7355results about "Force measurement" patented technology

The invention relates to the technical field of intelligent detection in the electronic manufacturing industry, in particular to a PCB warping degree intelligent evaluation system integrating visual positioning and multi-modal sensing, which comprises a multi-modal sensing unit, a visual positioning unit, an intelligent evaluation engine and a closed-loop control unit, the multi-modal sensing unit integrates laser displacement, infrared thermal imaging and strain sensors to acquire three-dimensional deformation, temperature and stress data; the visual positioning unit realizes sub-pixel-level positioning by using a high-resolution industrial camera and a feature point matching algorithm, and compensates vibration errors; the intelligent evaluation engine fuses data based on a time-space synchronization protocol, predicts a thermal deformation trend through an improved multi-modal convolutional neural network, and dynamically adjusts a qualified threshold value; and the closed-loop control unit executes sorting and rechecking according to an evaluation result, and optimizes warping and leveling parameters. According to the system, multi-dimensional accurate detection and intelligent control are realized, the PCB warping degree detection accuracy is effectively improved, the process can be dynamically optimized according to the production working condition, and the equipment fault risk is reduced.

The invention provides a forest land tree height measurement and determination method and system based on laser radar point cloud data. Stress wave signals are collected based on a trunk base acoustic emission sensor array to generate an acoustic characteristic parameter set, the digital twin model is driven to complete forest stand structure topological optimization, and a three-dimensional growth vector model reflecting the internal mechanical state of a trunk is formed. And synchronously fusing high-precision slope point cloud data returned by the unmanned aerial vehicle laser radar in real time, correcting a terrain distortion error through a dynamic splicing algorithm in combination with stress distribution characteristics, and generating a crown segmentation boundary constrained by physical characteristics. And finally outputting a tree height parameter corrected by the abrupt slope topography through model iterative optimization and space vector analysis. According to the technical scheme, synchronous sensing of the three-dimensional shape and the mechanical state of the tree in the complex terrain environment is achieved, and the tree height measurement error is reduced.

A disclosed airborne vehicle includes split-ring resonators (split ring resonators), which may be embedded within a material. Each split ring resonator may be formed from a three-dimensional (3D) monolithic carbonaceous growth and may detect an electromagnetic ping emitted from a user device. Each split ring resonator may generate an electromagnetic return signal in response to the electromagnetic ping. The electromagnetic return signal may indicate a state of the material in a position proximate to a respective split ring resonator. In some aspects, each may resonate at a first frequency in response to the electromagnetic ping when the material is in a first state, and may resonate at a second frequency in response to the electromagnetic ping when the material is in a second state. A resonant frequency of the 3D monolithic carbonaceous growth may be based on physical characteristics of the material.

The invention provides an intelligent pressure sensor temperature compensation system, and relates to the technical field of pressure sensors, and the system comprises a hardware sensing module which comprises an elastic sensitive element and is used for reducing the temperature drift magnitude of a pressure sensor; the environment data acquisition module comprises a flexible thermoelectric sensor array and is used for acquiring temperature and humidity data; the humidity correction module is used for integrating a dynamic humidity correction algorithm and establishing a cross-sensitive matrix model to correct the original signal to generate a first pressure correction signal; the temperature compensation module is used for carrying an incremental neural compensation network and constructing a compensation model to perform temperature compensation on the first pressure correction signal to generate a second pressure compensation signal; and the fault compensation module is used for triggering a digital twinborn compensation model to perform fault compensation on the second pressure compensation signal to generate a target pressure output signal when a fault of the single sensor is monitored, so that the pressure measurement error in the whole temperature range can be accurately controlled, and the environmental adaptability and the intelligent level of the system are improved.

The present invention belongs to the field of sensors, and relates to an ion gel film with a microstructure on the surface, a preparation method, and an ion-type sensor. The preparation method comprises: sandblasting on a precursor substrate to obtain a substrate, forming a mixed solution of a polymer and an ionic liquid on the substrate to obtain a wet film, and drying and curing the wet film to obtain an ion gel film, wherein the precursor substrate has an arc-shaped recess array, and the sandblasting conditions include: the sandblasting particle size is 5000 mesh to 10000 mesh, and the sandblasting pressure is 2 bar to 10 bar. The ion gel film is used for an ion-type sensor, which can improve the detection sensitivity of the sensor.

