585 results about "Sensor array" patented technology

This invention relates to the field of mechanical property monitoring technology for mine backfill bodies, specifically to a system and method for acquiring and analyzing tensile strength data of mine backfill bodies. The system comprises a data acquisition unit, a physical information coupling unit, a tensile strength inversion unit, and a spatiotemporal evolution mapping unit. This invention acquires the waveguide flight time and energy attenuation coefficient of the backfill body using an embedded guided wave sensor array. It uses the monotonically increasing law of hydration degree as a physical constraint to train the physical information coupling network, outputting a compliant hydration degree time series. Based on a hydration degree-tensile strength mapping relationship library, it inverts and fits to generate a strength growth curve, which is then loaded into a four-dimensional digital twin model to invert the internal tensile strength gradient field. It automatically identifies local abnormal regions where the growth rate is below the safety threshold, improving the physical rationality and accuracy of the inversion results, and realizing visualization of the spatiotemporal evolution of backfill body strength and early safety warning.

The utility model relates to road detection technical field especially, it relates to a road flatness intelligent detection device, including main control circuit, multichannel capacitance sensor array, electromagnetic shield casing, the multichannel capacitance sensor array is by the multiple capacitive proximity sensor that is arranged in matrix, is fixed in detection device bottom, the multichannel capacitance sensor array adopts differential type measurement structure, and is equipped with the isolation drive ring between adjacent capacitive proximity sensor, the signal conditioning circuit is connected between the multichannel capacitance sensor array and main control circuit, the inertia measurement unit is connected to main control circuit, the electromagnetic shield casing covers the device, adopts the layered shielding structure, contains at least one conducting layer and a layer electromagnetic shield layer, and is connected through multipoint earthing between layers, the utility model can adopt multichannel capacitance sensor array and realize high accuracy, non -contact type measurement, and through the electromagnetic shield design, temperature compensation and attitude change compensation of the target ensure measurement stability.

A distributed ultrasonic monitoring system for an internal fracture process of an ultra-large three-dimensional geological model includes a high-power ultrasonic phase control apparatus, ultrasonic transmitting and receiving integrated sensors, and measurement and control and three-dimensional ultrasonic imaging software. A geometric asymmetric monitoring layout mode is adopted to form a three-dimensional monitoring grid. The sensors are coupled with the three-dimensional geological model using a pre-embedded manner, the sensors according to sequential numbers are connected to the high-power ultrasonic phase control apparatus, and the sensors of each chain sensor array are excited one by one according to a pre-set delay time; and the three-dimensional ultrasonic imaging software inverts and analyzes a three-dimensional wave velocity field of the monitoring areas according to a relationship of echoes, transmission wave signals and the three-dimensional grid, and reflects rock fracture positions and degrees through changes in the wave velocity field.

The present application relates to a kind of based on multi-source industrial data's car body welding quality intelligent perception, prediction and decision-making method and system, belong to the technical field of intelligent manufacturing and industrial data analysis.The present application obtains multi-source high-frequency synchronous original signal by sensor array and robot bus;Perform space-time alignment and multidimensional feature mining;Quality perception model is constructed based on multi-path parallel network and cross-modal attention;Quality evolution trend and electrode cap life are evaluated using time series prediction model;Integrate expert rules and reinforcement learning to make process compensation decision.The present application realizes the accurate perception of welding quality, forward warning and closed-loop real-time compensation, significantly improves the perception accuracy, production robustness and prolongs the service life of electrode.

This invention belongs to the field of food or beverage processing technology, specifically relating to an intelligent evaluation and brewing control system for tea infusion quality based on multi-source sensor fusion. The system uses a multi-wavelength optical sensor array and distributed temperature sensors to acquire spectral absorption peak shift characteristics and temperature gradient vectors, respectively, and then concatenates them to construct a three-dimensional tensor containing time, spatial height, and wavelength dimensions. This three-dimensional tensor is input into a spatiotemporal graph convolutional network. Its spatial graph convolutional layer extracts spatial features using temperature nodes at different height levels as vertices and thermal conduction physical relationships as edges; the temporal convolutional layer extracts temporal features; and the fully connected layer outputs the predicted solute release rate and the deviation value of the target temperature gradient. The controller generates pulse-width modulation signals based on the deviation values ​​to adjust the heating plate power and the timing of the water injection valve. This invention jointly analyzes heat distribution and solute concentration changes, and corrects control commands based on the physical release state of the solute, ensuring that temperature field changes match solute diffusion.

