52 results about "Vibration spectra" patented technology

The invention provides a hydrogen energy storage equipment leakage fault early warning method and system based on deep learning, and the method comprises the steps: collecting the multi-source sensing data of hydrogen energy storage equipment in real time, constructing a multi-dimensional feature matrix, building the nonlinear mapping of pressure fluctuation and gas concentration through a bidirectional interaction network, and carrying out the early warning of the leakage fault of the hydrogen energy storage equipment. And performing spatial modeling on the temperature gradient and the vibration spectrum to generate a fusion feature tensor. And then, inputting the fused feature tensor into a spatio-temporal reasoning model, predicting equipment leakage and energy loss, and outputting a leakage probability cloud picture and an energy loss vector. And an entropy sudden change area is identified based on an energy loss vector, when the high-density leakage area and the entropy sudden change area are overlapped in a continuous detection period, a multi-stage early warning signal is triggered, a leakage source thermodynamic diagram and a pressure balance parameter set are generated, a self-adjusting system is activated to dynamically correct the valve opening degree, network weight is updated, and a closed-loop control link is formed. The early warning accuracy and the response speed of the leakage fault of the hydrogen energy storage equipment are improved.

The invention relates to the technical field of control and adjustment, in particular to a steam turbine fault diagnosis system based on multi-parameter fusion monitoring, which is characterized in that a quantum hybrid sensing module is used for establishing a picosecond-level space-time reference through entangled photon pair distribution, and unifying a time sequence label of multi-source heterogeneous data; the hypergraph feature extraction module loads the coefficient to a vibration measurement point vertex attribute channel, dynamically calculates a heat conduction hyperedge weight according to a rotor eccentricity inversion value, aggregates temperature field, vibration spectrum and magnetic domain features in a space-time hypergraph which retains physical topology, outputs a cross-scale aligned fusion feature tensor, and outputs a vibration measurement point vertex attribute channel; generating a diagnosis feature vector to drive a multi-scale twin experience certificate; and the federation decision module triggers a load reduction instruction according to the microscopic crack cloud picture to inhibit thermal stress sudden change, and meanwhile, the feature representation precision is improved through cloud federation optimization hyperedge weight parameters. According to the method, the problem of characterization distortion caused by time sequence asynchronization and scale mismatch of heat and machine coupling data is solved.

The present invention relates to the technical field of real-time correction of dynamic deformation measurement errors based on Beidou satellite navigation, and in particular to a method for monitoring deformation of pumped-storage dams based on Beidou positioning. This method addresses the technical problem of pseudo-fluctuations in monitoring data caused by the frequency domain aliasing of Beidou signals' multipath time-varying errors and the structural real displacement in a high-dynamic environment. Millimeter-level real-time solution is achieved through the construction of a multimodal collaborative monitoring network and dynamic feature analysis. The method includes: deploying a dual-frequency Beidou receiver array and environmental sensors, integrating Beidou observation data, reservoir water pressure gradients, foundation vibration spectra, and three-dimensional geological structure data, constructing a robust solution model constrained by a geological model, outputting confidence intervals for deformation parameters, and suppressing outliers through robust estimation; employing a dynamic time warping algorithm to match a historical operating condition library, combining a closed-loop feedback mechanism to dynamically calibrate warning thresholds and reversely optimize the monitoring network. The present invention effectively suppresses multipath time-varying errors.

