332results about How to "Improve spatial resolution" patented technology

The invention discloses a slope structure safety monitoring method and system based on a distributed sensing technology, and the method comprises the steps: carrying out the distributed monitoring of the surface and deep part of a slope, and obtaining monitoring data; data transmission is carried out on the monitoring data through a wireless network; preprocessing and analyzing the transmitted monitoring data to obtain a monitoring data set; according to the monitoring data set, a safety evaluation model of the slope structure is established, and slope surface displacement, deep stress and pore water pressure are comprehensively considered in the safety evaluation model; based on the safety evaluation model, obtaining a quantitative evaluation result of the slope safety state; and establishing a slope disaster early warning model, and performing trend analysis and threshold judgment on the quantitative evaluation result through the slope disaster early warning model to realize early warning and real-time early warning of the slope disaster. The monitoring method provided by the invention has the characteristics of distribution, multiple parameters, long-term stability and high reliability, can comprehensively sense the change of the slope safety state, and provides a reliable basis for disaster early warning.

The invention discloses a crop disease remote sensing monitoring and early warning system based on time sequence spectral information analysis, and relates to the technical field of agricultural disease and insect pest monitoring. Computer drawing software is utilized to divide a corn planting field in equal proportion, and sensors are deployed to monitor the growth environment change in each grid in real time and generate microenvironment data information; the method comprises the following steps: calculating a microenvironment difference index Xbd according to microenvironment data, identifying a microenvironment difference aggregation area and sending a risk analysis instruction, after receiving the risk analysis instruction, capturing related spectral data information of the microenvironment difference aggregation area by using an unmanned aerial vehicle and a multispectral sensor, and constructing a multispectral fluctuation coefficient Xgp by analyzing related spectral data, and comparing the calculated rust disease risk assessment index Zpg with a preset threshold W in combination with the microenvironment difference index Xbd and the trained risk assessment model, and obtaining corresponding grade early warning according to the rust disease risk degree.

The invention relates to the technical field of spectral analysis, and discloses a spectral analysis-based gas component detection method, device and equipment and a medium, the method comprises the following steps: carrying out axial scanning on a gas storage device to obtain hyperspectral image data; performing preprocessing and spectrum standardization on the hyperspectral image data to obtain preprocessed spectrum data; carrying out waveband selection on the preprocessed spectral data to obtain a characteristic waveband; performing abundance estimation on the characteristic wave band to obtain initial gas component content data; optimizing the initial gas component content data to obtain target gas component content data; and performing gas component anomaly detection on the target gas component content data to obtain a gas component anomaly detection report, thereby improving the accuracy of gas component anomaly detection.

The invention discloses a steel plate butt weld pseudo defect ultrasonic detection method, system and device and a medium, and relates to the technical field of weld detection, the method comprises the following steps: setting a plurality of detection areas on a steel plate butt weld based on acquired structure parameters and surface characteristic data of a to-be-detected steel plate; performing multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter by taking each detection area as a basic unit to obtain corresponding echo signal data; analyzing and identifying potential pseudo-defect signals, and calculating corresponding pseudo-defect characteristic values according to the pseudo-defect signals; taking each detection area as a basic unit, performing pseudo defect feature analysis according to the second detection parameters, and determining reliability evaluation data of pseudo defects; based on the pseudo-defect reliability evaluation data and the pseudo-defect characteristic value corresponding to each detection area, the pseudo-defect condition of the steel plate butt weld is analyzed, and a final weld quality comprehensive evaluation result is generated. According to the invention, the detection accuracy of steel plate butt weld detection is improved.