This application discloses a method and system for estimating the direction of arrival (DOA) of weak targets based on Riemannian manifold background suppression and adaptive sparse Bayesian learning. The method includes: acquiring time-series signals using a sensor array to construct a series of sample covariance matrices, mapping them to a point sequence on a Hermitian positive definite matrix manifold space; iteratively calculating the background interference covariance matrix using the non-Euclidean geometric properties and logarithmic shielding effect of the Riemannian metric; mapping the background interference covariance matrix back to Euclidean space, adaptively performing background subtraction based on an energy decision mechanism to reconstruct a positive definite covariance matrix to be measured; inputting the covariance matrix to be measured into a sparse Bayesian learning framework, first iteratively recovering the signal power through adaptive mesh refinement sparse Bayesian learning, then performing a closed-loop iteration of subspace noise cleaning while keeping the mesh fixed to recover the sparse spatial spectrum of the target signal; and finally, using local analytical interpolation techniques to eliminate mesh quantization errors and calculate the precise DOA of the target.

The application provides a static wireless charging auxiliary alignment positioning device and a positioning method. The device comprises a transmitting end device and a receiving end device. The transmitting end device comprises a wireless transmitting plate and a charging pile. The wireless transmitting plate is integrated with a transmitting end power coil, a three-dimensional Hall sensor array and an infrared distance measuring module. The charging pile is internally provided with a servo motor adjusting mechanism, a control unit and a first communication module. The receiving end device comprises a heterogeneous permanent magnet array integrated in a wireless receiving plate, a receiving end power coil and a second communication module. The heterogeneous permanent magnet array is arranged at the periphery of the receiving end power coil. The second communication module is connected with the first communication module through wireless communication. The transmitting end power coil is resonantly matched with the receiving end power coil. The application significantly improves the positioning accuracy and system robustness, and can adapt to the chassis height of different vehicle models to ensure the efficiency and stability of wireless charging.

This invention provides a constant temperature and pressure control method and a high and low temperature low pressure test chamber. Through high-precision sensor array multi-source data acquisition, signal filtering and feature extraction, combined with improved Granger causality test and coupling spectrum construction, the main propagation path and propagation characteristics of various disturbances are identified. By using sliding window online optimization and dynamic weight matrix, the disturbance suppression mechanism is embedded in the PID loop to achieve multi-channel weighted compensation of proportional, integral and derivative components. This invention can accurately identify and compensate for external disturbances of different paths, time sequences and frequency bands in real time, improve the control accuracy and anti-interference ability of the system, and ensure the stability and robustness of the test chamber operation.

This invention relates to the field of maintenance management decision-making technology and discloses an intelligent pavement condition assessment and resource allocation system integrated into a mobile platform. The system includes sequentially connected modules for mobile data acquisition, data preprocessing, pavement condition assessment, resource optimization allocation, and decision support and feedback. The mobile data acquisition module collects multi-source data through a sensor array and dynamic sampling strategy; the preprocessing module generates a high-quality dataset through cleaning, spatiotemporal calibration, and standardization; the assessment module calculates the Pavement Health Index (PHI) based on a three-level model to accurately classify pavement condition levels; the resource optimization allocation module aims to maximize overall maintenance benefits by solving for the optimal resource allocation using a multi-constraint linear programming model; and the decision support and feedback module provides visualized decision display and corrects model parameters based on post-maintenance re-inspection data. The system improves the accuracy of pavement assessment and the scientific nature of resource allocation, adapting to the needs of large-scale road network maintenance management.

The application belongs to the technical field of thermal field measurement under high temperature environment, and particularly relates to a high-temperature thermal field direct measurement sensor array. In use, thermal radiation is irradiated on a heat-absorbing layer, the heat-absorbing layer absorbs the thermal radiation and transmits the heat to a high-conductivity micro region, so that a transverse thermoelectric voltage is generated between a first electrode and a second electrode, and the heat flux density at the high-conductivity micro region is calculated according to the transverse thermoelectric voltage; the temperature at the high-conductivity micro region is calculated according to the resistance between a third electrode and a fourth electrode, the heat flux density at the high-conductivity micro region is calibrated through the temperature at the high-conductivity micro region, and the spatial distribution characteristics of the heat flux are inversed by comprehensively considering the heat flux and the temperature at multiple high-conductivity micro regions. The high-temperature thermal field direct measurement sensor array can output the spatial distribution of two modes of heat flux density and temperature, and realize high-precision spatial distribution measurement of the thermal field.