According to the iron ore alkali dissolution-electrolysis intelligent collaborative optimization system and the dynamic purification method provided by the invention, artificial intelligence and a metallurgical process are fused, and full-process dynamic regulation and control are realized. The system comprises: 1, an intelligent collaborative optimization module, which dynamically and collaboratively optimizes dissolution-electrolysis process parameters (NaOH concentration, liquid-solid ratio, Fe < 3 + > concentration and current density) based on reinforcement learning (DQN algorithm), predicts an impurity dissolution trend and adds a specific inhibitor in a gradient manner in combination with machine learning, and inhibits generation of Al2O3 / SiO2; the equipment health management module realizes corrosion / blockage two-factor accurate early warning (the accuracy is greater than or equal to 92%) through deep learning analysis of a corrosion image and a vibration spectrum, and is linked with a maintenance decision; the energy-resource coupling module integrates waste heat recovery (greater than or equal to 85%) and a multi-effect evaporation regeneration technology, so that the energy consumption per ton of iron is reduced to 2.9 GJ, and the alkali consumption is less than or equal to 0.95 kg; and 4, a self-adaptive process platform: dynamically updating the model based on a federated learning framework, and adapting to a complex ore source with Fe greater than or equal to 35% and Al2O3 less than or equal to 8%. The embodiment verifies that the system improves the hematite dissolution rate to 94%, reduces the non-planned shutdown of equipment by 40%, reduces the comprehensive cost by 14%, and is suitable for efficient and clean utilization of low-grade iron ores.

The present invention discloses a high-temperature and high-pressure temperature field measurement method based on low-resolution ultraviolet absorption tomography. The method comprises: selecting the electronic transition of NO or OH in the ultraviolet band as the absorption spectrum measurement object according to the temperature of the temperature field to be measured, and selecting the vibration spectrum band of the measurement object according to the concentration and size conditions of the temperature field to be measured to determine the wavelength range to be measured; selecting a broadband light source and a low-resolution spectrometer as the light source and detector required for the absorption spectrum measurement, respectively; establishing an optical path network for absorption tomography, wherein each optical path uses the selected broadband light source and low-resolution spectrometer, and the absorption spectrum of the measurement object is measured on all optical paths. The temperature of each spatial position is calculated from the absorption spectrum signals collected by each optical path, and the temperature field is reconstructed. The present invention can realize accurate temperature measurement by absorption spectrum under high-temperature and high-pressure conditions, and realize accurate measurement of high-temperature and high-pressure temperature fields by combining with a tomography reconstruction algorithm.

The invention relates to the technical field of vehicle assembly vibration fatigue tests, in particular to a road load spectrum-based accelerated random vibration spectrum determination method, which comprises the following steps of: selecting i-circle data of each characteristic road surface under full-load, half-load and no-load working conditions as original data of accelerated random vibration spectrum calculation; calculating an impact response spectrum and a fatigue damage spectrum of the i-circle data of each characteristic pavement; respectively accumulating the fatigue damage spectrum statistical values of the three working conditions; packaging the maximum values of the impact response spectrums under the three working conditions; according to a fatigue damage accumulation theory, calculating a fatigue damage spectrum of the total target mileage according to the number of cycles of three working conditions; packaging the maximum value of the impact response spectrum of the whole circle of characteristic pavement under the three working conditions to obtain the maximum value of the overall target mileage impact response spectrum; synthesizing an accelerated random vibration spectrum by using the fatigue damage spectrum of the total target mileage according to a damage equivalence principle; and finally, carrying out ERS calculation on the generated accelerated random vibration spectrum, and checking the correctness and rationality of the accelerated random vibration spectrum.

The invention discloses an SMA-based active vibration reduction method and device, and relates to the field of shape memory alloys. Comprising the steps that an active vibration reduction system provided with a control center and a plurality of electrically-connected SMA driving microwires is built; receiving the vibration signal, detecting the resistance change of the SMA driving microfilament in the active vibration reduction system in real time, and generating a time-strain curve of the SMA driving microfilament based on the resistance-frequency-strain correlation of the SMA driving microfilament; based on a time-strain curve, determining vibration spectrum information of the vibration signal and feeding back the vibration spectrum information to a control center; wherein the vibration spectrum information comprises vibration amplitude, vibration frequency, phase and wavelength; and based on the vibration spectrum information, the control center controls to use pulse electric heating to drive the SMA driving microwire, a compensation vibration spectrum opposite to the vibration spectrum information is generated, and active damping is achieved. According to the invention, based on SMA driving microwires, vibration spectrum monitoring and damping active control are realized by combining high-frequency strain / stress control under a confrontation structure system and combining a feedback control algorithm.