The invention relates to the technical field of remote sensing image processing, and particularly discloses a remote sensing hyperspectral image super-resolution fusion algorithm and system based on quaternion, and the method comprises the steps: employing a panchromatic image quaternion feature extraction module, a hyperspectral image quaternion feature extraction module and a self-attention fusion module, constructing a double-U-Net structure network based on a multi-scale residual link and a jump link; and inputting a panchromatic image and a low-resolution hyperspectral image, and calculating to obtain a high-spatial-resolution hyperspectral image. According to the method, a plurality of spectral channels of a hyperspectral image and high-resolution spatial information of a panchromatic image are embedded into four components of a quaternion, and spectral and spatial characteristics are modeled uniformly by means of algebra of the quaternion; and then feature extraction, fusion and reconstruction are carried out through a deep learning network, and finally a fusion image with both high spectral fidelity and high spatial resolution is generated, so that the spatial resolution of the hyperspectral image can be significantly improved, and the spectral consistency of the hyperspectral image can be maintained at the same time.

The invention discloses a rainfall prediction method and system for the Beijing, Tianjin and Hebei region, and relates to the technical field of rainfall prediction, and the method comprises the steps: obtaining multi-source data, carrying out the preprocessing of the data, extracting the core characteristics of the data, carrying out the dynamic rainfall modeling according to the core characteristics of the data, and simulating a rainfall evolution path; and constructing a rainfall prediction model, performing rainfall intensity prediction based on the rainfall evolution path, performing extreme weather early warning based on a prediction result, and generating a rainfall distribution diagram of a high-risk area. Through fusion of multi-source data, the generative adversarial network and spectral analysis, the spatial resolution of the data and the rainfall evolution prediction capability are improved, the real-time performance and the accuracy of rainfall prediction are improved in combination with dynamic rainfall modeling, a fractional order differential equation and a multiple regression model, and the prediction accuracy is improved. The rainfall prediction challenge under complex weather conditions can be effectively dealt with, and accurate prediction of rainfall intensity and extreme weather events is realized.

The invention discloses a transformer on-line monitoring and fault early warning system, and particularly relates to the technical field of power equipment monitoring, and the system comprises a signal collection module, a signal filtering module, a broadband focusing module, a signal complexity analysis module, a threshold self-tuning module, a fault early warning module and a fault positioning module. The signal acquisition module acquires operation data of a transformer in real time through a sensor network, the filtering module removes noise, and the broadband focusing module converts broadband signals into narrow-band signals, so that the resolution is improved; the signal complexity analysis module evaluates the signal complexity, and the threshold value self-tuning module dynamically adjusts the threshold value; the fault early warning module judges whether to trigger early warning based on the adjusted threshold value, and the fault positioning module determines the position of the partial discharge source through a cross positioning algorithm; according to the invention, the problem that the accuracy of early warning is affected due to the fact that a traditional fixed-threshold monitoring method is easy to generate false alarm or missing alarm can be solved, and operation and maintenance personnel can be helped to quickly determine the position of a fault source through cross positioning.

The invention discloses a virtual dynamic three-dimensional image fusion method and system based on pre-registration, and the method comprises the steps: obtaining a static three-dimensional image of a target region, and a dynamic three-dimensional CBCT image which at least comprises one respiratory cycle; performing breathing phase division on the dynamic three-dimensional CBCT image; obtaining a corresponding three-dimensional image frame on each phase node; registering the plurality of three-dimensional image frames obtained by division with the static three-dimensional image in sequence to obtain a single-frame deformation field; collecting breathing signals of a patient in real time during an operation; performing interpolation calculation on the single-frame deformation field based on the respiratory signal, and generating a complete deformation field in the whole respiratory cycle in real time; and applying the complete deformation field obtained by interpolation to the static three-dimensional image, so that the static three-dimensional image is virtually dynamic. Through a method of pre-registration of a pre-operative breathing phase node image and interpolation based on a real-time breathing phase in an operation, the calculation amount during real-time fusion in the operation is reduced, so that ultra-low-delay image fusion is realized.

