239 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 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 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 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 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 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 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.

The invention relates to the technical field of cervical vertebra rehabilitation systems, and discloses an intelligent self-adaptive cervical vertebra rehabilitation system. The system comprises a multi-mode sensing unit which synchronously collects form data and soft tissue data of the cervical vertebra of a user through an optical mark point array and an ultrasonic probe array to generate a multi-source sensing data set; the intelligent analysis unit constructs a cervical vertebra dynamic mechanical model by using a graph convolutional neural network based on the multi-source sensing data set, analyzes a cervical vertebra joint coupling relation and stress distribution, and generates an analysis parameter set; the strategy generation unit generates a personalized rehabilitation strategy according to the analysis parameter set, the personalized rehabilitation strategy comprises an action sequence and an impedance adjustment parameter, and a strategy instruction set is formed; the dynamic control unit responds to the strategy instruction set and combines muscle activity data fed back by the electromyographic signal sensor in real time to adjust an execution strategy and generate a control command set; and the flexible driving unit drives the soft robot outer skeleton to perform multi-axis linkage rehabilitation training based on the control command set.

The invention discloses a material corrosion-oriented surface microenvironment multi-parameter sensing method and system, which realize real-time monitoring of a plurality of key physical and chemical parameters by arranging a micro sensing probe array on the surface of a material. And constructing a space-time parameter matrix by using the obtained data, calculating the time change rate of each parameter, and setting a disturbance threshold value to mark an abnormal point. A disturbance area is identified through spatial clustering of abnormal points, corrosion activity indexes are defined in combination with temperature, relative humidity, electrochemical driving force, local acidification degree and chloride ion concentration, and a continuous corrosion activity distribution diagram is generated. And tracking a spatial overlapping relation of the disturbance area to form an evolution chain, and predicting a future expansion trend. And finally generating a comprehensive report containing a corrosion activity space-time overview map, a key event timeline and a regional risk grading list. The accuracy and efficiency of corrosion monitoring are improved, and a scientific basis is provided for preventive maintenance.

The invention provides an aluminum bar internal inclusion and pore detection system based on an ultrasonic flaw detection technology, and relates to the technical field of ultrasonic detection, and the system comprises a construction module which is used for constructing a detection module by taking an end face center point of an aluminum bar as a first reference position, taking the center of a phased array ultrasonic probe array as a second reference position, and taking a reference positioning edge of a detection table as a third reference position; a dynamic adjustable detection coordinate system is constructed; the calculation module is used for dividing the detection coordinate system into a plurality of hierarchical scanning sub-regions according to the two-dimensional spatial topological characteristics of the detection coordinate system and the actual size and shape distribution rule of the end face of the aluminum bar; and according to the spatial position and the area of each scanning sub-region and the geometric distribution characteristic of the distance between each scanning sub-region and the core region of the end surface of the aluminum bar, calculating to obtain a focusing delay parameter and a scanning path parameter corresponding to each sub-region. According to the invention, accurate and efficient detection of non-metallic inclusions and pore tiny defects in the aluminum bar is realized.

The invention discloses a lithium battery full life cycle health state monitoring method, belongs to the technical field of lithium ion battery detection, and aims to identify pore defects and dynamic bubble behaviors in a battery in real time. According to the method, broadband ultrasonic waves are emitted through an air coupling multi-probe array, and back scattering signals caused by bubbles and uneven structures in a battery in the charging and discharging process are collected. And in combination with a porous medium acoustic theory, extracting time domain and frequency domain characteristic parameters related to the bubble form and distribution, and inputting the time domain and frequency domain characteristic parameters into a preset bubble state-signal response model. On the basis, the evolution state of the internal gas production defect of the battery is judged, so that effective support is provided for fault early warning and safe operation of the lithium ion battery. The method has the remarkable advantages of simplicity and convenience in operation, high real-time performance, high accuracy and the like, and can be widely applied to online detection and quality control of a battery production line.