The present application relates to fine particle sensing technology, and particularly relates to a microcavity vibration spectrum system and method for measuring inherent vibration spectrum of fine particles. The microcavity vibration spectrum system comprises an inherent vibration excitation light path unit and a microcavity detection light path unit; the inherent vibration excitation light path unit is sequentially provided with a pulsed light source, a vibrating mirror, an objective lens and a particle to be measured; and the microcavity detection light path unit is sequentially provided with a tunable laser light source, an adjustable attenuator, a polarization controller, a coupling optical waveguide, an optical microcavity, a photodetector and an oscilloscope. The present application can realize precise measurement of sound waves caused by particle vibration of mesoscale particles and biological particles with inherent vibration frequency in the sub-megahertz-gigahertz frequency range.

Apparatus and method for measuring a vibration spectra of a sample using microscope-based Laser Doppler Vibrometer (LDV), where photothermal actuation uses pulsed light to drive vibrations without contact with the sample.

The application discloses a kind of sensor chip high reliability high accuracy test system and method for extreme environment, belong to sensor test technical field.The test method includes multiple physical field coupling environment loading, automobile working condition excitation injection, anti-interference synchronous acquisition, anti-drift real-time error compensation, dynamic performance degradation analysis and drift immunity test report generation steps.Anti-drift real-time error compensation is monitored by distributed auxiliary sensor array in real time temperature gradient kurtosis, vibration spectrum entropy and electromagnetic shielding effectiveness, freezes CNN convolution layer weight after triggering drift flag, only carries out incremental federal compensation to fully connected layer, and introduces the physical constraint correction compensation output based on FEM simulation.The application can effectively inhibit the mismatch of compensation coefficient caused by environmental drift, improve the long-term stability and precision of sensor chip test under extreme environment, meet the AEC-Q100 full life cycle reliability verification requirement.

A system (100), apparatus (110) and method for estimating a remaining useful life of at least one bearing are provided. The method includes receiving a request from a source (115, 125, 130) to analyze defects in a bearing, determining a vibration spectrum of the bearing from received operational data, monitoring impacts of defects on the bearing over a period of time based on the determined vibration spectrum, determining a characteristic value for which impacts of defects on the bearing are above a threshold range from the vibration spectrum, determining an impact force during operation of the at least one bearing based on the determined characteristic value and one or more parameters obtained from a virtual bearing model, determining a remaining useful life of the bearing based on the determined impact force during the period of time, and generating a notification on an output device indicating the remaining useful life of the bearing.

This application provides a cavity-enhanced mid-infrared photothermal vibration measurement system and method, relating to the field of photothermal vibration spectrum detection of materials, aiming to improve the accuracy and sensitivity of detection. The measurement system includes a cavity-enhanced substrate, a mid-infrared laser, a laser vibrometer, and a lock-in amplifier. The cavity-enhanced substrate includes a substrate and an asymmetric Fabry-Perot resonator. The asymmetric Fabry-Perot resonator includes a reflective layer, an intermediate dielectric layer, and a layer to be tested, sequentially stacked on the substrate. The mid-infrared laser applies mid-infrared laser light to the layer to be tested, causing the layer to generate a photothermal vibration signal. The laser vibrometer detects the photothermal vibration signal and converts it into a detection electrical signal. The lock-in amplifier extracts the detection electrical signal to determine the photothermal vibration spectrum of the layer to be tested. The ratio of the thickness of the intermediate dielectric layer to the thickness of the layer to be tested ranges from 0.8 to 10. The refractive index of the material of the layer to be tested is less than the refractive index of the material of the intermediate dielectric layer, but greater than the refractive index of air.