This invention discloses a method for monitoring the cold chain environment of fruits and vegetables based on multi-sensor fusion, belonging to the field of intelligent sensing and agricultural product logistics technology. It includes: using a flexible multimodal sensor array attached to the surface of fruits and vegetables to acquire the temperature, humidity, and original level signals of the target gas in the surface microenvironment; performing a cross-drift compensation step based on local temperature and humidity physical feedback, using a multivariate nonlinear regression model to use temperature and humidity as dynamic compensation factors, calibrating the baseline drift of the gas sensor in real time, and obtaining high-confidence gas concentration values; calculating the rate of change of the gas concentration values ​​in real time, and automatically triggering an edge interruption when the rate of change exceeds a preset jump threshold, dynamically increasing the sampling frequency and adjusting the radio frequency duty cycle. This invention solves the technical problems of large measurement errors caused by the inability of traditional rigid sensors to conformally fit, severe sensor baseline drift in high humidity environments, and the mutual constraint between high-frequency monitoring and node energy consumption.

The application discloses a kind of intelligent operation body position monitoring method and system for long time operation pressure injury prevention, it is related to intelligent medical equipment and medical sensing monitoring technical field, for solving the problem of poor anti-interference and prone to body position displacement caused by blind decompression of traditional operation pressure sore prevention means.First, stress and temperature and humidity signals are acquired by sensor array and compensation calibration is carried out, environmental interference is eliminated to construct pressure distribution matrix;Subsequently, stress gradient is analyzed and time accumulation mapping is carried out relying on topological characteristics, and core high-risk site and load characteristics are accurately locked;Then, physiological and time sequence parameters of patient are fused to deduce tolerance baseline, and individualized bearing limit boundary is generated to realize dynamic early warning;Finally, the strategy of establishing support by using peripheral air bag progressive pre-inflation and center air bag servo unloading exhaust is adopted, which completely resolves concentrated stress while maintaining the absolute stability of operation body position, and constructs active protection closed-loop system.

This application relates to the field of big data acquisition technology and provides a carbon-saving deodorization control method and system based on online gas monitoring. The method includes: deploying a corresponding sensor array according to a preset sensor deployment strategy to collect gaseous environmental data, obtaining a multi-dimensional spatiotemporal dataset; extracting features from the multi-dimensional spatiotemporal dataset using a multi-layer convolutional neural network to obtain a diffusion feature set of odor pollutants; constructing an odor pollutant diffusion model based on the diffusion feature set; simulating the probability distribution of the diffusion path of the odor pollutants using a Monte Carlo algorithm based on the odor pollutant diffusion model to generate a diffusion topology; determining the control priority of a preset emission valve based on the diffusion topology; and controlling the opening and closing state of the preset emission valve according to the control priority to ensure that the concentration of the odor pollutants meets a preset concentration condition. This method helps improve the prediction accuracy of the diffusion path of gaseous pollutants.

This invention discloses a multi-channel programmable miniaturized high-speed FBG demodulation system and method based on an AWG (Optical Fiber Optic Generator), belonging to the field of fiber optic sensing technology. The AWG-based multi-channel programmable miniaturized high-speed FBG demodulation system includes a high-stability broadband light source module, a low-loss isolation module, a miniaturized programmable fiber optic amplifier, a circulator, a two-stage miniaturized high-speed optical switch, a high-crosstalk AWG module, a photoelectric conversion module, a programmable A / D conversion module, and a core control module. The AWG-based multi-channel programmable miniaturized high-speed FBG demodulation method involves the optical signal entering an FBG sensor array, the FBG sensor reflecting the optical signal, the reflected optical signal entering the AWG module, and the output light undergoing photoelectric conversion to calculate the center wavelength of the FBG sensor. This invention, based on an AWG, improves demodulation accuracy while ensuring the demodulation range, achieving continuous wavelength demodulation within the AWG wavelength range.