The invention discloses a vehicle-mounted VR back-row entertainment method, and relates to the field of VR, and the method comprises the steps: processing image data transmitted by a controller through a DCT plate negative reflection plate lens, and generating aerial imaging data; reflecting a virtual image corresponding to the aerial imaging data by using a plane mirror to generate real image data; performing voice recognition processing on the input voice of the user to obtain voice control instruction data; acquiring image data of user gestures through an infrared sensor, and performing image recognition to obtain gesture control instruction data; generating interaction control data according to the three-dimensional coordinates in the real image data, the voice control instruction and the gesture control instruction; aiming at low image imaging precision in a vehicle-mounted VR entertainment system in the prior art, high-quality aerial imaging is generated by using a DCT plate negative reflection plate lens and a plane mirror, multi-modal interaction and the like are realized by adopting voice recognition and gesture recognition, and a vivid imaging effect is provided.

The invention provides a method, device and equipment for determining a buoyancy generation item of atmospheric turbulence kinetic energy and a storage medium, and the method comprises the steps: obtaining the wind speed at a plurality of moments through a wind measurement radar within a specified time length, and obtaining the buoyancy generation item of the atmospheric turbulence kinetic energy according to the wind speed at the plurality of moments; the dissipation rate and pulsation components corresponding to the wind speed in different coordinate axis directions are determined, a turbulence trend item, a shear generation item and a turbulence transmission item are determined according to the pulsation components corresponding to the different coordinate axis directions, and the wind speed is acquired by adopting a wind measurement radar, so that the spatial resolution and the data continuity of data are improved, and the detection range is expanded. And more accurate dissipation rate, turbulence trend term, shear generation term and turbulence transmission term are determined, so that the buoyancy generation term of the atmospheric turbulence kinetic energy can be more accurately deduced according to the dissipation rate, turbulence trend term, shear generation term and turbulence transmission term, and the accuracy of the buoyancy generation term is ensured.

The invention belongs to the technical field of image processing, and particularly relates to a remote sensing image super-resolution reconstruction method based on a degradation mechanism. Comprising the following steps: S1, constructing a degradation model, inputting a high-resolution remote sensing image into the degradation model, and obtaining a degraded image corresponding to the high-resolution remote sensing image; s2, constructing a super-resolution network, and inputting the degraded image into the super-resolution network to obtain a reconstructed image; s3, training the super-resolution network by using the joint loss function to obtain a trained super-resolution network; and S4, inputting a degraded image to be reconstructed into the trained super-resolution network to obtain a reconstructed super-resolution image. According to the method, the resolution of the remote sensing image is improved, the quality and processing efficiency of the image are remarkably improved, and the method has high practical application value.

The utility model discloses a transformer partial discharge detection device based on a quantum sensor. The transformer partial discharge detection device comprises a quantum detection module, a signal processing module, a control module, a power supply module, a communication module and a signal analysis module. The quantum detection module comprises a diamond NV color center sensor and a fluorescence detection unit; and the fluorescence detection unit outputs laser to the diamond NV color center sensor to obtain electron spin resonance information of the diamond NV color center sensor. According to the utility model, the diamond NV color center is used as the quantum sensor for partial discharge detection, and tiny partial discharge events in the transformer can be detected in real time in the early stage of partial discharge based on high sensitivity of the quantum sensor and simultaneous measurement of a plurality of physical quantities such as a magnetic field, an electric field, temperature and the like, so that the detection sensitivity is improved; abundant signal data is provided, and more time windows are provided for maintenance and fault prevention of power equipment; and the spatial resolution is high, so that the partial discharge generation position can be accurately positioned.

The invention discloses a high temporal-spatial resolution risk assessment method for agricultural non-point source pollution in a plain river network region. The method comprises the following steps: selecting an assessment region; dividing evaluation units; selecting an evaluation time period; basic data collection and necessary supplementary monitoring of an evaluation area; agricultural non-point source pollution in-river load accounting; evaluating the bearing capacity of the riverway on non-point source pollution; calculating evaluation indexes; carrying out risk grade delimiting; compiling a priority treatment area list; agricultural non-point source pollution control measures are implemented; and evaluating agricultural non-point source pollution prevention and control performance. The polder area and the irrigation and drainage area are used as agricultural non-point source pollution risk last-stage evaluation units, so that the spatial resolution of agricultural non-point source pollution risk evaluation is greatly improved; a monthly risk assessment method is provided, and the time resolution of agricultural non-point source pollution risk assessment is greatly improved; a land and water linkage evaluation index system is adopted, excessive adoption of weights is avoided, the index meaning is clear, and targeted accurate recognition of a key source area is achieved through mutual verification of different indexes.