The present application relates to a kind of based on self-assembled monolayer interface heat conduction regulation and control physical characteristic engineering construction method.The method comprises the following steps: constructing interface heat transport simulation system;Molecular dynamics simulation is carried out to interface heat transport simulation system, obtains physical dynamic information matrix;All physical dynamic information matrix is subjected to data statistical operation operation, obtains first physical characteristic dataset;The vibration spectrum physical information of the self-assembled monolayer obtained is subjected to peak searching operation and vibration spectrum overlapping area calculation, obtains second physical characteristic dataset and third physical characteristic dataset;Physical characteristic dataset is summarized, and finally constructs based on self-assembled monolayer interface heat conduction regulation and control physical characteristic engineering.Compared with prior art, the present application realizes the construction of physical characteristic engineering based on the interface heat conduction characteristics of self-assembled monolayer, and has important significance for carrying out data-driven self-assembled monolayer interface heat conduction characteristics regulation and control design.

The present application relates to a kind of numerical control machine tool health diagnosis method and system based on vibration spectrum coupling, belong to the field of fault diagnosis.Therein, the method includes obtaining original electric energy by energy self-adaptive capture and converting into stable electric energy, obtain coupling coefficient matrix;Based on coupling coefficient matrix, stability evaluation is carried out, and dynamic stability margin is obtained;Based on dynamic stability margin, early fault risk prediction model is constructed, and fault development time prediction value is obtained;Based on three-order resonance modal coupling coefficient, fault coupling frequency combination is screened out, dynamic parameter compensation is carried out based on fault coupling frequency combination, and targeted parameter compensation amount is obtained;Based on targeted parameter compensation amount, corresponding parameter is compensated, and global knowledge evolution is carried out.The present application realizes vibration spectrum coupling analysis, energy self-capture, dynamic stability evaluation and knowledge evolution mechanism, realizes sensitive capture of early fault, predictive maintenance and adaptive compensation, and improves the intelligent level of machine tool health management.

The present invention relates to the technical field of predictive maintenance of industrial equipment, and discloses a method and system for predicting the health of industrial equipment based on multi-source data synchronization. The method comprises: synchronously collecting vibration spectra, temperature gradients, and current harmonics in response to MOM system instructions; reorganizing the vibration spectrum based on spindle period slicing; calculating the cross-correlation delay offset between current harmonics and temperature gradients and translating the temperature data; integrating multi-source data according to the spindle slicing time window to generate a synchronization signal matrix; inputting a wear degradation model to generate a health decline index; and triggering a maintenance response when the index exceeds the dynamic threshold of the MOM system. The present invention solves the problems of asynchronous fusion distortion of multi-source data and insufficient adaptability of static strategies through vibration phase synchronization, delay compensation, and dynamic threshold decision-making, thereby improving the accuracy of equipment status prediction and maintenance efficiency.

The invention relates to a dynamic closed-loop energy efficiency management method and system for a numerical control machine tool, and belongs to the field of energy efficiency management. The method comprises the steps that original electric energy and total generation power are obtained through energy self-adaptive capture, and the original electric energy is converted into stable electric energy; vibration signals are obtained through stable electric energy, vibration spectrum entropy mutation detection is carried out based on the vibration signals, and an effective machining period is obtained; obtaining effective machining energy based on the effective machining time period; establishing an adaptive communication protocol according to the effective processing energy; and performing optimization based on an adaptive communication protocol to obtain optimized total energy consumption and reference total energy consumption in a preset period, and obtaining an energy efficiency improvement net value in the preset period. According to the method, the machining state recognition precision is improved through vibration spectrum entropy sudden change detection, self-powered sensing is achieved through multi-source energy collection, intelligent communication is triggered based on the battery state and energy efficiency change, and therefore accurate, real-time and energy-saving energy efficiency monitoring and optimization are achieved without external intervention.