This invention relates to a method for diagnosing and locating inter-turn short-circuit faults in air-core reactors based on a magnetic field sensor array, belonging to the field of power equipment testing. The method includes the following steps: Step 1: Arranging a magnetic field sensor array at an axial position on the outer side of the air-core reactor to acquire magnetic field distribution data near the reactor; Step 2: Calculating the magnetic field distribution data at the location of the magnetic field sensor array under normal operating conditions and inter-turn short-circuit fault conditions at different locations, and constructing a complete fault feature database; Step 3: Setting an inter-turn short-circuit fault at a determined location on the air-core reactor, and calibrating the data based on the measured data and the data in the fault feature database; Step 4: Calculating the measured data of the air-core reactor using a fault diagnosis algorithm to determine whether a fault has occurred in the reactor and accurately locate the fault location. This invention can diagnose inter-turn short-circuit faults and accurately locate the fault point, improving the safety and reliability of power equipment operation.

This invention discloses a method and system for magnet pose estimation based on magnetic dipole constraints. The method includes estimating the initial orientation and position of the magnet based on the triaxial magnetic field vectors measured by each magnetic sensor in a magnetic sensor array to determine the initial estimated orientation unit vector and initial estimated position of the magnet; iteratively solving the initial pose state parameters of the magnet using a nonlinear optimization algorithm based on a magnetic dipole model to obtain the final estimated orientation unit vector; obtaining the position residual and orientation residual using a pre-trained residual neural network model; and compensating the initial estimated position and the final estimated orientation unit vector based on the position residual and orientation residual to obtain the final magnet pose estimation result composed of the magnet orientation. This invention aims to overcome the influence of initial value deviation, sensor error, and environmental interference factors, improve robustness and generalization ability in complex environments, and meet the high-precision pose detection requirements of magnetic positioning.

The application belongs to the technical field of low-altitude aircraft detection, and particularly relates to a static electricity radar device for low-altitude aircraft detection and a working method thereof. The device comprises: a metal spherical shell configured to be grounded; an insulating material arranged on the surface of the metal spherical shell; a plurality of static electricity sensing electrodes embedded in the insulating material, the plurality of static electricity sensing electrodes being arrayed on the surface of the metal spherical shell, and the normal directions of the plurality of static electricity sensing electrodes converging at the geometric center of the metal spherical shell; and a signal processing module comprising a gating unit, a conditioning unit and a processing unit. The gating unit is connected to the static electricity sensing electrodes and is used for selecting specified static electricity sensing electrodes to be connected to subsequent circuits in time. The conditioning unit is configured to convert the induced charge signals into voltage signals and amplify and filter the voltage signals. The processing unit receives the digitized static electricity signals, and analyzes the spatial pose information of the low-altitude aircraft according to the signal intensity difference of different static electricity sensing electrodes. The spatial positioning of the low-altitude aircraft is realized by using the static electricity sensor array.

The application discloses a kind of deep neural network gas identification method and system based on internet of things electronic nose, gas sample response signal obtained by gas sensor array collection is sent to cloud data center by terminal equipment with sensor array and internet of things module.In the pre-processing of data to microcontroller MCU, gram angle field transformation is carried out, so that the two-dimensional sensor response data received by host computer becomes three-dimensional data that can be input into convolutional neural network after dimensionality increasing, and the gas label is output through classifier, which can represent gas category and concentration grade, realizes the real-time, anti-interference and high detection accuracy of remote monitoring.Gives play to the advantages of strong feature extraction ability, fast model convergence and high recognition accuracy of convolutional neural network.It can be widely applied in environmental detection, industrial production, medical treatment and safety fields.

This invention discloses a multi-sensor continuous ultrasonic welding monitoring method based on reinforcement learning, comprising: synchronously acquiring multi-dimensional physical signals such as vibration, pressure, energy, and displacement during the welding process using a multi-sensor array; extracting calibration features of each signal and fusing them to form a high-dimensional state vector; constructing a deep reinforcement learning network model integrating two algorithm architectures, defining corresponding state and action spaces, and setting a reward function based on quality compliance, abnormal parameter states, and adjustment amplitude; within a single welding cycle, inputting the high-dimensional state vector into the model to generate optimal parameter adjustment action commands, and adjusting the ultrasonic generator output and pressure mechanism setpoints in real time through a servo actuator to form a complete closed-loop control process. This method, through the combination of multi-sensor fusion and reinforcement learning, achieves dynamic adaptive monitoring and precise parameter adjustment of the welding process, improving welding quality consistency and process stability.