The invention provides an insulating part defect identification method based on a synthetic aperture ultrasonic imaging technology, which belongs to the technical field of ultrasonic defect identification, and comprises the following steps: step 01, setting parameters of an ultrasonic transducer to enable the ultrasonic transducer to emit ultrasonic waves, and attaching the ultrasonic transducer to the surface of a detected insulating part; 02, connecting the ultrasonic sensor with an acquisition card, and acquiring real-time echo data by using acquisition software; step 03, importing the data into data processing software for data processing, and performing defect imaging by applying an imaging algorithm; and step 04, performing defect analysis and positioning on the formed ultrasonic image. According to the method, the accuracy, reliability and practicability of defect detection of the insulating part are remarkably improved, and more effective technical support is provided for quality control in the industrial field. Due to the automatic and intelligent characteristics of the system, the detection efficiency is greatly improved, the uncertainty caused by human factors is reduced, and the system has remarkable practical value and popularization significance.

The invention belongs to the technical field of hydraulic engineering, and provides a river section form measurement method and system, a storage medium and electronic equipment, and the method comprises the steps: collecting and processing data needed for measuring a river section form; extracting a waterline and a center line from data required for measuring the river section form; calculating a relative stability index of the section based on the center line and the waterline, and identifying a stable river reach in the river channel through the relative stability index of the section; dividing the stable river reach into a curved river reach and a straight river reach; giving elevation values to the waterline of the curved river reach and the waterline of the straight river reach by using data required for measuring the shape of the cross section of the river to obtain waterline elevation values; and measuring the river section form based on the waterline elevation value. According to the method, any section form of the river channel can be effectively constructed, the space-time limitation of measurement is broken, basic data support is provided for runoff monitoring, and an important basis is provided for large-scale flood process monitoring and water resource management decision.

The invention relates to the technical field of vehicle detection and identification, and discloses an expressway vehicle detection and identification method based on distributed optical fiber sensing. The method comprises the steps that when a vehicle runs on a detection road section, a distributed optical fiber sensor collects a sensing signal, and first data is generated after preprocessing; dividing all the extended feature information into a plurality of threshold categories based on a multistage binarization technology, marking the threshold categories for the extended feature information, and summarizing based on type labels to generate a feature data table; summarizing all the third data based on the type labels to generate a driving data table; performing data fusion on the feature data table and the driving data table to generate a comprehensive data table, and identifying the foundation type of the detected road section; and constructing a detection and identification model, inputting the extended feature information of the to-be-monitored vehicle into the detection and identification model, outputting vehicle information of the to-be-monitored vehicle, and completing detection and identification of the to-be-monitored vehicle. According to the invention, high precision, high efficiency and high reliability of highway vehicle detection and identification are realized.

The invention provides an ionosphere TEC prediction model integrating double mechanisms of self-attention and self-correlation, and belongs to the technical field of ionosphere delay prediction, and the model comprises a trend prediction module, a correlation analysis module and a sequence fusion module. Wherein the trend prediction module predicts the overall change trends of an ionized layer TEC sequence and space environment parameters by means of an autocorrelation operation mechanism; the correlation analysis module analyzes the mutual relation among the ionized layer TEC sequence, the space environment parameters and the longitude and latitude positions by using a self-attention mechanism; and the sequence fusion module performs further integration and optimization on the overall trend of the ionized layer TEC sequence by using the correlation information obtained by the correlation analysis module, and finally obtains an ionized layer TEC prediction result fusing the space environment and the latitude and longitude position information. According to the method, the spatial environment data and the longitude and latitude position information are fully utilized, and the accuracy of model prediction is greatly improved.

