344 results about "Probe array" patented technology

The invention relates to the technical field of artificial intelligence, and discloses an AI-based composite insulator internal defect ultrasonic detection method, which comprises a multi-mode ultrasonic probe array module, a signal preprocessing module, an AI defect analysis module, a dynamic parameter optimization module, an edge calculation module and a visual report module, the method comprises the following steps: acquiring a full-dimensional signal through a multi-modal ultrasonic probe array, and inputting the full-dimensional signal into a deep space-time convolutional neural network for defect recognition after adaptive noise reduction and feature fusion; the detection precision is improved by combining dynamic waveform matching and multi-physics coupling analysis; model lightweight and real-time processing are realized by adopting transfer learning and edge calculation. The system integrates the functions of parameter adaptive optimization, three-dimensional visualization and Internet of Things cooperation, solves the problems of low efficiency and high false detection rate of a traditional detection method, and improves the intelligent level and engineering applicability of composite insulator defect detection.

The invention relates to the field of chip packaging testing, in particular to a BGA chip packaging testing method. The method comprises the following steps: carrying out full-flow thermal imaging scanning on a BGA chip packaging process, carrying out space temperature gradient diffusion distribution analysis, and constructing a temperature diffusion distribution map of each region; according to the probe array, acoustic scanning is carried out on the BGA chip solder ball contact surface, abnormal frequency detection is carried out, and abnormal acoustic nodes are marked; performing transient temperature mutation detection and potential packaging defect positioning analysis on the temperature diffusion distribution map based on abnormal acoustic nodes, and extracting a potential packaging defect area; and carrying out multi-threshold micro-vibration excitation on the potential packaging defect area, carrying out comprehensive evaluation on the reliability of the defect area structure, and generating a reliability evaluation report of the solder ball contact surface structure. According to the invention, accurate packaging test failure prediction is realized, packaging process parameters are optimized, and chip packaging quality and stability are improved.

The invention relates to the technical field of medicine quality detection, and particularly discloses an optical detection method and system for the content of vitamin tablets. The method comprises the following steps: driving an optical fiber probe array to carry out three-dimensional multi-angle near-infrared scanning through a multi-axis mechanical arm, and collecting reflection spectrum data; a weighted spectrum is generated through derivative spectrum analysis and double evaluation, and auxiliary material noise is corrected and separated in combination with subspace projection and a dynamic kernel function; performing spectral vector projection and regression coefficient iterative optimization through an online PLS model, and synthesizing an error coefficient based on a four-level index retrieval standard library to perform dual-channel feedback; and finally, fusing the credibility weight to output a detection result of the binding confidence. The method realizes nondestructive and high-precision detection of the vitamin tablets, has the beneficial effects of multi-dimensional data fusion, dynamic error compensation and high model adaptability, and remarkably improves the detection accuracy and reliability.

The invention relates to the technical field of high-pressure resin transfer molding (HP-RTM), in particular to an intelligent forming system and equipment based on thermal-mechanical coupling carbon fiber composites.The intelligent forming method comprises the steps that real-time temperature field and strain field data are collected through a partition temperature control mold, thermal-mechanical coupling state parameters are obtained through signal filtering and abnormal value removing processing, and the thermal-mechanical coupling state parameters are obtained through a thermal-mechanical coupling module; an ultrasonic probe array is combined to detect internal defect distribution to evaluate a forming quality index, process parameters are dynamically compensated according to the quality index, and a deep learning model is constructed to optimize a forming process. According to the invention, real-time monitoring and closed-loop control of multi-physics field coupling can be realized, the defect rate is obviously reduced, the debugging period is shortened, the production efficiency is improved, and an intelligent solution is provided for carbon fiber composite material forming.