The invention provides an electric power secondary circuit multi-parameter intelligent detection system and method based on edge computing, the system comprises a composite sensing array, a self-adaptive probe system and an edge computing system, the composite sensing array comprises a plurality of sensors, the self-adaptive probe system comprises a multi-direction adjustable probe array, and the multi-direction adjustable probe array is connected with the edge computing system. The tail end of each probe in the multidirectional adjustable probe array is embedded into the permanent magnet, and the multidirectional adjustable probe array transmits the acquired electrical signals of the terminal strip to be tested to one or more of the plurality of sensors through the multiplexer; and the composite sensing array and the adaptive probe system are connected with the edge computing system, so that the detection efficiency is effectively improved.

The invention provides an inclined shaft gas-liquid slug flow ultrasonic flow velocity monitoring and calculating method and system, and the system comprises an ultrasonic flow velocity monitoring probe array module, a signal collection and preprocessing module, and a data processing and calculating module. The method comprises the following steps: performing variational mode decomposition on a signal, separating characteristic components of different flow structures in slug flow, realizing real-time discrimination of a liquid slug and a liquid film section and accurate capture of liquid phase apparent velocity, and accurately calculating gas phase apparent velocity through a unified mechanism model. Through the multi-angle same-direction array design, the measurement deviation caused by non-uniform cross section flow velocity distribution of the inclined shaft is overcome; the composite signal in the slug flow is effectively separated through variational mode decomposition, and the frequency shift extraction precision is improved; the innovative real-time flow state discrimination method based on the signal-to-noise ratio realizes the self-adaption of the measurement model to the flow structure, and significantly improves the measurement accuracy under the complex intermittent flow.

The invention relates to the technical field of integrated circuit testing, in particular to an integrated circuit testing method and system. The method comprises the following steps: carrying out power-on operation on a to-be-tested integrated circuit, carrying out probe contact standard comparison, and generating a probe contact quality evaluation code; performing probe channel distribution processing according to the probe contact quality evaluation code, performing magnetic field excitation frequency band analysis, and generating magnetic field excitation avoidance frequency band data; applying a static vector magnetic field environment to the to-be-tested integrated circuit based on the magnetic field excitation avoidance frequency band data, and performing circuit channel test processing to obtain circuit test characteristic response data; performing channel test analysis according to the circuit test characteristic response data to obtain integrated circuit test result data; and performing cross-module fault relevance detection according to the integrated circuit test result data to obtain functional module fault relevance data. Abnormal channel jump and impedance fluctuation detection of the integrated circuit is realized through multi-frequency-point probe array testing in a static magnetic field environment.

The invention relates to the technical field of aluminum ash recycling digital twinning, and discloses an aluminum ash recycling treatment method based on a high-aluminum material. According to the method, a digital twinborn body in a processing process is constructed, and a virtual probe array corresponding to a key reaction site of a real device is set in the digital twinborn body, so that dynamic evolution information of aluminum ash processing is continuously captured. An evolution chain of a physical field and a material flow is constructed based on the information, then a processing path is deduced reversely, and key evolution nodes and constraint conditions are identified. The nodes and conditions are converted into a control strategy set, and a real processing system is driven to execute closed-loop regulation and control. According to the method, deep perspective of the internal evolution mechanism in the aluminum ash treatment process is achieved, accurate regulation and control are achieved based on causal analysis, and the stability and the resource recovery rate of the treatment process are improved.

The invention provides a landslide early warning and evaluation method and system. The landslide early warning and evaluation method comprises the steps of uploading target parameters obtained through periodic measurement of a probe array to a cloud platform, dynamically inverting shear strength parameters of depth points of a sensing section based on the target parameters through an inversion model, and calculating a safety coefficient according to the shear strength parameters; wherein when the safety coefficient is larger than a set threshold value, pre-sliding early warning is triggered; and monitoring the temperature time sequence in real time to obtain the depth of the sliding surface and trigger landslide early warning when the temperature time sequence of any depth point meets the condition of the sliding event, evaluating the volume of the landslide mass based on the depth of the sliding surface, and outputting a landslide report. According to the invention, in-situ and continuous measurement of the target parameters of the soil body can be realized, the attenuation process of the shear strength of the soil body can be sensed in advance, and the loss possibly caused by landslide disasters is reduced; meanwhile, the scale and the influence range of the landslide can be quickly known after the landslide occurs.

