952 results about "Vibration response" patented technology

The invention relates to the technical field of aircraft structure detection, and discloses an aircraft structure crack intelligent identification method based on deep learning. The method comprises the following steps: acquiring original vibration response signals and electromagnetic field distribution data on the surface and inside of an aircraft structure in parallel through a multi-source sensor network; synchronously processing the data by using a multi-scale convolutional neural network, and extracting time-frequency domain abnormal fluctuation features and space magnetic field distortion features; constructing a cross-modal correlation model, analyzing a topological dependency relationship of the two types of features through a graph attention mechanism, and generating a fused damage sensitive feature vector; inputting the vector into a pre-trained deep belief network to obtain a probability distribution mapping relation for different crack types; and according to the mapping relation, carrying out adaptive weighted fusion on original multi-sensor data, inhibiting environmental noise and structural background interference, and separating and reconstructing an accurate three-dimensional morphology map of the target crack. According to the method, multi-source data information can be effectively fused to improve the accuracy of aircraft structure crack identification.

The invention discloses a pre-twisted damper fatigue life prediction method for an extra-high voltage ground wire, and particularly relates to the technical field of power transmission line vibration prevention. Collecting multi-source vibration and environment data, and constructing a vibration characteristic time sequence; amplitude, frequency and strain energy are extracted based on the multi-frequency vibration response, and a multi-frequency collaborative vibration model is established; obtaining a damper structure and material parameters, establishing a finite element model, coupling the finite element model with a vibration model, and simulating local stress response; a Rainflow counting method and a Miner damage criterion are adopted to construct a fatigue damage factor distribution matrix; predicting the residual fatigue life of the damper based on the damage evolution trend, and evaluating the replacement opportunity; according to the method, accurate fatigue life prediction and optimal replacement strategy recommendation of the pre-twisted damper under complex working conditions can be realized, and the method has high precision, high adaptability and engineering practicability.

The invention discloses a large-model-based steel bar engineering quality detection method, system and equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring vibration response data and three-dimensional point cloud data of a to-be-detected reinforcement project; inputting the vibration response data into a pre-trained vibration characteristic analysis model to obtain a stress distribution map and a stress transmission path, and performing segmentation processing on the three-dimensional point cloud data along the stress transmission direction to obtain segmented point cloud data; based on the segmented point cloud data, extracting morphological characteristics of each section of reinforcing steel bar in the to-be-detected reinforcing steel bar project, and establishing a stress-geometry coupled digital twinborn model according to the stress distribution map and the morphological characteristics; performing dynamic mapping on the digital twinborn model and a pre-calibrated BIM design model, and determining steel bar deformation parameters of the stress abnormal region; and based on the steel bar deformation parameters, generating a quality detection report of the to-be-detected steel bar project. By implementing the technical scheme provided by the invention, the accuracy of reinforcing steel bar engineering quality detection can be improved.

The invention relates to the technical field of fan defect detection, in particular to a fan blade inspection method based on an unmanned aerial vehicle, which comprises the following steps: acquiring static basic data of a fan; constructing a blade reference model based on the static basic data of the fan, and collecting dynamic vibration response data according to a preset short-time dynamic vibration excitation rule; identifying a blade high-risk area according to the dynamic vibration response data, and generating a layered surrounding route in combination with a blade reference model; the unmanned aerial vehicle is controlled to collect blade multi-angle images according to the layered surrounding route, the blade multi-angle images are processed to recognize surface defects, and visual confidence is generated; and mapping the dynamic vibration response data to a blade reference model by using a space-time alignment model, extracting power spectral density characteristics of corresponding positions, calculating a damage index by fusing visual confidence, and outputting an inspection report. The objective of the invention is to solve the technical problem that blade internal damage is difficult to identify in a static inspection mode.