The invention provides a task chain self-healing transmission prediction method and system based on parameter fingerprint holographic perception, and relates to the technical field of parameter transmission, and the method comprises the steps: deploying a probe array to collect a task chain parameter flow, and extracting a feature tensor through a chaotic feature network to generate a feature fingerprint. The feature fingerprints are stored in a dynamic certificate chain, and a high-dimensional transfer matrix is constructed to track performance changes. And constructing an adaptive sensing network according to the dynamic certificate chain and the high-dimensional transfer matrix, and training an improved chaos twinborn model for constructing an anomaly recognition network. And generating a self-adaptive repair strategy according to the abnormal features and the historical data, and storing the self-adaptive repair strategy in a distributed knowledge graph. And training a prediction engine based on the knowledge graph and the chaos twinborn model, predicting the risk of the task chain, and finally evaluating the system performance through deep reinforcement learning to realize continuous optimization. According to the method, the task chain risk can be effectively predicted, self-adaptive repair is realized, and the stability and reliability of the task chain are improved.

The invention discloses a rubber-lined pipeline defect detection method and system, and the method comprises the steps: arranging an ultrasonic probe array, obtaining large-area scanning information of a rubber-lined pipeline, collecting an ultrasonic signal, an echo signal and a resonance signal, generating a resonance signal curve, and reflecting a mapping image of the interior of the rubber-lined pipeline. And calculating a half-power bandwidth and a damping characteristic parameter, generating a corresponding characteristic vector through the identification model, identifying and positioning defects in the rubber-lined pipeline, evaluating the severity of the defects, and outputting an identification result. Through the structural design of arranging a plurality of array elements of the array probe, the coverage range is increased, ultrasonic wave emission and receiving are carried out on the rubber-lined pipeline from different angles and positions, the probability of discovering small-area debonding is improved, in addition, the machine learning technology is combined, an intelligent recognition model is trained, rich features are provided, and the detection accuracy is improved. The capability of identifying different types of defects is enhanced, the sensitivity to different types of defects is improved, and the risk of missing detection of small-area debonding is reduced.

The invention relates to the technical field of silicon waveguide and optical fiber coupling, and particularly provides an AI-based silicon waveguide-optical fiber mode field self-alignment coupling method and system, and the method comprises the steps: monitoring the strain distribution of a chip in real time through an integrated distributed fiber bragg grating array, and obtaining the light field intensity distribution of a coupling region through cooperation with a near-field optical probe array; constructing a deep space-time convolutional network, and generating a deformation compensation vector and a waveguide reconstruction parameter by an output layer; a nanofluid channel is integrated on the side wall of the waveguide, and the refractive index of liquid is adjusted through an electrowetting effect to realize dynamic broadening of a mode field; and the electrostatic driving micro-beam embedded below the waveguide adjusts the spatial pose of the waveguide according to an instruction of an output layer of the depth space-time convolutional network. The system comprises a light field intensity acquisition module, a convolutional network construction module and a spatial pose adjustment module. According to the method, real-time analysis and prediction are performed, so that system parameters are actively adjusted, and alignment precision and stability are improved.

The invention provides a high-imaging-resolution method for identifying a lead sealing defect part of a cable, and relates to the field of nondestructive testing. Comprising the steps that a linear array probe array is utilized, a plurality of array elements emit ultrasonic waves to a to-be-detected defect part at the same time, and a received echo signal reflects the waveform shape and the waveform phase of the defect. A two-dimensional image is preprocessed through a synthetic aperture focusing technology, a combined image is reprocessed through a phase coherence technology, the quality and accuracy of the image are further improved, and a high-resolution three-dimensional image is constructed in combination with an imaging synthetic aperture focusing technology. The ultrasonic phased array technology, the SAFT technology, the phase coherence technology and the synthetic aperture focusing technology are combined, the imaging resolution is effectively improved, the method has remarkable advantages especially when defect parts in complex structures such as cable lead seals are recognized, the imaging quality is optimized, a two-dimensional image is converted into a high-resolution three-dimensional image, and finally an accurate defect recognition result is obtained.

