61 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.

The invention relates to the field of metallurgical casting blank monitoring, and provides a method and a system for non-contact online monitoring of a solidification end point position and a blank shell thickness, the method comprises the following steps: S1, carrying out vibration measurement on the surface of a casting blank by adopting a non-contact monitoring method to obtain an original vibration signal of the casting blank in a continuous casting process; s2, converting the original vibration signal from a time domain to a frequency domain through fast Fourier transform processing to obtain a vibration spectrum; s3, comparing the obtained vibration spectrum with the vibration spectrum of the casting blank of the same model in a standard database, and determining the position of the solidification end point of the casting blank; and S4, according to the obtained position of the solidification terminal point, in combination with a solidification heat transfer model, the blank shell thickness of the casting blank at each position before the solidification terminal point is determined. According to the method, a new way is provided for online, dynamic, non-contact and nondestructive detection of the continuous casting solidification process, reliable reference is provided for parameter optimization of the pulling speed, cooling, electromagnetic stirring, soft reduction and the like, and finally accurate control over the quality of the continuous casting billet is achieved.

The disclosure features methods that include obtaining a vibrational spectrum of a solution in a biological manufacturing system, analyzing the vibrational spectrum using a first chemometrics model to determine a value of a first quality attribute associated with the solution, analyzing the vibrational spectrum using a second chemometrics model to determine a value of a second quality attribute associated with the solution, and adjusting at least one parameter of a purification unit of the biological manufacturing system based on at least one of the values of the first and second quality attributes.

The present disclosure provides methods and systems for label-free de novo sequencing of an analyte via vibrational spectral signatures. The system may include a sequence identification service, such as a machine learning model trained to receive vibrational spectral signature inputs and to output identifying sequence information. The system may comprise a chip, comprising an array of non-uniform features (e.g., resonators or a nanogap) for concentrating incident light at the analyte for detection of vibrational spectral signatures.

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 invention discloses a high-temperature and high-pressure temperature field measurement method based on low-resolution ultraviolet absorption chromatography, which comprises the following steps: selecting electron transition of an ultraviolet band NO or OH as an absorption spectrum measurement object according to the temperature of a temperature field to be measured, and selecting a vibration band of the measurement object according to the concentration and size conditions of the temperature field to be measured, determining a wavelength range to be measured; selecting a wide-spectrum light source and a low-resolution spectrometer as a light source and a detector required by absorption spectrum measurement respectively; an absorption chromatography light path network is established, each light path uses the selected wide-spectrum light source and the low-resolution spectrometer, absorption spectrum measurement of measurement objects is carried out on all the light paths, the temperature of each spatial position is obtained through calculation of absorption spectrum signals collected by all the light paths, and temperature field reconstruction is completed. Accurate absorption spectrum temperature measurement under high-temperature and high-pressure conditions can be realized, and accurate measurement of a high-temperature and high-pressure temperature field is realized by combining a chromatography reconstruction 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 discloses a seat assembly road spectrum generation method and device, and the method comprises the steps: obtaining a sample vehicle parameter, and setting a vehicle road surface driving test condition; vibration information at the seat assembly is collected based on the preset road condition, the preset speed and the preset time of driving of the test sample vehicle; performing data processing on the acquired vibration information to obtain effective data; according to the low-frequency vibration simulation requirement of the test bench, setting a sampling frequency, and re-sampling effective data to obtain a processed time domain signal; performing Fourier transform on the time domain signal to obtain a power spectrum frequency domain signal, and generating a seat assembly road spectrum database based on the power spectrum frequency domain signal; according to the method, the assembly bench test vibration spectrum collection iteration process is made to be streamlined and standardized, the repeatability and consistency of evaluation and test results are improved, support is provided for the performance evaluation test accuracy of the seat assembly, and the customer satisfaction is improved; through data acquisition, data interception, frequency setting and parameter optimization, road spectrum data time domain signals are converted into frequency domain signals which can be used by a seat rack, the road surface excitation state is perfectly restored, and the accuracy and timeliness of the test are improved.

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.

Method for monitoring the condition of a machine of a machine system (200), in particular a wind turbine, comprising the steps: - Provision of a time series of measured natural vibration spectra of the machine system (200) (S1), - Recording of a deformation parameter in at least one monitoring time interval (S2), wherein the deformation parameter is characteristic for a deviation of the measured natural frequency spectra from a reference natural frequency spectrum of at least one reference machine system, - Acquisition of a noise parameter for at least one monitoring time interval (S2), wherein the noise parameter is characteristic of the noise of the measured eigenvibration spectra, and - Determination of the machine state from the deformation parameter and the noise parameter (S4).

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.