The invention relates to the technical field of electromagnetic metamaterial characterization, in particular to a near-field characterization method for equivalent electromagnetic parameters of an electromagnetic metamaterial, which comprises the steps of multi-probe array sampling, data calibration, signal decomposition and phase compensation, boundary effect correction, non-uniformity compensation, parameter inversion, adaptive filtering, real-time monitoring and the like. By comprehensively applying the technical means, the accuracy and the reliability of electromagnetic field distribution sampling under the near-field condition are remarkably improved, the boundary effect and the non-uniformity influence are effectively reduced, and the accuracy and the stability of equivalent electromagnetic parameter extraction are ensured. Meanwhile, a real-time monitoring and feedback control mechanism enhances the dynamic tracking capability and the system optimization efficiency. According to the method, the requirements of modern electromagnetic metamaterial design and optimization can be met, and the defects of the prior art in the aspects of representation precision, calculation efficiency and complex structure adaptability are overcome.

The invention discloses an insulating pull rod full-automatic detection system and method based on an annular ultrasonic probe group. The system comprises a detection assembly; an insulating pull rod is arranged in the detection assembly, and the detection assembly is electrically connected with the signal processing unit, the defect analysis module and the computer; the detection assembly comprises an annular ultrasonic probe group and an automatic stepping device; the two ends of the annular ultrasonic probe set are connected with the automatic stepping device, and a stepping track is arranged in the automatic stepping device and used for driving the annular ultrasonic probe set to stably move in the axial direction of the insulation pull rod. Full-circle scanning of the insulation pull rod is achieved through the annular ultrasonic probe set, the problems of poor coupling and missing detection in traditional ultrasonic detection are effectively solved by matching with the spiral scanning path of the automatic stepping device and the self-adaptive adjusting mechanism, meanwhile, the position is calibrated in real time through the infrared distance measuring sensor, and it is ensured that the detection precision is stable.

This invention belongs to the field of concrete pouring technology, and particularly relates to a precise control method for pile foundation concrete pouring based on multi-source sensor fusion. Addressing the problems of large measurement errors, frequent over-pouring, and significant concrete waste in traditional pile foundation pouring, this invention employs a high-frequency ultrasonic probe array coaxially fixed to the outer wall of the pouring guide pipe to uniformly elevate and scan, acquiring three-dimensional point cloud data of the entire pile foundation. After two levels of outlier removal and adaptive multi-scale spectral filtering preprocessing, combined with the expansion of the over-pouring section point cloud, a high-precision three-dimensional model of the pile foundation is constructed. Cross-sectional features at each depth are extracted to generate a pumping flow rate feedforward compensation curve, and a segmented adaptive improved PID controller is constructed with real-time concrete interface elevation and rise speed as feedback quantities to dynamically regulate the pumping flow rate. This invention achieves automated, intelligent, and precise control of the entire pile foundation pouring process, effectively improving pouring control accuracy, significantly reducing concrete waste and construction costs, and solving the measurement and pouring control problems of traditional construction.

The application discloses a GIS insulator partial discharge charge on-line detection method and system, and relates to the technical field of charge detection.The method comprises the following steps: according to a GIS simulation model, simulating the electric field distribution of charge generation in the partial discharge process, determining the performance index of the required electric field sensing probe, and preparing the electric field sensing probe; according to an epoxy resin model, obtaining the charge density, the charge distribution range and the electric field signal collected by the electric field sensing probe under different voltage pulses, and constructing a test data set; according to the GIS simulation model, obtaining the electric field signal under different charge densities and different charge distribution radii, and constructing a training data set; training a neural network model according to the training data set, and correcting according to the test data set; and collecting the partial discharge electric field signal by using the electric field sensing probe array arranged on the outer wall of the GIS insulator, and obtaining the charge density and the charge distribution range on the surface of the insulator by using the neural network. Non-invasive and non-contact on-line measurement is realized.