The invention provides an unmanned aerial vehicle part circumferential weld ultrasonic automatic detection method and system, and relates to the technical field of nondestructive detection.The method comprises the steps that 1, a to-be-detected unmanned aerial vehicle part circumferential weld is fixed to an automatic detection platform, an ultrasonic phased array probe is coupled to the surface of the weld, and arrangement parameters and the initial coupling state of the probe are obtained; 2, according to the arrangement parameters and the initial coupling state of the probe, in combination with the curvature characteristics of the welding seam, the motion path length of the probe on the curved surface of the welding seam is calculated, the axial and circumferential composite motion trail of the probe is planned, the probe array is controlled to move along the composite motion trail, and ultrasonic signals are excited and received in a full-matrix capture mode; acquiring an ultrasonic original signal of the welding seam area; according to the method, the compound motion track of the probe is planned by combining with the weld curvature, the signal is synchronously calibrated, and the detection quality of internal defects of the circumferential weld is improved.

The invention provides a multi-probe array real-time pressure optimization and control method for wafer testing, and relates to the technical field of semiconductor testing, and the method comprises the steps: collecting real-time pressure data and a wafer stress limit value, building an initial distribution state, calculating the contact area and angle through displacement, determining a stress concentration factor, and carrying out the pressure correction, calculating strain rate distribution to identify a sensitive area to perform pressure compensation, monitoring a stress-strain ratio to identify a microcrack initiation point to determine an optimal pressurization parameter, and performing real-time monitoring and early warning. According to the invention, the damage risk in the wafer testing process can be reduced, and the testing precision and the yield can be improved.

The invention relates to the technical field of power transmission line safety monitoring, and particularly discloses a self-adaptive calibration method for an ultrasonic wind speed sensor, which comprises the following steps of: arranging an orthogonal ultrasonic probe array at the top of a tower, and compensating probe offset caused by swinging of a tower body in real time through GNSS / IMU (Global Navigation Satellite System / Inertial Measurement Unit) fusion positioning; integrating a temperature, humidity and pressure sensor and vibration spectrum analysis to construct an environmental parameter compensation model; double-frequency ultrasonic waves are adopted to detect the ice accumulation thickness of the protective cover and correct the sound path distance; deploying a lightweight LSTM model at an edge computing unit to realize minute-level dynamic parameter adjustment; electromagnetic interference is suppressed by combining linear frequency modulation spread spectrum and beam forming technologies; and establishing a three-height-layer wind speed gradient model to generate a galloping early warning. The problem of measurement distortion caused by tower deformation, icing and parameter solidification of a traditional sensor is solved, all-working-condition operation from-40 DEG C to 60 DEG C is supported, and the monitoring reliability in a strong electromagnetic environment is remarkably improved.

The invention relates to a real-time detection method and system for slurry quality. Comprising the steps that an ultrasonic probe unit is configured to conduct scanning detection on slurry, slurry target ultrasonic reflection information is generated after scanning detection, and the slurry target ultrasonic reflection information at least comprises m slurry ultrasonic reflection signal sets, the m groups of slurry ultrasonic reflection signal groups are respectively generated by sequentially performing m times of ultrasonic scanning on slurry by using an ultrasonic probe unit, and based on the m groups of slurry ultrasonic reflection signal groups and the generation sequence of the m groups of slurry ultrasonic reflection signal groups, calculating to obtain a reflection signal correlation coefficient group corresponding to each probe array element, based on the reflection signal correlation coefficient group of each probe array element, the quality state of the slurry is determined, and the quality state of the slurry includes that no foreign matter exists in the slurry or foreign matter exists in the slurry. The slurry quality can be detected in real time, and the detection efficiency and the detection precision are high.

The invention provides a blood coagulation factor activity detection system and method and a storage medium, and the system comprises a quantum dot fluorescent probe array module which comprises a plurality of quantum dot fluorescent probes and is used for identifying and marking different blood coagulation factors in a blood sample; the laser module is used for emitting laser beams with various preset wavelengths to the blood sample, and the various preset wavelengths are matched with excitation wavelengths of different quantum dots; the signal capturing module is used for continuously capturing a fluorescence signal corresponding to each quantum dot fluorescence probe and transmitting the fluorescence signal to the activity detection module in real time; and the activity detection module is used for recording fluorescence change signals corresponding to different blood coagulation factors, labeling blood coagulation factor types for the fluorescence change signals, and inputting an activity prediction model to obtain activity levels of different blood coagulation factors. The multi-quantum-dot fluorescent probe can efficiently detect the activity of various blood coagulation factors, and the comprehensiveness and accuracy of blood coagulation factor activity detection are improved.