The invention discloses a loss tuning method of a power transformer, which is applied to a transformer body sleeved with a winding and comprises the following steps: applying scanning current excitation containing fundamental waves and harmonic waves to the winding, synchronously acquiring a body vibration signal and converting the body vibration signal into a frequency spectrum; extracting a formant from the frequency spectrum, matching the formant with a theoretical electromagnetic force wave and a structure inherent frequency library, and identifying a coupling formant to be optimized; aiming at each formant, installing a vibration exciter in a corresponding area, sending out an anti-phase periodic pulse force, and dynamically and finely adjusting a pulse force parameter by monitoring a vibration response in real time and taking equivalent mechanical impedance minimization as a target; when the optimal damping state is achieved, the vibration exciter output rod is locked, and static pre-tightening force is formed; and after all formants are adjusted and optimized in sequence and the prestress is locked, final pressing and fixing of the transformer body are completed in the state that the pretightening force is kept. According to the invention, the dynamic loss source of the individual transformer can be actively inhibited and cured before assembly and curing, the operation loss and noise are effectively reduced, and the structural stability is improved.

The invention provides a vibration signal space-time reconstruction method based on a multi-modal condition diffusion model, and relates to the technical field of vibration signal reconstruction, and the method comprises the steps: firstly collecting structure vibration response through multiple sensors, constructing a multi-dimensional vibration signal matrix, and automatically recognizing a space continuous missing region and a time random missing region; performing coarse reconstruction on the missing region by adopting self-adaptive multi-scale interpolation so as to recover the basic trend and frequency band characteristics of the signal; a pseudo-missing mask is further applied to complete data, a training sample is constructed through a self-supervision strategy, and the model is guided to learn spatio-temporal correlation features and missing modes; in a training stage, a diffusion model is used as a generation framework, Gaussian noise disturbance is applied to a missing region, four types of condition embedding of time, space, trend and frequency domain are introduced in a denoising inversion process, signal periodicity, multi-sensor space coupling, low-frequency change and a physical frequency spectrum structure are respectively described, and the noise is reduced; and high-fidelity signal reconstruction under multi-modal information joint constraint is realized.

The invention discloses a subway depot upper cover building vibration response prediction method based on deep learning, and the method comprises the steps: constructing a feature library containing vibration signals and working condition data, generating enhanced data through a mechanical model, and fusing the enhanced data into a data set; a mixed deep learning model embedded with physical prior is constructed, and training and dual-objective parameter optimization are carried out; a prediction result is output after working conditions of real-time data are recognized through the lightweight model; parameters are finely adjusted through regular incremental learning, and transfer learning adaptation is carried out when working conditions suddenly change; verifying precision and rationality, and adjusting the weight of a regular term or suggesting to add a sensor; according to the method, measured data sparseness is made up by enhancing data fusion; the double-branch architecture overcomes the deep nonlinear mapping problem, and physical constraints are prevented from violating physical rules; the incremental learning reduces the cost, and the transfer learning solves the time-varying vibration capture problem; precision is improved through closed-loop verification, accurate real-time prediction of vibration response is achieved, and safety and comfort of a building are guaranteed.

The invention discloses an intelligent quality inspection system for medicinal empty capsules, particularly relates to the field of intelligent detection, and comprises a multi-dimensional optical characteristic acquisition module, a dynamic thermodynamic response analysis module, a near infrared spectrum component inversion module, a multi-source data fusion decision module and a self-adaptive feedback optimization module. Omnibearing nondestructive detection of the capsule is realized through non-contact multispectral imaging and vibration response analysis, traditional destructive sampling loss is thoroughly avoided, and the multisource data fusion module integrates optical texture features, mechanical frequency domain energy density and near infrared spectrum inversion values based on the D-S evidence theory, so that the detection accuracy is improved. And the self-adaptive optimization module dynamically adjusts an optical wavelength weight, a mechanical sweep frequency range and a spectrum modeling parameter by applying reinforcement learning, is self-adaptive to fluctuation of different batches of gelatin materials and environmental interference, remarkably reduces a misjudgment rate and ensures continuous and stable operation of a production line.