The invention discloses a bolt pre-tightening force intelligent monitoring method and system based on acoustic characteristics, and relates to the technical field of structure monitoring, and the method comprises the steps: synchronously obtaining three types of acoustic characteristic data of resonance characteristics, sound velocity ratio and nonlinear characteristics, carrying out the interactive calibration, and generating a credibility evaluation result; according to a credibility evaluation result, dynamically adjusting weight coefficients of the three types of acoustic characteristic data in a pre-tightening force calculation weight distribution strategy; inputting the weighted three types of acoustic characteristic data into a staged fusion model by adopting a staged fusion strategy to carry out pretightening force joint calculation; and establishing a long-term monitoring database, and according to deviation analysis of historical monitoring data and a real-time resolving result, updating acquired acoustic characteristic data parameters and a weight distribution strategy to form a closed-loop calibration mechanism. The technical problems of poor dynamic adaptability of multi-source acoustic characteristic data and calculation error accumulation in bolt pre-tightening force monitoring under complex working conditions are solved.

The invention relates to the technical field of stress detection, in particular to an absolute stress detection method and system for a concrete bridge, and the method comprises the following steps: obtaining stress data of a bridge girder, a support, a box girder and a main tower, collecting wind speed and wind direction sensor data, calculating a wind load gradient value, and extracting wind load primary and secondary influence regions and a transmission buffer region. And generating a wind load area stress data set. According to the method, through environmental factors and stress data, the influence of wind load on structure stress is identified, data comprehensiveness is ensured, through wind load gradient change rate calculation and stress sudden change area extraction, the structure weak point identification capability is improved, the stress fluctuation trend is quantified through time sequence analysis, and the cumulative change rate is deduced, so that fatigue damage prediction is more accurate; abnormal point identification is combined with deviation ratio analysis, measurement data is corrected, analysis reliability is improved, fatigue damage information is extracted based on stress attenuation features, local fatigue evaluation is optimized, a damaged area is accurately locked, and the accuracy of structural health monitoring is improved.

The invention discloses an instantaneous torque testing method of an aero-engine and a related system. The method comprises the following steps: dividing an engine shafting into three temperature zones, and applying acoustic excitation signals with different frequencies to obtain acoustic response signals; determining an operation phase point according to the rotating speed change rate to collect a torque response signal; acquiring inter-axis crosstalk signals to extract a response time difference and an amplitude ratio; collecting pressure field information and extracting spatial distribution and time domain evolution data; an instantaneous torque value is calculated from the signals and data. According to the technical scheme, the problem of torque signal transmission distortion caused by heterogeneous material interface stress wave reflection can be effectively solved, and the accuracy of instantaneous torque measurement is improved.

The invention provides an on-line monitoring method and system for crack propagation of silicon-based new material equipment in a high-temperature environment, and relates to the technical field of crack detection, and the method comprises the steps: collecting stress distribution data through arranging a stress sensor, and generating a stress field distribution diagram by using an attention mechanism deep neural network model; identifying a stress concentration region based on a region growing algorithm, when a stress value exceeds a preset threshold value, acquiring temperature distribution data, extracting temperature distribution characteristics through a deep mixed probability model, performing multi-modal data fusion in combination with a stress field distribution diagram, and establishing a crack propagation prediction model by using a graph structure neural network. The crack propagation rate and direction are solved through a swarm intelligence optimization algorithm, when the crack propagation rate exceeds a preset threshold value, a control system adjusts equipment operation parameters, the sampling frequency of a sensor is adjusted according to the crack propagation direction, and model parameters are updated through an incremental learning method to achieve real-time monitoring.

The invention relates to the technical field of pressure sensing, and discloses a pressure distribution data acquisition method and device, and the method comprises the steps: carrying out the calibration and signal preprocessing of a pressure sensor array, and obtaining an initial state matrix, a preprocessing parameter set, and a response curve database; calculating a pressure change rate to obtain a pressure sampling dynamic trigger threshold value and a pressure sampling control matrix; performing partition control on the pressure data acquisition process to obtain a pressure acquisition partition control model; collecting target pressure data and inputting the target pressure data into the time weighted processing network model for feature extraction to obtain multi-modal pressure distribution feature data; the multi-modal pressure distribution characteristic data is input into a closed-loop control system, and the pressure sampling parameters and the pressure processing parameters are updated to obtain a pressure acquisition control parameter set, so that high-precision pressure distribution acquisition is realized, and the limitation of a traditional method in processing non-linear and time-varying pressure signals is solved.