The invention relates to the technical field of nondestructive testing, in particular to an ultrasonic phased array-based PE (Poly Ethylene) hot-melt joint nondestructive testing method and system, which comprises the following steps: acquiring material parameters in real time, establishing an anisotropic finite element model, dynamically compensating a sound wave path, spirally scanning a detection area, fusing and analyzing defect characteristics, optimizing three-dimensional imaging and the like. The system comprises an ultrasonic phased array probe array, a dynamic compensation controller, a six-axis mechanical arm and an imaging optimization engine. The invention solves or at least alleviates the problem of insufficient detection precision caused by non-uniform material anisotropy, dynamic density gradient and elastic modulus distribution in the nondestructive detection of the PE hot-melting joint in the traditional ultrasonic detection method, and provides the nondestructive detection method and system for the PE hot-melting joint based on the ultrasonic phased array.

The invention relates to the technical field of circuit board detection, and provides a circuit board damage detection optimization method and system, and the method comprises the following steps: S1, synchronously collecting a contact resistance signal, a probe pressure signal and environment data of a circuit board test point through a probe array, and carrying out the optimization processing of the collected data parameters; s2, establishing a contact impedance dynamic model, depicting the dynamic change of the contact impedance of the circuit board, extracting a characteristic signal for analysis, and mining the mode characteristics of an abnormal signal; and S3, fusing the abnormal multi-source evidences of the circuit board, processing the uncertainty and relevance among the evidences, and reversely deducing the positions and reasons of the potential defects on the circuit board. Through a multi-dimensional verification and error self-correction mechanism, the error between a defect solution and a real defect is quantified and reversely deduced by using posterior error estimation, so that the reliability and consistency of a detection result are improved, a reliable result support is provided for engineering application of circuit board damage detection, and meanwhile, the dependence on detection experience of detection personnel is avoided.

The invention relates to the technical field of wafer testing, and discloses a visual wafer identification probe station which comprises a processing table, a probe card, a bearing table assembly and an observation assembly. The probe card is selectively arranged on the processing table; the probe card comprises four groups of probe array assemblies; the bearing table assembly is used for driving the wafer to move in the space so as to be selectively matched with the probe card; the observation assembly comprises a driving assembly and four groups of visual monitoring assemblies, the four groups of visual monitoring assemblies are in one-to-one correspondence with the four groups of probe array assemblies, and the driving assembly is used for driving the four groups of visual monitoring assemblies to selectively monitor the corresponding probe array assemblies; the visual monitoring assembly comprises a camera and an adjusting assembly, and the adjusting assembly is used for adjusting the angle of the camera so as to monitor each probe body in the probe array assembly. The condition of the tip end of the probe body can be observed more accurately, so that the abrasion loss of the probe body can be compensated selectively, or the probe body or the probe card can be replaced selectively.

The invention relates to the technical field of LED display testing, in particular to an LED screen backlight module performance testing system which comprises the steps that a model identification code of a module to be tested is received, a corresponding standard optical parameter set is called, and initial driving current is applied. Actual optical signals driven by different currents are collected through a light sensing probe array and converted into a digital optical measurement value set containing brightness and color coordinate values of multiple sampling points. Comparing the brightness measurement value with a target brightness value point by point to generate a brightness consistency deviation matrix; and judging the color coordinate measurement value and the target range, and generating a color coordinate qualified identifier list. And calculating an actual brightness uniformity value according to the deviation matrix, and comparing the actual brightness uniformity value with a standard threshold value. And if the actual brightness uniformity value reaches the standard and the color coordinates of all the sampling points are qualified, generating a module qualification judgment instruction. According to the system, automatic and high-precision comprehensive evaluation of brightness space uniformity and chromaticity consistency of the backlight module is realized.