The invention discloses a surface feature information extraction method based on a hyperspectral and high-resolution remote sensing image, and relates to the technical field of remote sensing. The method comprises the following steps: acquiring a hyperspectral and high-resolution remote sensing image, and preprocessing the hyperspectral and high-resolution remote sensing image; cutting and fusing the preprocessed image to obtain a fused image; performing spectral analysis and wave band screening on the fused image to obtain first image data; performing image enhancement processing on the first image data to obtain a plurality of grayscale images; performing wave band synthesis on the plurality of grayscale images, and performing grid analysis and wave band screening to obtain second image data; performing threshold segmentation on the second image data, and performing grid surface turning to obtain a first vector; obtaining DEM data in a preset elevation range of the research area, and performing grid surface turning to obtain a second vector; and cutting the first vector according to the second vector to obtain a distribution vector result. According to the method provided by the embodiment of the invention, the extraction precision and reliability can be effectively improved.

The invention belongs to the technical field of watershed hydrological process simulation research, particularly relates to a distributed storage and hypersonic dynamic combination model construction method based on water and soil conservation measures, and solves the technical problems that an existing loess plateau region hydrological model is low in simulation precision and poor in applicability. Firstly, a research area is subdivided into a plurality of uniform grids through uniform grid division, and each grid represents different underlying surface features; the method comprises the following steps: carrying out an observation test on a typical field slope of a loess plateau to obtain observation data under different water and soil conservation measures, and determining a model parameter range in each grid under the water and soil conservation measures. According to the method, the rainfall-runoff process in each grid is linked with each other by combining a one-dimensional motion wave equation to form a complete distributed storage hyperdynamic combined model, the model structure can dynamically reflect runoff production mechanisms of different grid units, and the prediction capability of the model is improved.

The invention relates to the technical field of computed tomography, in particular to a CT imaging system and method based on a distributed micro-focus X-ray source, and the system comprises the distributed X-ray source provided with a plurality of micro-focuses, a detector, a scanning carrier, a control module and a data processing module. In the scanning process, the distributed X-ray source and the detector rotate around the rotation center relative to the object to be detected at the same time, the multiple small and micro focuses are sequentially subjected to beam outgoing according to the beam outgoing strategy so as to disperse heat dissipation, the peak power of the small and micro focus radiation source can be effectively improved, and the time needed by single CT scanning is shortened. Besides, by designing a beam outgoing strategy of the distributed X-ray source, sampling distribution of a plurality of small microfocuses can be optimized, sub-pixel-level image reconstruction is realized, and the spatial resolution is further improved. According to the system and the method, ultrafast high-definition CT imaging can be realized, and the problem that a traditional single-focus X-ray CT system is difficult to consider high spatial resolution and high time resolution at the same time is solved.

The invention discloses a defect detection method and equipment based on an NV color center, and relates to the technical field of nondestructive testing. Comprising the following steps: preprocessing detection data obtained by magnetic flux leakage detection based on a diamond NV color center, and filtering out abnormal signals; filtering and denoising processing is carried out on the preprocessed data; and judging a defect signal according to the processed data and calculating the depth and width of the defect. According to the method, the reliability and the accuracy of detection data are ensured by establishing data preprocessing and filtering and denoising processes, the signal quality is improved, and interference is reduced; nV color center detection is carried out based on the magnetized leakage magnetic field, grading processing is carried out on detection data, and a corresponding data processing algorithm is adopted, so that the spatial resolution and sensitivity of detection are improved; an evaluation system is established through defect depth and width parameters, and the detection efficiency is improved.

The invention belongs to the technical field of marine instruments, and particularly relates to an offshore real-time internal wave observation system and method based on three anchors, and the system comprises a three-anchor fixing frame system, a real-time internal wave observation system and a shore station terminal system. Wherein the real-time internal wave observation system is fixed in the three-anchor fixing frame system in a sliding connection manner, and the real-time internal wave observation system moves up and down along the three-anchor fixing frame system and cannot rotate in the horizontal direction under different sea surface heights, so that the stability of an observation environment is ensured; the real-time internal wave observation system is used for collecting real-time observation data and sending the real-time observation data to the shore station terminal system for processing; and the shore station terminal system is used for analyzing according to the received real-time observation data and detecting whether internal waves exist so as to judge whether to provide early warning. According to the invention, the complete measurement of the internal solitary wave in the ocean can be realized for a long time, the time resolution and the space resolution are very high, and good data are provided for the research of the internal wave.