The invention discloses an automatic soft soil foundation settlement monitoring system based on multi-source data fusion, and relates to the technical field of soft soil foundation monitoring, the system comprises an information acquisition module, a fusion processing module, a settlement prediction module and an intelligent monitoring module; the information acquisition module is used for acquiring foundation settlement sensing data and inputting the acquired data into the fusion processing module; the fusion processing module is used for preprocessing and integrating the collected data; the settlement prediction module is used for soft soil foundation settlement prediction; the intelligent monitoring module comprises a self-adaptive processing module and an interaction alarm module, the self-adaptive processing module is used for generating an optimization strategy, and the interaction alarm module is used for carrying out user interaction and multi-mode abnormal alarm reminding. An early warning response window is provided for engineering personnel, and the occurrence rate of sudden settlement accidents is reduced.

The invention relates to the technical field of power equipment state monitoring, in particular to a lightning arrester state monitoring method, system and equipment based on multi-physics field coupling and a storage medium. Acquiring current-voltage characteristic parameters, temperature distribution data and mechanical stress data of the lightning arrester, performing electro-thermal-mechanical coupling analysis based on multi-physical field monitoring data, identifying overlapping positions of an electric field distortion area, a temperature abnormal area and a stress concentration area, and determining the overlapping positions as a degradation key area; establishing a correlation response relationship between the leakage current and the temperature and a transfer response relationship between the temperature and the mechanical stress for the deteriorated key area; on the basis of the leakage current change trend of the degradation key area and the coupling influence of the superimposed temperature field and stress field, a degradation feature fusion factor is constructed, the evolution law of the degradation feature fusion factor in the time sequence is analyzed, and the degradation threshold value under the multi-field synergistic effect is determined in combination with the electric-thermal coupling acceleration effect and the thermal-mechanical coupling weakening effect.

The present invention relates to a multi-region collaborative control method and device for a high-precision pressure sensor array. The method: based on a first collaborative sampling parameter, data is collected from multiple sensor units in a pressure sensor array to obtain a pre-processed pressure data set and a sensor unit spatial position matrix; a spatial weighted pressure covariance matrix is ​​constructed; eigenvalue decomposition and information entropy calculation are performed, and the number of target pressure points is determined according to the minimum description length criterion and the information gain ratio; a pressure feature subspace and a local perception domain are constructed; the pre-processed pressure data set is projected onto the pressure feature subspace to generate a sensor unit state data set; a multi-layer attention encoder is input for processing, and the first collaborative sampling parameter of the pressure sensor array is adjusted to obtain a second collaborative sampling parameter. The implementation of the present invention improves the system's response sensitivity to local pressure changes, thereby realizing multi-region collaborative control of pressure sensing.

A disclosed airborne vehicle includes split-ring resonators (split ring resonators), which may be embedded within a material. Each split ring resonator may be formed from a three-dimensional (3D) monolithic carbonaceous growth and may detect an electromagnetic ping emitted from a user device. Each split ring resonator may generate an electromagnetic return signal in response to the electromagnetic ping. The electromagnetic return signal may indicate a state of the material in a position proximate to a respective split ring resonator. In some aspects, each may resonate at a first frequency in response to the electromagnetic ping when the material is in a first state, and may resonate at a second frequency in response to the electromagnetic ping when the material is in a second state. A resonant frequency of the 3D monolithic carbonaceous growth may be based on physical characteristics of the material.

The invention provides a packaging and sintering evaluation method and device for a power semiconductor device, and the method comprises the steps: carrying out the non-destructive scanning through a high-frequency acoustic microtechnique, carrying out the correction through combining with a temperature-sound velocity relation model, achieving the real-time monitoring of a sintering process, and solving a problem that the transient change cannot be captured. Through frequency domain conversion and an improved inverse Fourier transform algorithm, precise reconstruction of the microstructure of the sintering interface is realized, and the limitation that the microstructure is difficult to evaluate in the prior art is overcome. Based on the reconstructed microstructure, a detailed three-dimensional geometric model is established, and time domain finite element analysis is performed, so that comprehensive thermal stress evolution data is obtained, and the defect of surface information of a traditional method is overcome. And quantitative evaluation is carried out by using the multi-dimensional feature space and the preset discrimination model, so that comprehensive analysis of the sintering quality is realized, and the defect of lack of comprehensive quantitative evaluation capability is overcome. Through organic combination of the steps, the accuracy and comprehensiveness of packaging and sintering evaluation are remarkably improved.