The application discloses an assembly detection method, device, equipment and system of a voltage inspector, and the method comprises the following steps: acquiring a standard vibration spectrum and excitation source information when a test voltage inspector interface module is normally connected with a single cell of a test electric pile; inputting the excitation source information into the current voltage inspector interface module to obtain a current vibration spectrum when the current voltage inspector interface module is connected with the single cell of the current electric pile; and judging whether the connection between the current voltage inspector interface module and the single cell in the current electric pile is normal according to the standard vibration spectrum and the current vibration spectrum. Through the comparison of the vibration spectra, it can be quickly and accurately detected whether the interface connection between the voltage inspector and the single cell of the electric pile is abnormal, the assembly inspection time is reduced, and the risk of electric pile testing and electric pile running caused by poor contact of the voltage inspector is avoided.

This invention relates to the field of highway pavement inspection technology, specifically a method for detecting the friction performance of highway pavements based on intelligent sensors. The method includes: collecting vibration spectra, surface texture depth sequences, and environmental meteorological readings using a multimodal intelligent sensor array deployed on the highway pavement to form a raw pavement dataset. A sparse coding algorithm optimized based on the projection characteristics of tribological feature subspaces is used to extract vibration feature vectors. These vectors are then reconstructed in three dimensions and fused with temporal features to obtain texture feature maps and pavement environmental state vectors. Multiple features are input into a multi-source fusion network to generate a comprehensive state representation. Finally, a deep convolutional neural network model decodes and outputs estimated friction coefficients and spatial distribution maps. Based on this, risk level assessments and maintenance recommendations are generated and uploaded to a management platform. This method accurately preserves friction-related features, enables collaborative analysis of multi-source data, fully reflects the spatial distribution of pavement friction, and improves the accuracy and completeness of the detection results.

The present invention relates to a monitoring device (10) arranged to be operably connected to a medicament delivery device (12), said medicament delivery device (12) comprising a manually operated movable dose activation element (20), said monitoring device (10) comprising an electronic circuit (42), said electronic circuit (42) comprising an optical sensor (68), wherein said optical sensor (68) is positioned in relation to said dose activation element (20) so as to detect a manual operation of said dose activation element (20) from an initial position; said electronics circuit further comprising a vibration sensor (70), wherein said vibration sensor (70) is positioned in relation to said medicament delivery device so as to detect specific vibration spectra produced by the medicament delivery device when said dose activating element (20) is operated, wherein said electronic circuit (42) comprises computing elements capable of correlating the information from the optical sensor (68) with the information from the vibration sensor (70) when said dose activation element (20) is operated in order to register when a correct dose has been set.

The invention provides an optical cavity enhanced mid-infrared light thermal vibration measurement system and method, relates to the field of material photo-thermal vibration spectrum detection, and aims to improve the accuracy and sensitivity of detection. The measurement system comprises an optical cavity enhanced substrate, an intermediate infrared laser, a laser vibration meter and a lock-in amplifier. The optical cavity enhancement base comprises a substrate and an asymmetric Fabry-Perot resonant cavity, and the asymmetric Fabry-Perot resonant cavity comprises a reflecting layer, an intermediate dielectric layer and a to-be-detected object layer which are sequentially stacked on the substrate. The mid-infrared laser acts mid-infrared laser on the to-be-detected object layer, so that the to-be-detected object layer generates a photo-thermal vibration signal. The laser vibration meter detects a photo-thermal vibration signal and converts the photo-thermal vibration signal into a detection electric signal. And the lock-in amplifier extracts the detection electric signal to determine the photo-thermal vibration spectrum of the to-be-detected object layer. And the ratio of the thickness of the intermediate dielectric layer to the thickness of the to-be-detected object layer is 0.8-10. The refractive index of the material of the to-be-detected object layer is smaller than the refractive index of the material of the intermediate dielectric layer and larger than the refractive index of air.