The invention relates to alpha particle measurement equipment, method and device, a storage medium and a program product. The equipment is formed by surrounding a side wall of the equipment, a cavity top and a cavity bottom; a collector and a cathode are arranged in the cavity; the collector is arranged at the top of the cavity; the cathode is arranged at the bottom of the cavity; the collector is parallel to the cathode; the distance between the collector and the cathode meets a first preset distance; the collector comprises a plurality of first anode wires laid along a first direction and a plurality of second anode wires laid along a second direction; the distance between each first anode wire and each second anode wire in the third direction is a second preset distance, the distance between two adjacent first anode wires in the first direction is a third preset distance, and the distance between two adjacent second anode wires in the second direction is a fourth preset distance. By adopting the method, the accuracy of alpha particle measurement results can be improved.

The invention discloses a TGD-OFDR / OCC-BOTDR integrated multi-parameter sensing system and a working method thereof, and relates to the technical field of optical fiber sensors. The multi-parameter sensing system comprises a laser, an optical fiber coupler, an electro-optical modulator, an optical fiber circulator, an optical fiber Bragg grating, an acoustic optical modulator, an erbium-doped optical fiber amplifier, a random scrambler, a piezoelectric ceramic tube, a heating vessel, a delay optical fiber, a photoelectric balance detector, a filter and detector, a data acquisition card, a polarization controller, a direct-current power supply and a microwave source. An arbitrary waveform generator and the like. According to the invention, multiple parameters can be represented at the same time, the measuring speed is fast, and the sampling rate of the system can be effectively improved under the condition that sensing parameters are the same; the method has the advantage of high spatial resolution; the sensor has the advantages of high fusion and low cost, can realize simultaneous measurement of vibration and temperature / strain through single sensing, and is high in fusion and effective in cost control.

The invention provides an optical frequency domain reflectometer image signal denoising method and measurement method based on deconvolution. The denoising method comprises the following steps: converting reference and measurement signals of an OFDR (Optical Frequency Domain Reflectometer) into distance domain reference signals and measurement signals by adopting FFT (Fast Fourier Transform); dividing a scattering medium for measurement into a plurality of sections according to the spatial resolution of the OFDR, and converting distance domain reference and measurement signals of each section into time domain reference and measurement signals by adopting STFT (Short Time Fourier Transform); calculating a cross-correlation spectrum curve of each segment of corresponding time domain reference and measurement signals to obtain a cross-correlation two-dimensional image; autocorrelation is carried out on the time domain reference signal of each segment, and an autocorrelation two-dimensional image is obtained; taking a main lobe, corresponding to a cross-correlation peak, of each section in the cross-correlation two-dimensional image as a wavelength interception range of the section, and intercepting an image located in the wavelength interception range of the section from each section of the self-correlation two-dimensional image as a point spread function (PSF); and de-noising the cross-correlation two-dimensional image by adopting deconvolution according to the PSF. According to the invention, the problem that the OFDR cannot carry out image signal denoising based on deconvolution is solved.