A disclosed leaky coaxial resonant sensor system and methods. In use, the system includes at least one split-ring resonator (SRR) embedded within a material of the component. The at least one SRR is formed from a composite material. Additionally, the at least one SRR is configured to resonate at a first frequency in response to an interrogation signal from a leaky coaxial cable antenna. In some aspects, each SRR may resonate at a first frequency in response to an electromagnetic ping when the composite material is in a first state, and may resonate at a second frequency in response to the electromagnetic ping when the composite material is in a second state. A resonant frequency of the composite material may be based on physical characteristics of the composite material.

The invention relates to the technical field of field data acquisition, in particular to an on-line temperature self-compensation calibration method and circuit for a force measurement transmitter. The calibration method comprises the steps that a working strain gauge and a temperature compensation gauge are synchronously excited through a two-way precision constant current source, the working strain gauge and the temperature compensation gauge are consistent in material parameter and are located in the same temperature field, and output current values of the two-way precision constant current source are equal and are controlled by a high-precision reference voltage source and a sampling resistor in a closed-loop mode. According to the invention, differential signals of the working strain gauge and the temperature compensation gauge are decoupled in real time through double-path precise constant-current source excitation and synchronous ADC acquisition technologies, gradient compensation is carried out on the temperature change rate in combination with a dynamic weighting algorithm, a lag error of traditional fixed coefficient compensation in a transient temperature field is effectively eliminated, and the accuracy of temperature compensation is improved. And online self-compensation of the temperature drift of the strain gauge is realized.

The invention discloses a silicon piezoresistive pressure sensor temperature compensation method and system based on IRIME-CNN-DD, relates to the technical field of pressure detection, and aims to solve the problem of low temperature compensation accuracy of an existing software compensation method. The method comprises the following steps: firstly, acquiring pressure data at different temperatures as a training data set; carrying out normalization processing on the training data set; the model parameters of the temperature compensation model are optimized through an improved rime algorithm, and the optimal model parameters are obtained; inputting the normalized training data set into a temperature compensation model, and training the temperature compensation model by using the optimal model parameters; and inputting the pressure data to be measured into the trained temperature compensation model for temperature compensation. The improved rime algorithm is used for optimization in the aspect of neural network parameter optimization, the robustness of the model is improved, local features of the temperature compensation data set are extracted through the convolutional neural network, and the sensitivity of the pressure sensor is further improved.

The invention provides a composite board detection method and system, and relates to the technical field of board detection, and the method comprises the steps: carrying out the ultrasonic scanning of a composite board, dividing the composite board into a plurality of acoustic characteristic layers, building a sound wave propagation model based on a recursive transfer matrix method, and calculating the reflection coefficient and transmission coefficient of each layer interface. A deep learning algorithm is combined with physical constraints to dynamically correct acoustic parameters, the corrected parameters are substituted into a model reconstruction signal, and defects are accurately positioned. And performing grid division on the defect position to analyze stress field distribution, and determining a stress concentration position. And fine scanning is carried out on a stress concentration area by adjusting probe parameters, and high-resolution data is obtained to update defect distribution information. And finally, outputting detection data including defect positions, stress concentration distribution and hazard levels, and realizing accurate detection and evaluation of the defects of the composite board.

The invention discloses a curved surface stress detection method, which comprises the following steps of: 1, fixing a detected piece on an object placing table by using a self-adaptive clamp; step 2, scanning the measured piece to generate three-dimensional shape data of the measured piece; 3, calibrating the initial position of the measured piece by a displacement sensor, and establishing a coordinate system; step 4, adjusting the position of the measured piece by using a self-adaptive clamp, emitting X-rays to the measured piece by using an X-ray tube, and collecting diffraction signals by using a second detector; and step 5, the calculation module calculates the stress distribution state of the measured piece. According to the curved surface stress detection method, the problems of low irregular surface positioning precision and poor adaptability of traditional equipment are solved, and the detection efficiency and reliability are remarkably improved.