The invention discloses an optical cable fitting fatigue damage detection method and system, and relates to the technical field of power transmission line state monitoring, and the method comprises the following steps: S1, constructing a wind field and structure coupling observation baseline, obtaining a full-time-domain vibration response signal of an optical cable fitting in a non-uniform wind field environment, generating a phase consistency distribution map, and obtaining a phase consistency distribution map; establishing a corresponding relation between the multi-path reflection source group and the time correlation sequence as a traceable reference for phase analysis; and S2, based on the phase consistency distribution map, performing causal beam demixing processing, performing arrival time difference densification calculation and curvature spectrum separation analysis on each sound wave propagation path, and extracting crack propagation pointing data. According to the method, through wind field-structure coupling observation, path unmixing, phase regression and error checking, multi-path propagation recognition and correction are achieved, crack propagation topology is reconstructed, polarization rotation and a phase suppression mechanism are combined, and direction recognition stability and detection adaptivity are improved.

The invention discloses a submarine pipeline scour-vibration response analysis method based on a cross-scale coupling framework. The method comprises the following steps: establishing a multi-physics field coupling model according to geographical and structural information of a pipeline layout area and initializing the multi-physics field coupling model; marine environment data are obtained through real-time monitoring, the model is imported for scouring dynamic deduction, and a scouring boundary data set is generated. And reconstructing a multi-physics field solving environment, and forming a real-time physics solving environment package. After the model is updated, pipeline vibration response is analyzed, and a vibration data set is obtained. And performing fatigue damage analysis, deducing a flow guide field disturbance coefficient, updating the model again, performing next time step coupling calculation, and finally obtaining a full-period coupling analysis data set. And evaluating the pipeline operation safety situation based on the data set, and generating and pushing a safety report. Various physical field effects on the submarine pipeline in the marine environment are comprehensively considered, the safety of the submarine pipeline is evaluated more comprehensively, and cross-scale coupling analysis between the scouring effect and the vibration effect is achieved.

The invention relates to the technical field of intelligent detection, and discloses a building quality evaluation method and system based on concrete nondestructive testing and a storage medium. The method comprises the steps that a piezoelectric ceramic sensor array is arranged to collect micro-vibration response signals, and an original vibration data set is obtained; extracting an energy distribution coefficient of each frequency band by using a wavelet packet decomposition algorithm, and constructing a damage feature vector matrix; establishing a physical constraint neural network model, and outputting a damage variable time sequence; fusing the damage variable with ultrasonic and rebound data, and calculating comprehensive strength and damage degree indexes; and calculating the remaining service life by using a time sequence prediction algorithm, and generating an evaluation report. According to the method, the technical problem that the existing concrete nondestructive testing technology cannot realize microstructure damage evolution dynamic monitoring and residual life prediction is solved, and the accuracy of building quality evaluation and the scientificity of predictive maintenance decision are improved.

The invention provides a tunnel backfill compactness estimation method and device, a terminal and a medium. The method comprises the steps that vibration response information and real-time settlement information are obtained; performing feature extraction on the vibration response information to obtain response frequency spectrum information; inputting the response frequency spectrum information and the real-time settlement information into various machine learning models to obtain various backfill compaction degree estimation data; and performing fusion processing on the multiple backfill compactness estimation data through a Bayesian triangular cap fusion method to obtain fusion compactness estimation data. According to the method, the Bayesian triangular cap fusion method is utilized to integrate the backfill compactness estimation data based on the machine learning algorithm, the final fusion compactness estimation data is generated, and the prediction precision of the tunnel backfill compactness is improved. The efficiency of tunnel backfill compactness detection is improved, the detection period of the tunnel backfill compactness is shortened, and continuous automatic monitoring of a large-range tunnel backfill layer is achieved.