The invention discloses an impedance self-adaptive high-frequency probe, a probe card and a testing method, and belongs to the technical field of semiconductor high-frequency testing. When an existing high-frequency probe is used for a crimping test, a conductive probe body of the existing high-frequency probe generates mechanical deformation due to contact pressure, so that characteristic impedance is deviated, and uneven pressure in an array causes impedance dispersion. The problem is solved by coating the outer side of the conductive needle body with a composite material layer, the composite material layer is composed of an elastic insulating matrix and metal particles dispersed in the elastic insulating matrix, the metal particles have bimodal particle size distribution, and the total integral number is 30%-40%. When the probe is pressed, the composite material layer is subjected to reversible microscopic reconstruction, the effective dielectric constant of the composite material layer is increased along with the increase of the pressure, and the generated impedance change can counteract the impedance drop caused by the deformation of the conductive probe body, so that the self-adaptive stability of the characteristic impedance of the probe under the change of the pressure is realized. The impedance dispersion of the probe array can be remarkably reduced, the consistency and precision of high-frequency testing are improved, and the process compatibility is good.

The invention discloses a multi-frequency-point multi-polarization parallel sampling phased-array antenna automatic calibration platform, and relates to the technical field of antennas, and the platform comprises a control center which is used for parameter modeling and test task configuration, parallel sampling strategy generation, and data storage and tracing; the FPGA hardware controller is used for generating synchronous trigger pulses and synchronously triggering the radio frequency switch matrix, the multi-path signal source, the six-axis mechanical arm, the multi-probe array module, the double-axis rotary table and the vector network analyzer VNA array; the radio frequency switch matrix is used for quickly switching multi-frequency-point multi-polarization signals; the multi-path signal source, the six-axis mechanical arm, the multi-probe array module, the double-axis rotary table and the vector network analyzer VNA array are used for synchronously collecting test data; the data processing module is used for receiving the sampling data, calculating a test index and carrying out closed-loop compensation and result verification; the test efficiency, the equipment utilization rate and the measurement precision are remarkably improved, and full-process automatic calibration and multi-dimensional data tracing are achieved.

The invention discloses a bullet train wheel set ultrasonic wear detection device, and particularly relates to the technical field of rail transit detection, and the bullet train wheel set ultrasonic wear detection device comprises an ultrasonic probe module which comprises a multi-frequency composite probe array and a self-adaptive coupling structure and is used for carrying out all-directional scanning on a wheel flange, a tread and a rim of a wheel set; and the signal processing module is connected with the probe module and comprises a noise reduction unit, a feature extraction unit and a real-time early warning unit. According to the invention, the multi-frequency composite probe array and matrix layout are adopted, deep crack and surface wear detection is considered, the omission ratio is reduced, and the efficiency is improved by more than 30%; a liquid immersion type structure and a three-degree-of-freedom mechanism guarantee stable detection and adapt to more than 99% of vehicle models; accurate recognition is realized through a WT-CNN algorithm and the like, and the false alarm rate is reduced by 40%; the modular design adapts to multiple scenes, and the fault detection rate reaches 99.5% through full-dimensional diagnosis; the equipment adapts to an extreme environment, the service life is prolonged, the single-wheel detection time is finally shortened, the labor cost is reduced, and the overhaul efficiency and the rail traffic safety are remarkably improved.

The invention discloses a method and system for testing the performance of a magnetic flux leakage detection probe, and relates to the related field of magnetic flux leakage nondestructive detection.The method comprises the steps that a magnetic field is generated on the surfaces of a plurality of standard defect simulation samples through an excitation component, magnetic flux leakage signals are excited, the magnetic flux leakage signals are received through a magnetic flux leakage detection probe array, and a probe electric signal set is output after conversion; performing sensitivity feature extraction on the probe electric signal set, and analyzing to obtain a probe sensitivity test result; extracting stability characteristics, and analyzing to obtain a probe stability test result; multi-mode switching reliability feature extraction is carried out, and a probe multi-mode switching reliability test result is obtained through analysis; and integrating test results to obtain a probe performance test result. The technical problems that in an existing magnetic flux leakage detection probe performance test, the accuracy of a test result is difficult to guarantee, and the test efficiency is low are solved, and the technical effects of improving the accuracy and reliability of the test result and improving the test efficiency are achieved.