The utility model discloses an IV probe row for 0BB production, which comprises an installation frame and a circuit board, a front installation strip and a rear installation strip are arranged on the installation frame, front connecting seats are distributed on the front installation strip along the horizontal direction, rear connecting seats are distributed on the rear installation strip along the horizontal direction, and tension springs are fixed on the front connecting seats and the rear connecting seats. A gold wire is connected between the two tension springs corresponding front and back, the circuit board is fixed to the rear end of the mounting frame, and a wire is connected between the circuit board and the rear mounting strip. The IV probe row for 0BB production mainly acts on IV detection on an 0BB silicon wafer, can effectively detect broken wafers under the combined action of the IV probe row and a silver row, elastically contacts an auxiliary grid on the silicon wafer under the action of a tightened gold wire, is novel in structure, can adjust the position of the gold wire according to the position of the auxiliary grid, reduces cost and efficiency in production of the 0BB silicon wafer, and reduces the fragment rate at the same time.

A method and device for human behavior recognition in ecological protection zones based on gait feature recognition are proposed. The method involves laying a ring-shaped first optical fiber detection layer around the perimeter of the protected area's isolation zone; deploying a radial second optical fiber detection layer along the isolation zone towards the center of the protected area; and deploying a tri-band WiFi probe array within the isolation zone. An intrusion location recognition module uses vibration signals detected by the first optical fiber detection layer to calculate the intrusion location coordinates using a time difference positioning formula, and activates the monitoring channels of the corresponding radial second optical fiber detection layer based on the location coordinates. A gait feature fusion and extraction module extracts multi-scale energy features and generates comprehensive gait features. An identity discrimination module inputs the comprehensive gait features into a pre-trained classification model and determines the identity of the intruder based on the comprehensive gait features, thereby constructing an intelligent, dynamic, interconnected, and low-cost ecological protection technology system for ecological protection zones.

The invention discloses a bolt pre-tightening force monitoring system and method based on ultrasonic waves. The system comprises an ultrasonic probe, a data acquisition and processing analyzer and the like, a probe array is uniformly mounted on the surface of a bolt, an improved depth residual network is arranged in the data acquisition and processing analyzer and can process a flight time difference signal, and an audible and visual alarm can trigger a three-level alarm according to pre-tightening force deviation. The data remote transmission device provides data for the digital twin system, the display unit displays a pre-tightening force distribution atlas in real time, and a digital twin system platform generates a three-dimensional visual dynamic model and the like. According to the method, bolt pre-tightening force monitoring is achieved through the system. The system is high in measurement precision, convenient to install, capable of achieving real-time early warning and intelligent operation and maintenance, and suitable for various industrial fields.

The invention discloses a multi-field coupling intelligent inclination angle plane physical similar simulation experiment system and method. The system comprises an experiment platform with a controllable inclination angle, a stress monitoring module, an optical deformation monitoring module and an acoustic emission monitoring module. The experiment platform realizes high-precision adjustment and stable maintenance of an inclination angle of + / -0.1 degree through cooperation of hydraulic drive and a mechanical lock. The stress module adopts a wireless sensor network to monitor a stress field; the optical module is used for measuring full-field displacement strain based on a CCD camera and a digital image related technology; and the acoustic emission module positions a rock stratum fracture signal through the probe array. The method comprises the steps of platform deployment, inclination angle adjustment, system debugging, synchronous mining monitoring and the like. According to the invention, inclination angle accurate control and multi-physical field information synchronous integrated acquisition are realized, and the system is suitable for inclined coal seam mining rock stratum movement and disaster mechanism research.

The application provides a multi-probe array obstacle positioning method and device. The method comprises: in the case that multiple ultrasonic probes enter a transmitting mode of transmitting ultrasonic waves in turn and the multiple ultrasonic probes all enter a receiving mode of receiving ultrasonic waves, generating multi-dimensional time data corresponding to each transceiver pair; the transceiver pair comprises a pair of ultrasonic probes in the transmitting mode and an ultrasonic probe in the receiving mode; performing grid processing on the front area of the ultrasonic probe to obtain multiple grid points; determining a voting value corresponding to each grid point based on the multi-dimensional time data by using a spatial voting algorithm; and in the case that the voting value corresponding to the grid point is greater than a first threshold, determining positioning information of an obstacle based on the grid point. In this way, in a multi-obstacle scene, the positioning information of the obstacle can be confirmed by the voting values of the multiple grid points corresponding to the multiple grids in the front area of the ultrasonic probe, so that the purpose of accurate positioning and judgment in a multi-obstacle scene can be achieved.