An inspection method is provided during which a head of an inspection scope is inserted into an interior of a powerplant. The head of the inspection scope includes an actuator. The powerplant includes a component located within the interior of the powerplant. The head of the inspection scope is abutted against a surface of the component within the interior of the powerplant. The head of the inspection scope is preloaded against the surface of the component using a preload device located outside of the interior of the powerplant. Vibrations are induced in the component using the actuator. A vibratory response in the component excited by the vibrations is measured using a sensor to provide sensor data.

The invention belongs to the technical field of control detection, and particularly relates to a laser cutting machine cutting control method and system.The laser cutting machine cutting control method comprises the following steps that S1, frequency sweeping excitation is applied to a plurality of preset grid node positions of a laser cutting machine workbench, and vibration response data of a cutting head is collected; a dominant pole and a zero point of a vibration transfer function of each grid node are identified and extracted, spatial distribution is fitted by using a non-uniform rational B-spline surface, and a spatial model of continuous mapping between a cutting head position and a vibration transfer function parameter is established; s2, decomposing a to-be-processed path into a plurality of path infinitesimal segments, and calculating a preliminary feed-forward compensation instruction of each path infinitesimal segment based on a space model and a zero-phase error tracking control algorithm; according to the invention, the contour error caused by structural vibration and non-linear factors is reduced, the processing precision and the cutting surface quality of the laser cutting machine in a full working range are improved, and the forming effect of a complex contour at a high speed is improved.

The invention provides a structural engineering bearing capacity field detection method, and belongs to the technical field of structural engineering detection.The structural engineering bearing capacity field detection method comprises the steps that a multi-axial acceleration sensor and a strain gauge array are installed on the surface of a to-be-detected structural member, and an intelligent loading device is adopted to apply incremental loads; a mobile data acquisition terminal is utilized to acquire vibration response data and strain response data in real time, modal parameters are extracted based on a frequency domain analysis method to establish a load-modal parameter relation curve, the bearing capacity of a component is analyzed and calculated, a graph theory shortest path algorithm is adopted to optimize load transmission path analysis, and the load transmission path analysis is optimized. The bearing performance of the component is accurately evaluated through the structural response prediction model based on the Transform architecture, the technical integration of multi-dimensional detection data fusion, intelligent loading control, quantitative bearing capacity evaluation and accurate performance prediction is realized, and the technical problem of insufficient detection precision of the bearing capacity of the structural component is solved.

The invention relates to the technical field of aero-engine rotor vibration tests, in particular to an aero-engine rotor unsteady-state thermally induced vibration test system which comprises a rotor experiment table, an air inlet and exhaust system, a lubricating oil system, a protection system and a heating system. The rotor experiment table comprises a first supporting system, a second supporting system, a rotor outer protection casing, a gas compressor disc, a gas compressor sealing disc, a turbine disc, a turbine front sealing disc, a front shaft diameter, an inter-disc drum, a rear shaft diameter, a first squirrel-cage elastic support, a ball bearing, a second squirrel-cage elastic support and a rolling rod bearing. The first supporting system is composed of a first squirrel-cage type elastic support and a ball bearing, meanwhile, an air inlet is formed in the first supporting system, and the ball bearing in the first supporting system is connected with the front shaft diameter in an interference fit mode. Rotor unsteady-state characteristics considering heating conditions are finally created, and vibration response and durability of a wheel disc structure under the unsteady-state thermal load condition are studied in combination with test conditions such as temperature vibration and the like.