The invention discloses an intelligent main control board detection device and method, and the device comprises a recognition module, an operation module, a detection tool, a detection module, a control module and a display module, and the recognition module is used for transmitting a signal after recognizing that a PCB reaches a to-be-detected region; the operation module comprises a mechanical arm which is provided with a vacuum chuck and a label pasting mechanism; the detection jig is provided with a probe array and is matched with PCB test points; the detection module is connected with the PCB through a probe and executes short circuit detection and power-on function test; the control module coordinates all the modules; the display module has CAN communication, display screen and network uploading functions; wherein after receiving a signal of the identification module, the control module controls the operation module to transfer the PCB to the detection jig; then the detection module is triggered to perform short-circuit detection and then perform power-on function test; and finally, the operation module is controlled to label and sort according to a test result. According to the invention, a full-automatic transmission, identification, testing and sorting assembly line is constructed, the detection efficiency is greatly improved, and the misjudgment rate and the equipment damage rate are reduced.

The invention discloses an elevator steel belt damage detection and quantitative analysis system based on eddy current and magnetic flux leakage dual-mode detection, and aims to solve the problems of single-mode information loss and serious industrial field strong noise interference in the existing steel belt detection. The system synchronously integrates an eddy current sensor, a magnetic flux leakage sensor and an encoder through a multi-probe array adapter; and multi-dimensional damage physical information in the steel strip is obtained. An improved wavelet packet transform-empirical mode decomposition (WPT-EMD) collaborative noise reduction algorithm is adopted, and in combination with a sub-band energy entropy and a self-attention mechanism, non-stationary mechanical noise is effectively filtered out. A multi-rule feature extraction engine is used for extracting smooth residual errors, derivative mutation and other features, a support vector machine (DE-SVM) model introducing physical priori knowledge weights is constructed, and the small sample recognition problem is solved in combination with a virtual sample generation technology. The method can realize high-precision positioning and quantitative evaluation of steel strip damage under complex working conditions, and has the characteristics of strong anti-interference capability, high identification accuracy and good generalization performance.

The invention provides an optical signal synchronous calibration device and method of an optical computing system. The device comprises an optical probe array, an AI coprocessor, an optical path tuning engine and a low-speed electric feedback line, wherein the optical probe array is arranged on a chip; the optical probe array detects optical signals of wavelength channels corresponding to the plurality of optical calculation units and converts the optical signals into electric signals; the AI coprocessor drives a corresponding optical calculation unit to emit a detection pulse according to a pre-distributed time slot index variable, extracts a phase error from the electric signal and calculates a final calibration amount based on the phase error; the optical path tuning engine performs an optical path tuning operation based on the final calibration amount to calibrate an error of the corresponding optical calculation unit; and the low-speed electric feedback line transmits the electric signal to the AI coprocessor and transmits the detection pulse to the chip. According to the invention, through cooperation of spatial distributed detection and board-level centralized processing, real-time calibration in a dynamic environment is realized.

The invention relates to the technical field of face injection, in particular to a face precise injection system based on real-time B-ultrasonic imaging and a using method, and the method comprises a high-frequency ultrasonic imaging module which is provided with a deformable curved surface probe array; the image processing unit integrates a blood vessel segmentation algorithm, a three-dimensional reconstruction module and a dangerous area dynamic calibration function; the navigation positioning module comprises an electromagnetic positioner and an optical tracker; the injection executing mechanism is composed of a six-degree-of-freedom mechanical arm, a pressure feedback type injector and a needle tip microspur sensor; the main control unit is used for coordinating data interaction of all the modules and generating injection safety early warning; by adopting high-frequency ultrasonic imaging, the skin layer, fat layer, muscle and blood vessel structures can be clearly displayed, deviation caused by traditional touch typing injection is avoided, tiny blood vessels can be recognized through an AI blood vessel automatic segmentation algorithm, and therefore the risk of wrong injection in the blood vessels is remarkably reduced.