This invention discloses a fault diagnosis method for crane maintenance management, relating to the field of crane equipment operation and maintenance technology. It includes collecting a multi-source sensor data sequence consisting of vibration spectrum of the hoisting mechanism, wire rope tension fluctuations, and temperature changes at hinge points within the crane's operating cycle. The multi-source sensor data sequence is time-synchronized and outlier-removed to generate a standardized synchronization data matrix. The synchronization data matrix is ​​then fed into a hierarchical fault feature extraction process, outputting degradation feature vectors for key components and anomaly pattern identifiers. The remaining effective working range length of the components is calculated using the degradation feature vectors, and the fault initiation time point is located using the anomaly pattern identifier. These two types of information are merged and encoded to generate a maintenance trigger signal, which is then pushed to the crane control terminal display interface. This method achieves standardized organization and hierarchical feature mining of multi-source operating data, quantifies the service status of components, and identifies the fault initiation time, providing a standardized status basis for crane maintenance management.

The invention discloses a screen module fault original positioning method and system. The method comprises the following steps: spraying a quantum dot solution on key nodes of a to-be-detected screen module; collecting a vibration spectrum of the screen module by using a laser Doppler vibration meter; the acoustic impedance Za of the screen module is obtained through analysis; the electrical impedance Ze, measured by the three-dimensional impedance vector field, of the screen module is utilized, and the acoustic impedance Za and the electrical impedance Ze are combined to obtain acoustic-impedance joint confidence; the first layer is used for judging the fluorescence intensity threshold value of each key point quantum dot, the second layer is used for carrying out acoustic-impedance joint confidence evaluation on the acoustic-impedance joint confidence model, the third layer is used for outputting a maintenance strategy of reinforcement learning, a decision tree model is constructed, and fault positioning is carried out on the screen module through the decision tree model. According to the invention, the fault is positioned through the change of the quantum dot response state of each key node, and the method has the advantages of high efficiency and high accuracy.

A kind of test system of aircraft surface structure gap and seal piece flow-induced sound vibration, wherein the test system is substantially a longitudinally extending multi-pipe segment closed structure, the multi-pipe segment closed structure is mounted on a support, and includes gas supply section, noise elimination and flow stabilizing and pressure stabilizing section, test section and gas release section connected in sequence;Wherein the test section includes sample mounting part, the test sample container of the sample mounting part is detachably connected, the pressure and temperature in the test sample container are controlled;The test section further includes microphone and vibration meter.The system can simulate aircraft cruising speed flow field and can simulate temperature and pressure difference environment when aircraft is running, obtain flow-induced noise spectrum, flow-induced vibration spectrum and transfer characteristics of typical structure gap and seal piece in simulated aircraft working environment, and key data in the field of civil aircraft vibration reduction and noise reduction control technology.

The invention provides a thermal power oil liquid quality evaluation method based on multi-source data fusion, and relates to the technical field of industrial data processing, and the method comprises the steps: obtaining multi-source heterogeneous data such as an oil liquid microstructure acoustic scattering spectrum, a thermodynamic entropy flow, a microscopic vibration spectrum, an external environment and an operation condition; a multi-scale degradation chain type fusion evaluation strategy is adopted, data time sequence evolution is dynamically captured, contribution weights are corrected, real-time self-adaptive evaluation of dynamic working conditions is achieved, and the accuracy and generalization ability of the model are remarkably improved; meanwhile, a degradation chain reaction risk index and driving factor weight distribution are generated, and a refined linkage control strategy including maintenance task, execution time, material personnel and equipment parameter adjustment is generated in combination with deep reasoning of a maintenance knowledge graph and historical records; and super-early warning, dynamic traceability and intelligent intervention are executed, and an evaluation result is converted into a structured instruction set capable of guiding operation and maintenance, so that the interpretability, operability and practicability of a decision are greatly improved.

This invention relates to the field of highway pavement inspection technology, specifically a method for detecting the friction performance of highway pavements based on intelligent sensors. The method includes: collecting vibration spectra, surface texture depth sequences, and environmental meteorological readings using a multimodal intelligent sensor array deployed on the highway pavement to form a raw pavement dataset. A sparse coding algorithm optimized based on the projection characteristics of tribological feature subspaces is used to extract vibration feature vectors. These vectors are then reconstructed in three dimensions and fused with temporal features to obtain texture feature maps and pavement environmental state vectors. Multiple features are input into a multi-source fusion network to generate a comprehensive state representation. Finally, a deep convolutional neural network model decodes and outputs estimated friction coefficients and spatial distribution maps. Based on this, risk level assessments and maintenance recommendations are generated and uploaded to a management platform. This method accurately preserves friction-related features, enables collaborative analysis of multi-source data, fully reflects the spatial distribution of pavement friction, and improves the accuracy and completeness of the detection results.