The invention discloses a vibration monitoring and displacement identification method for a towering steel structure based on machine vision, and relates to the technical field of towering steel structures. Comprising the following steps: S1, visual acquisition and reference calibration: arranging visual acquisition equipment in the height direction and the circumferential direction of the towering steel structure according to mechanical characteristics of a vertical stiffness mutation region and a dynamic response sensitive part of a geometric asymmetric distribution characteristic of the structure; a three-dimensional coordinate system is established based on a structure installation reference surface, fixed reference monitoring points are arranged in a tower foot symmetric area and a mast antenna root, three-dimensional coordinate data of the reference points are synchronously collected, the collection range completely covers a node concentration area and a key stress part of a structure transparent area, and a continuous image sequence of the structure surface is captured in real time; the resolution and the sampling frequency of the visual acquisition equipment are determined according to the inherent frequency of the structure and the vibration response characteristics, and calibration is completed through reference point coordinates after the equipment is installed; s2, carrying out image preprocessing and feature enhancement; S3, carrying out feature point extraction and trajectory tracking; S4, carrying out vibration displacement calculation and twin fusion; and S5, carrying out multi-source verification and structural state linkage treatment.

An inspection method is provided during which a head of an inspection scope is inserted into an interior of a powerplant. The head of the inspection scope includes an actuator and a sensor. The powerplant includes a component within the interior of the powerplant. The head of the inspection scope is abutted against a surface of the component. Vibrations in the component are induced using the actuator. A vibratory response excited by the vibrations is measured using the sensor to provide measurement data. The measurement data is filtered to provide filtered data, and the filtering includes detrending the measurement data.

The invention relates to a site micro-vibration attenuation test measuring point determination method and system, belongs to the technical field of vibration test, and solves the problem that vibration test measuring point arrangement depends on vibration source load accuracy or artificial experience in the prior art. The method comprises the following steps: determining a basic measuring point based on a target site parameter, obtaining an actual measurement vibration response, and calculating an actual measurement response transfer ratio; establishing an initial finite element model of the target site, and applying a preset load to the initial finite element model to obtain an initial finite element calculation result; according to the basic measuring points, corresponding model calculation points and predicted vibration responses are extracted, and predicted response transfer ratios are calculated; and performing model parameter updating by using the actually measured response transfer ratio and the predicted response transfer ratio, obtaining a basic finite element model, generating a vibration transfer form curve, obtaining vibration transfer characteristics, and determining the number and the positions of the measuring points. The micro-vibration transmission characteristics are accurately determined without depending on the vibration source load, and the number and the positions of the vibration attenuation test points are reasonably formulated.

The invention discloses a tuned mass vibration damper with controllable damping, and relates to the field of vibration control of offshore wind power generation equipment structures. The mass damping unit is arranged in a suspended mode, the clamping ring is coaxially arranged, the electromagnetic damping units are evenly distributed in the circumferential direction of the clamping ring, and the electromagnetic damping units are connected with the mass damping unit through winding ropes which are arranged in a radial mode to form a multidirectional synergistic composite damping system; the mass damping unit generates reverse inertia force in vibration to restrain movement of the tower and drives the electromagnetic damping unit to act at the same time, the generator is driven to generate electromagnetic damping through the one-way bearing and the speed increaser, and lossless reset is achieved through the torsion ring. The device is integrated with an energy recovery unit, vibration energy is converted into electric energy to be stored, real-time regulation and control of damping force, omni-directional vibration response and energy feedback are achieved, and the vibration reduction efficiency and the energy utilization rate are remarkably improved.

The invention discloses a blade vibration monitoring sensor layout optimization method and system and a storage medium. The method comprises the steps that S100, geometric constraints of sensor layout and strategy constraints of vibration evaluation are acquired; s200, generating a sensor phase sequence based on geometric constraints; s300, determining a plurality of vibration orders to be analyzed; s400, for each vibration order, constructing a coefficient matrix of vibration response estimation based on the sensor phase sequence and the total number of the periods to be calculated; s500, for each vibration order, calculating a conditional number of a product of a coefficient matrix and a transposed matrix thereof; s600, selecting the maximum value of the condition number as an evaluation parameter of the current sensor phase sequence; s700, under the geometric constraint, adjusting the sensor phase sequence based on the phase adjustment step length, and executing the steps S300-S600 again; and S800, selecting a minimum value in all evaluation parameters, and outputting a sensor phase sequence corresponding to the minimum value as an optimization result.