The invention provides a phased array ultrasonic nondestructive evaluation method and system for the grain size of a complex component, and belongs to the technical field of ultrasonic nondestructive testing. Comprising the following steps: detecting a workpiece with multiple curved surfaces by adopting a liquid immersion mode in cooperation with a phased array ultrasonic probe array, and dividing to-be-detected areas of different structure types according to the shape characteristics of the workpiece; an acoustic beam focusing rule and an acoustic beam propagation path of the phased array ultrasonic probe array are designed, and phased array ultrasonic detection parameters are designed for to-be-detected areas of different structure types according to size parameters of workpieces; detecting grain sizes of to-be-detected areas of different structure types of a workpiece, and collecting phased array ultrasonic signals of the to-be-detected areas through the phased array ultrasonic probe array; calibrating the collected phased array ultrasonic signals of each to-be-detected area, and respectively calculating the average attenuation coefficient of the phased array ultrasonic probe array signals of each to-be-detected area; and calculating the grain size of the to-be-measured area through a pre-constructed grain size phased array ultrasonic evaluation model.

The invention discloses an ecological protection area human behavior recognition method and device based on gait feature recognition. An annular first optical fiber detection layer is laid on the periphery of an isolation belt of a protection area; deploying a radial second optical fiber detection layer on the isolation strip towards the center of the isolation area; the three-frequency WiFi probe array is deployed in the isolation zone domain; the intrusion position identification module is used for detecting a vibration signal by using the first optical fiber detection layer, calculating an intrusion position coordinate through a time difference positioning formula, and activating a monitoring channel of a radial second optical fiber detection layer in a corresponding direction according to the position coordinate; the gait feature fusion extraction module is used for extracting multi-scale energy features and generating gait comprehensive features through the multi-scale energy features; and the identity judgment module is used for inputting the gait comprehensive features into a pre-trained classification model, and judging the identity of an intruder according to the gait comprehensive features, thereby realizing the construction of an ecological protection area protection technology system with intelligent perception, dynamic response, global linkage and low cost.

The invention discloses an anti-aging prediction method and system for an automobile paint surface protective film based on microelement analysis, and relates to the technical field of anti-aging evaluation of bonding materials, and the method comprises the steps: based on the automobile paint surface protective film, arranging a microcell spectrum probe array, and setting a multi-spectrum cooperative detection coordinate system; constructing a dynamic material degradation characteristic spectrum; meanwhile, a dynamic environment simulation cabin is configured, and an accelerated aging data set is obtained; and simulating a quantitative relation between a micro-element migration track and a mechanical property degradation rule, and carrying out cross-scale reverse prediction on the residual service life of the automobile paint surface protection film. According to the method, the technical problems that in the prior art, the micro element valence state distribution of the automobile paint surface protection film is difficult to accurately analyze, the residual service life prediction lacks a cross-scale analysis means, and the aging prediction accuracy is insufficient are solved, the micro element valence state distribution analysis of the automobile paint surface protection film and the cross-scale reverse prediction of the residual service life are realized, and the aging prediction accuracy is improved. And the aging prediction accuracy of the protective film is improved.

A high-density bioprobe array is provided comprising conductive or optical shanks. A method of making high-density bioprobe arrays also is provided. A bioprobe system using the array also is provided.

The invention discloses a cavitation bubble group internal structure observation method and device based on plane waves in the technical field of cloud bubble measurement, and the method comprises the steps: carrying out a hydrofoil experiment in a water tank, and generating to-be-observed cloud bubbles; adjusting the ultrasonic imaging probe array through computer programming, and adjusting time delays of different array elements to generate a plurality of plane waves with different deflection angles; collecting plane wave echoes received by each array element, and storing echo data corresponding to each deflection angle; coherent superposition is carried out on image data obtained at different deflection angles, the contrast ratio and the signal-to-noise ratio of imaging are improved, and the effect equivalent to focusing imaging is obtained.