The invention relates to the technical field of optical microscopic imaging, and discloses a scanning structured light microscopic imaging system and method based on a multi-focus diffraction-free light beam. Exciting light emitted by a laser light source sequentially passes through an electro-optical modulator and a lens group I and then enters a spatial light modulator; the spatial light modulator is used for synchronously regulating and controlling the multi-focus array and the non-diffraction light beam to generate the multi-focus array with the non-diffraction light beam characteristic; afterwards, the light sequentially passes through a lens group II, a two-dimensional scanning galvanometer, a scanning lens, a tube lens, an emission optical filter, a double-color piece and an objective lens and then irradiates a sample to be imaged; fluorescent light generated by a to-be-imaged sample passes through the objective lens and the double-color sheet and then is transmitted to the area-array camera, and fluorescent light signals at a plurality of focal points are collected to form a fluorescent light image. According to the invention, a diffraction-free optical phase modulation mechanism is introduced, simultaneous imaging of different depth layers is realized, the imaging speed is improved, sample information missed due to limited focusing depth is avoided, and the optical power utilization rate and the imaging quality are greatly improved.

The invention discloses a machine tool cutter space pose on-machine measurement device and a measurement method thereof, and the device comprises a calibration module which is installed at one side of a cutter handle of a cutter; a frequency-modulated continuous wave laser interference system and a galvanometer are installed on a vibration isolation workbench of the machine tool, light beams emitted by the frequency-modulated continuous wave laser interference system achieve conversion of a set angle through the galvanometer so as to cover the calibration module, and a space positioning algorithm is adopted to fit the plane where the target ball is located. And obtaining a deviation value between the mass center and the normal vector in two measurement results before and after machining, and taking the deviation value as the tool space pose error before and after machining of the machine tool, so that rapid and high-precision direct measurement of the tool space pose error is realized. The method has the advantages of being large in measurement range, high in measurement precision, simple in structure and low in cost, and the defect that in an existing method, the position and pose errors of the tool are indirectly calculated through an error model is overcome.

The invention discloses a plasma-assisted liquid metal self-activation method and application thereof.The self-activation method comprises the steps that patterned liquid metal photoresist is subjected to plasma treatment, hydrophilic groups are introduced into liquid metal nanoparticles and a silicon substrate, and then an elastomer solution is directly poured on a micro-scale liquid metal pattern; and when the elastomer film is stripped from the silicon substrate, due to the interaction of hydrophilic groups, the adhesive force and cohesion between the liquid metal nanoparticles and the silicon substrate and between the liquid metal nanoparticles are enhanced, so that the local stress concentration is enhanced, and the discrete particles are more easily broken and fused to form a conductive path. This process maintains high quality of the lithographically defined microscale liquid metal pattern while converting it from an insulator to a high conductor.

The present invention discloses an electromagnetic composite nondestructive testing sensor, system and method, belonging to the field of nondestructive testing technology, including an excitation component and a receiving component; the excitation component includes a first excitation coil for receiving an extremely low frequency excitation signal, a low frequency excitation signal or a medium-high frequency excitation signal, and a second excitation coil for receiving a medium-low frequency excitation signal or a high frequency excitation signal. The excitation component and the receiving component working based on excitation signals of different frequencies are integrated into the same sensor, and different excitation signals are introduced into the first excitation coil and the second excitation coil at different times to achieve different nondestructive tests, including eddy current detection, AC electromagnetic field detection, magnetic Barkhausen noise detection, incremental magnetic permeability detection and other nondestructive tests, so as to obtain stress changes caused by microstructures, the influence of incremental magnetic permeability on stress, and the influence of electrical conductivity and magnetic permeability on stress, so as to accurately judge the stress size of components, and provide an experimental verification basis for the study of complex stress theory.

The invention discloses a metal plate defect imaging method based on laser ultrasound and surface wave number filtering analysis, and aims to position defect positions and invert defect shapes by using metal plate surface wave echoes. The position of detection light of a laser vibration meter is determined on the surface of a fixed metal plate, and multiple groups of ultrasonic data are obtained by performing field scanning on the surface of the same side of the metal plate through a field scanning system. Performing wavelet transform on the obtained surface wave data to remove a low-frequency component in the signal, and performing Fourier transform on a time component to obtain a frequency spectrum; and then extracting signal data of a specific frequency and carrying out two-dimensional Fourier transform to obtain a wave number spectrum. And finally, filtering and inverse Fourier transform are carried out on the wave number spectrum to obtain a defect image, and defect positioning and defect shape imaging are realized.