A light receiver circuit with compensation of propagation times has at least one light sensor, one control circuit, one connecting line to a TDC circuit, and a test circuit. The test line is connected to a test signal source. The test circuit connects the test line to the control circuit and forwards the test signal to the control circuit. The control circuit routes a measurement signal of the light sensor to the TDC circuit and a test signal to the connecting line and to the TDC circuit to evaluate the test signal and propagation time of test signal from test circuit to TDC circuit. The light sensor array further includes a plurality of light receiver circuits of such kind. The invention also relates to a Lidar receiver for capturing optical events with a light sensor array with a TDC circuit and a test signal source and with a timecode generator.

This invention provides a method, system, and medium for crosstalk suppression and timing optimization in high-frequency circuits. A sensor array is deployed along the critical signal path to simultaneously acquire high-frequency crosstalk spectrum and timing eye diagram parameters, generating a crosstalk intensity matrix (CIM) and a timing margin heatmap (TMM) to achieve multi-dimensional quantitative characterization of signal integrity. Based on the CIM, the main interference source is located, and the impedance of the affected line is dynamically adjusted and a reverse compensation current is injected to cancel high-frequency crosstalk at its source. The margin attenuation is predicted using a pre-trained model, and the clock phase of the affected line is fine-tuned to compensate for timing deviations. The optimized efficiency index per unit energy consumption after compensation is calculated, triggering a dynamic update or re-compensation mechanism for the strategy library. This invention achieves dynamic synergy between crosstalk suppression and timing optimization based on a closed-loop architecture composed of monitoring data, neural network prediction, dual-loop compensation, energy efficiency verification, and strategy learning.

This invention discloses a method for constant temperature and humidity control of a cigar cabinet based on a fuzzy control algorithm, comprising the following steps: setting a target temperature and humidity range; collecting environmental data of each layer through a distributed sensor array and comparing it with the target range to obtain the temperature and humidity deviation of each layer; inputting the deviation into a temperature and humidity decoupling control module and outputting a weight adjustment signal; inputting the weight adjustment signal into a fuzzy controller to construct a multi-objective fitness function, optimizing it with the WFPSO algorithm, and outputting hierarchical fuzzy controller parameters; inputting the hierarchical fuzzy controller parameters into a hierarchical temperature and humidity model to monitor the status of each layer in real time, and outputting a drive command when the limit is exceeded; inputting the drive command and hierarchical parameters into an actuator, adjusting it, and outputting new environmental data; and using a feedforward control module to adjust in advance when a door opening / closing disturbance warning is issued, dynamically adjusting the status of the affected space layer. This invention improves the temperature and humidity control accuracy and disturbance adaptability of the cigar cabinet through hierarchical optimization and feedforward intervention control mechanisms.

The invention belongs to the technical field of structural health monitoring, and particularly provides a fiber grating displacement sensing-based crack propagation real-time monitoring and early warning method and system, and the method comprises the steps: carrying out the real-time monitoring and early warning of crack propagation on the basis of strain wavelength signals collected by a fiber grating sensor array which is arranged on a miter gate in a fan shape, and employing a finite element digital twin database and a signal matching algorithm; and multi-dimensional characteristic values such as crack length, opening displacement and stress intensity factors are extracted, and the accuracy of crack state recognition is improved by combining multi-measuring-point signal fusion and fracture mechanical analysis. Through combination of gate operation load characteristics and crack propagation rules, a mapping relation between sensor data characteristics and a database is matched, and accurate identification of crack initiation, propagation paths and danger levels is realized. The monitoring and early warning system provided by the invention can realize full-life-cycle online automatic diagnosis, quantitative evaluation and early warning positioning of gate cracks from microscopic expansion to macroscopic failure, and is expected to solve the problem that the hydraulic metal structure cracks are difficult to quantitatively monitor and safely predict in real time.