The invention discloses a disturbance observation driven minimum control synthesis adaptive vibration control method and system. The method comprises the following steps: establishing a nominal model of a structure based on a vibration response signal of the structure; carrying out fusion processing on the nominal model of the structure and the vibration response signal, constructing a disturbance observation framework, estimating various disturbances borne by the structure in real time, and generating a disturbance estimation value; combining the disturbance estimation value with a control law of a minimum control synthesis algorithm in a feedforward compensation mode to construct a driving control instruction; and generating an acting force according to the driving control instruction to adjust the vibration of the structure. According to the method, a cooperative control architecture with strong anti-interference capability is constructed by fusing a disturbance observation technology and a minimum control synthesis algorithm, and disturbance and uncertainty are effectively suppressed while vibration is controlled, so that the vibration control precision is improved.

The invention provides a bridge health monitoring and intelligent control method and system based on machine learning, and the method comprises the steps: carrying out the distributed sensing data collection of a bridge structure, generating a structure monitoring data set, carrying out the spatial-temporal feature extraction, and obtaining a vibration response feature sequence and a traffic load feature sequence of the bridge structure; performing correlation analysis on the two sequences, generating a structural damage sensitive feature matrix, performing damage evolution trend prediction based on the structural damage sensitive feature matrix, generating damage development probability distribution of the bridge key component, and generating a dynamic traffic control instruction according to the damage development probability distribution. The dynamic traffic control instruction comprises a vehicle passing parameter dynamically adjusted based on a damage degree quantitative index, and sending the dynamic traffic control instruction to a traffic management system. According to the invention, the accuracy of bridge health monitoring and the dynamic adaptability of control measures can be improved.

The invention discloses a flexible riser vibration response characteristic analysis method, and relates to the technical field of ocean engineering. According to the method, a flexible riser vibration model is established based on a vibration theoretical model and a fluid control equation for vibration analysis, a theoretical time domain response curve of the flexible riser is obtained through MATLAB calculation, and then a flexible riser three-dimensional simulation model is established in an ANSYS Workbench integrated simulation platform. According to the method, a flexible riser three-dimensional simulation model is constructed, material constitutive parameters, boundary conditions and load application of the flexible riser three-dimensional simulation model are configured, then simulation is performed in an ANSYS Workbench integrated simulation platform by using the flexible riser three-dimensional simulation model, bidirectional fluid-solid coupling analysis is performed by coupling a Fluent flow field system and a Transient Stratum module, the radial displacement time history of the flexible riser under a preset working condition is obtained, and the radial displacement time history of the flexible riser under the preset working condition is calculated. And extracting resonance characteristics of the flexible riser. According to the method, the vibration response characteristics of the deep-sea flexible riser under the influence of internal and external fluids in the service process are accurately obtained, and a foundation is laid for guiding the structural stability of a deep-sea operation system.

The invention discloses a stay cable vibration recognition method and system based on unmanned aerial vehicle video and image correction. The method comprises the steps that S100, a dynamic response video of a stay cable under natural excitation is shot through an unmanned aerial vehicle; s200, performing semantic segmentation on a stay cable region in the video image to obtain a clear stay cable pixel region; s300, pixel displacement tracking is carried out on the inhaul cable target area and the peripheral fixed reference point area, and time sequence displacement data containing inhaul cable vibration response and unmanned aerial vehicle disturbance components are extracted; s400, geometric correction of the image sequence is realized, and overall jitter caused by attitude change of the unmanned aerial vehicle is eliminated; s500, extracting an intrinsic mode component; identifying a common-mode disturbance component by comparing modal features of the two, and stripping from the inhaul cable response; and S600, carrying out identification and early warning on abnormal vibration behaviors such as loosening, strand breaking and vibration excitation abnormity. And high-precision and automatic monitoring of the vibration state of the stay cable is realized through a technical closed loop from video acquisition to abnormal early warning.

