required to achieve the preset oscillation frequency.

A bearing damage detection system includes a rotation sensor that detects rotation of a rolling bearing and outputs a rotation signal, a rotation fluctuation extraction section that extracts rotation fluctuation of the rolling bearing from the rotation signal and generates a rotation fluctuation signal, a frequency analysis section that performs frequency analysis on a waveform of the rotation fluctuation signal and derives a frequency characteristic, a peak intensity calculation section that derives a peak intensity corresponding to bearing damage from the frequency characteristic, and a damage detection section that detects bearing damage of the rolling bearing based on the peak intensity. The rotation fluctuation extraction section derives a waveform of the rotation fluctuation signal from which various noises are removed.

A kind of transmission equipment intelligent monitoring system and method based on noise feature analysis, through the method, expert can input the sound evaluation information heard from console, the sound evaluation value of expert corresponds to the state of specific reduction mechanism, the loudness and frequency characteristic of noise signal output by spectrum analyzer as input layer, the sound evaluation value of expert as output layer, mapping relationship between the two is established through data accumulation and neural network algorithm. Through the database of abnormal noise experts as a reference, warning is found by comparing similar abnormal noise data, ensure that noise meets the standard, through the noise evaluation of experts and neural network algorithm, the timbre can be evaluated, and then the specific type of fault can be judged. Moreover, the influence of on-site noise on sound signal collection is excluded, and the accuracy of machine detection is further improved.

The present application relates to a kind of vibration isolation device low-frequency transfer characteristic test system and test method, belong to spacecraft vibration reduction field.A kind of vibration isolation device low-frequency transfer characteristic test system, comprising: disturbance source simulator, vibration-isolated component, spacecraft simulation cabin, cabin unloading device, vibration-isolated component unloading device, suspension device, mass center alignment component and micro-vibration measuring device;Wherein, the disturbance source simulator is installed on the side plate of spacecraft simulation cabin, and the spacecraft simulation cabin is hung on the suspension device by the cabin unloading device;The vibration-isolated component is used to be set on the vibration isolation device to be tested, and is hung on the suspension device by the vibration-isolated component unloading device;The mass center alignment component is installed on the bottom plate of the spacecraft simulation cabin;The micro-vibration measuring device is used to test the micro-vibration parameter of different positions and the frequency characteristic of test system.

The invention provides a water pump intelligent monitoring control system and an application method thereof. In the method, a control system firstly extracts a mechanical noise component corresponding to a real-time rotating speed from initial baseline data by utilizing the relevance between the rotating speed and mechanical noise, and then constructs a baseline noise template to obtain mechanical noise interference during normal operation of a water pump. And the control system subtracts the baseline noise template from the original acoustic vibration signal to obtain a residual signal containing impurity impact information. And then the control system carries out continuous wavelet transform on the residual signal, and a generated time-frequency energy distribution diagram can identify the time node and frequency characteristics of the impact event so as to realize positioning of the impact event. And finally, the control system calculates the impact event rate and the average impact energy value in a preset statistical time window, and quantifies the progressive accumulation process of blockage. According to the method, the technical problem that early blockage cannot be identified by fixed threshold alarm is relieved, and the timeliness of fault prediction is improved.