A system and method for detecting and mitigating aircraft propulsor faults uses deliberate speed perturbations of individual propulsors and analysis of resulting vibration spectra to identify problematic units. Distributed sensors monitor vibration across multiple propulsors. A propulsor operates at an adjusted speed different from the ensemble. Resulting vibration characteristics reveal if the adjusted propulsor is an anomaly source. Its unique signature emerges in the vibration frequency data. The system cycles propulsors through adjusted speeds, detects correlated frequency shifts, and isolates faulty units. Targeted mitigation then acts only on identified bad propulsors while others remain operational. This enables automated in-flight troubleshooting of vibration issues and pinpointed mitigation.

The present invention relates to a monitoring device (10) arranged to be operably connected to a medicament delivery device (12), said medicament delivery device (12) comprising a manually operated movable dose activation element (20), said monitoring device (10) comprising an electronic circuit (42), said electronic circuit (42) comprising an optical sensor (68), wherein said optical sensor (68) is positioned in relation to said dose activation element (20) so as to detect a manual operation of said dose activation element (20) from an initial position; said electronics circuit further comprising a vibration sensor (70), wherein said vibration sensor (70) is positioned in relation to said medicament delivery device so as to detect specific vibration spectra produced by the medicament delivery device when said dose activating element (20) is operated, wherein said electronic circuit (42) comprises computing elements capable of correlating the information from the optical sensor (68) with the information from the vibration sensor (70) when said dose activation element (20) is operated in order to register when a correct dose has been set.

This application provides a rapid fault triggering device and method for a cantilever structure sensor, belonging to the field of sensor technology. It includes a base plate, a mounting base, a mounting plate, and a collision clamp. The mounting base and mounting plate are vertically connected to the upper surface of the base plate. The mounting plate moves axially along the sensor under test. The collision clamp is mounted on the mounting plate. The sensor under test passes sequentially through the mounting base, the mounting plate, and the collision clamp. The collision clamp has a through hole for the sensor to pass through, the diameter of which is larger than the outer diameter of the sensor. The method includes mounting the sensor under test on the mounting base, mounting the collision clamp on the mounting plate, adjusting the position of the collision clamp and the gap between the through hole and the sensor; conducting vibration tests using the HB5830 test method and vibration spectrum; and swinging the collision test fixture under vibration using the cantilever structure to amplify the test magnitude through the collision effect, thereby achieving rapid fault triggering. This application significantly improves R&D efficiency and reduces time costs and experimental resource waste.

The invention discloses a seven-stringed plucked instrument timbre quantitative analysis method and system based on multi-mode voiceprint recognition, and innovatively realizes digital analysis of acoustic characteristics of a traditional musical instrument. The technical core comprises: 1) a multi-modal data acquisition device, which eliminates artificial playing differences through standard electromagnetic excitation (0.1-5N adjustable) and synchronous vibration / sound wave detection; 2) processing a time domain vibration spectrum (sampling rate of 192kHz) and space domain sound field distribution (64-channel beam forming) by using a double-flow deep network model, and outputting a 128-dimensional feature vector; and (3) a three-dimensional timbre space mapping algorithm is adopted, and abstract timbres are converted into quantifiable coordinates (such as vigorous degree 0-100 / brightness 0-100 / afternote 0-60s). The system is matched with a portable terminal and a cloud database, supports the functions of voiceprint comparison, value evaluation, maintenance suggestion and the like, and can be widely applied to the aspects of hacking process optimization, cultural relic identification and evaluation, non-missing digital protection, music teaching guidance and the like.