The invention provides a construction method for installing a large-span special-shaped beam curved template system, and belongs to the technical field of building construction. According to the construction method, accurate three-dimensional modeling is conducted on the shape of a special-shaped beam through a special-shaped curved surface parametric modeling algorithm, and material prefabrication is guided; eight oscillation excitation devices and twelve vibration monitoring devices are optimally arranged by using experimental design and a graph theory analysis method to form a dynamic monitoring network, vibration response data are analyzed in real time by using a wavelet transform monitoring algorithm, and the energy ratio of each frequency band is calculated as a quality evaluation index. A game optimization model is established, and according to different ranges of energy ratios, the support spacing is automatically adjusted, a back ridge fixing mode is combined or a supporting system is reinstalled, so that a comprehensive quality assurance system of accurate geometric modeling-dynamic state monitoring-intelligent parameter adjustment is constructed. The technical problem that the installation quality of a large-span special-shaped beam curved template system is difficult to guarantee is solved.

The invention provides an aircraft component fault intelligent diagnosis and maintenance control system, and relates to the technical field of aircraft component diagnosis. A stall modeling module of the system establishes an aeroelastic coupling equation for quantifying stall behaviors on the basis of collected pressure disturbance data of an air inlet flow field of an air compressor and blade row vibration response information. The elastic response deduction module discretizes the equation through a state conversion operator and then embeds the equation into a graph neural network node update function. The graph embedding coupling recognition module recognizes blade tip gap mutation behaviors induced by local stall and time sequence precursor characteristics of the blade tip gap mutation behaviors by using a node state evolution trajectory output by the graph neural network, and constructs a surge precursor evolution path. And the early warning output module carries out instability trend judgment on the surge precursor evolution path, and outputs a maintenance suggestion and an early warning identifier aiming at a blade fracture fault, so that the structure failure risk caused by the surge of the gas compressor is effectively predicted, and the accuracy and timeliness of fault diagnosis of aircraft parts are remarkably improved.

The invention provides a crimping quality online detection method and system based on acoustic emission signal analysis, relates to the technical field of industrial detection, and solves the technical problems that an existing detection method is not sensitive to early defects and is insufficient in adaptability under complex working conditions. The method comprises the following steps: applying mechanical excitation to the crimping structure, exciting the crimping structure to generate vibration response, and synchronously collecting a vibration response signal and an acoustic emission signal; wherein the mechanical excitation represents sweep frequency excitation or pulse excitation generated by a piezoelectric vibration exciter or an impact hammer so as to excite a plurality of co-frequency offset vibration modes of the crimping structure; calculating the resonant frequency of the crimping structure based on the vibration response signal; calculating frequency offset characteristic parameters according to the resonant frequency based on an inversion method of a physical model; calculating acoustic emission signal characteristic parameters based on the acoustic emission signals; and identifying the type and severity of the crimping defect by utilizing a D-S evidence theory and combining the frequency offset characteristic parameters and the acoustic emission signal characteristic parameters.

The invention belongs to the technical field of wind power generation, and discloses a monitoring and sensing system and method based on a large wind driven generator. The method aims to solve the problem of load prediction deviation of a downwind unit caused by wake flow interference in a fan group array effect. According to the method, the wake flow propagation dynamic topological graph is constructed by obtaining the real-time operation state data of the fan group, and the space influence range and the intensity distribution of the wake flow are accurately represented. And based on the blade turbulence separation feature point set and the wake flow topological graph, identifying a wake flow interference sensitive area of the downwind generator set, analyzing a dynamic gain effect of wake flow interference through a vibration response transfer function, and generating a real-time load prediction correction model. The model is combined with prediction deviation adaptive optimization, and the prediction precision is ensured. Meanwhile, a fan group dynamic risk assessment model is constructed, the operation scheduling strategy is optimized, and the wake flow interference influence is reduced. According to the method, the load prediction accuracy, the unit operation safety and the overall efficiency of the fan group are improved.