The present application relates to the technical fields of mechanical engineering, and proposes a hoist head sheave operation parameter adjustment method and system based on radial runout compensation, which comprises: collecting radial runout displacement signals and steel wire rope tension signals of the head sheave in real time by using a multi-dimensional sensor array; performing empirical mode decomposition on the radial runout displacement signals to decouple low-frequency eccentric components and high-frequency deformation components of the head sheave; calculating a dynamic load change rate of the head sheave to nonlinearly correct the low-frequency eccentric components and generate a rotational speed adjustment parameter of the head sheave; generating a resonance spectrum of the head sheave, calculating a similarity between the resonance spectrum and a preset standard health spectrum, identifying a resonance main frequency band of the high-frequency deformation components when the similarity is lower than a preset similarity threshold, determining a damping stiffness adjustment parameter of a head sheave bearing seat, and combining the rotational speed adjustment parameter and the damping stiffness adjustment parameter to perform adaptive adjustment on the head sheave. The present application can improve the operation stability of the head sheave system.

This invention relates to the field of computer graphics processing and 3D modeling technology, specifically to an automated intelligent generation system for 3D modeling of shoe exteriors. The system includes: data acquisition and streaming, where an image acquisition terminal generates and sends four-channel image data using a high-precision sensor array; feature reconstruction and representation, where a topological semantic reconstruction server extracts semantic features and constructs an initial geometric representation using an implicit function based on pixel alignment and a decoder to predict the symbolic distance function; topology optimization and segmentation, where topological streamline optimization and component semantic segmentation are performed based on the curvature field to generate a structured 3D model with independent component structures; and interaction and local updates, where an interactive terminal responds to user editing operations on independent component structures, sending local topology update commands, and the server performs parametric recalculation of the local mesh based on the commands. This invention solves the problem of the separation between geometric structure and semantic information, achieving real-time and refined model updates.

An apparatus for configuring a wearable device for exercise tracking includes a data storage unit for storing sensor data generated by a sensor arrangement in the wearable device based on sensed movement of the wearable device and optical movement data including representations of an individual obtained from an image-based monitoring system; and a processing unit configured to: execute a movement tracker model on the sensor data to determine a first exercise activity and an associated first confidence indicator; execute an optical tracker model on the optical movement data to determine a second exercise activity and an associated second confidence indicator; process the movement tracker model based on the first confidence indicator and the second confidence indicator.

Systems and apparatus are provided for using a non-invasively monitored uncalibrated pressure signal from a patient to compute cardiac output and other cardio-vascular parameters, thereby providing safe, effective, reliable and low cost monitoring of patient health. Wearable devices are disclosed that include a sensor array for obtaining patient data that is used to provide an estimate of aortic systolic blood pressure, cardiac output, and end-systolic elastance that may be determined without the need for a cuff.

An anti-collision system suitable for a mobility scooter or similar comprises a sensor array, a controller and a power isolation unit. The sensor array may comprise Lidar, Radar, ultra-sonic or infra-

The application provides a generator oversize retainer ring bulging process parameter optimization method and system, relates to the plastic processing technical field, and the method comprises the steps of constructing a multi-source sensor array, synchronously collecting trace gas concentration field information and sealing gap change information, forming a leakage original data set and a wear original data set respectively, obtaining a leakage characteristic parameter and a wear amount parameter, constructing a high-dimensional feature vector based on the leakage characteristic parameter and the wear amount parameter, calculating bulging uniformity, wear unevenness, wear leakage coupling abnormality index and instability risk index according to the high-dimensional feature vector, determining a bulging process state category according to a multi-threshold-based judgment logic tree, and generating a corresponding process parameter adjustment strategy according to the bulging process state category. The technical problems of isolated multi-source sensing information, incomplete state representation, lagging abnormality identification and lack of closed-loop control mechanism are solved.

The application provides a heart magnetic signal measuring device and a measuring method, which comprises a bed body, a surrounding measuring module and a plurality of detachable sensor array modules; the surrounding measuring module comprises a first measuring plate, a second measuring plate, a third measuring plate and a fourth measuring plate; the first measuring plate is liftable, and the second measuring plate and the third measuring plate are both translatable to adapt to different body types; each measuring plate is provided with a detachable sensor array module, the positions of the sensor array modules are adjustable, and the sensor array modules are replaceable to adapt to different heart magnetic signal measuring requirements; when the heart magnetic signal is measured, the sizes of the central measuring areas are adjusted by adjusting the measuring plates to make the measuring plates as close to the human body as possible; and the optimal layout of the heart magnetic signal measuring sensor distribution area is realized by designing the sensor array modules on the measuring plates. The application can adapt to different user measuring requirements and improve the adaptability and flexibility of the measuring system.