Disclosed are various embodiments for a sensor enabled geogrid for the monitoring and detection of subgrade deformation in infrastructure such as roadways, railways, working platforms, and marine applications. The system and methods contain a sensor enabled geogrid, inertial measurement units (IMUs), one or more sensors, a data collection apparatus such as a sensor pod, an information transmission apparatus such as a gateway device, a communications network, and a computing device capable of performing analytics on information from the IMU's and other sensors. The disclosure further includes methods of processing information received from a sensor enabled geogrid by a sensor pod. In the example, the sensor pod transmits received information to a gateway device for transmitting to a backend computing system. The backend computing system then performs an analysis on the information to determine variance from an initial sensor position, and alerts of possible infrastructure failure.

According to the-40 DEG C to 600 DEG C anti-explosion online stress monitoring system and the stress monitoring method provided by the invention, a high-temperature-resistant alloy substrate of the stress monitoring system eliminates thermal expansion difference through seamless welding, and dynamically corrects thermal drift error in combination with a temperature compensation algorithm, so that the monitoring precision at an extreme temperature is ensured; the direct electrical connection between the power management module and the signal processing module is cut off by adopting a magnetic coupling isolator, the energy consumption of the monitoring module is dynamically managed through a time-sharing power supply strategy, the power consumption is reduced to the maximum extent, the total energy consumption of the system is compressed to be within an anti-explosion authentication threshold value, and the real-time monitoring and rapid alarm capability of high-risk equipment is guaranteed. According to the utility model, the system endurance is obviously prolonged, the contradictory requirements of safety protection and energy consumption control are effectively balanced, remote data transmission without manual intervention is realized through the RS485 communication module, and the personnel safety is ensured.

The invention relates to the technical field of ship propulsion system monitoring, in particular to a shafting load analysis method based on real-time data monitoring, and the method comprises the following steps: S1, collecting a pressure parameter and a displacement parameter of a shafting; s2, performing timestamp alignment and data frame encapsulation to generate a synchronous data stream; s3, shafting natural vibration noise and real load signals are separated, and shafting real-time torque distribution is calculated; s4, if the torque distribution deviates from the correction threshold value, graded early warning is triggered; and S5, generating an interactive report according to the triggered early warning level and the torque distribution result. According to the invention, through multi-sensor synchronous acquisition, edge calculation data alignment, vibration noise decoupling, dynamic safety threshold adjustment and intelligent fault tracing analysis, high-precision monitoring, abnormity early warning and intelligent maintenance of the shafting load are realized, and the safety and operation and maintenance efficiency of ship operation are improved.

Various embodiments are directed to sensor apparatuses and methods thereof. An example sensor apparatus includes a plurality of capacitors and sensor circuitry. The plurality of capacitors including a first substrate having a plurality of first electrodes, a second substrate having a second electrode, and a dielectric material, and with the plurality of first electrodes and the second electrode being separated by the dielectric material. The plurality of first electrodes are aligned with respect to the second electrode such that each of plurality of first electrodes form one of the plurality of capacitors with the second electrode. The sensor circuitry is coupled to the plurality of capacitors to differentiate between normal and shear forces applied to apparatus based on a pattern of impedance responses of each of the plurality of capacitors formed by the second electrode and the plurality of first electrodes.

The invention relates to the technical field of material mechanical property testing, in particular to a method for measuring residual stress of a metal component. According to the technical scheme, the method for measuring the residual stress of the metal component comprises a working process for measuring the residual stress of the metal component; according to the method, a technical path of multi-modal data assimilation is adopted, and a mechanical release mechanism of a drilling method and an ultrasonic stress measurement technology are deeply fused to calibrate and correct mass sound velocity data obtained by carrying out rapid ultrasonic scanning on the whole component on site, so that the precise measurement of the residual stress state of the metal component is realized, and the measurement precision is improved. According to the method, data authority and high credibility of a drilling method in a key area are reserved, the advantages of high efficiency and wide coverage of full-field measurement of an ultrasonic method are brought into full play, and efficient and accurate stress information is provided on the premise that components are not excessively damaged.

A system determines the position of a seatbelt in a crash test using a pressure sensing garment affixed to a crash test dummy. The pressure sensing garment is a surface or material configured to measure pressure applied to the crash test dummy during a crash test. The pressure sensing garment measures pressure applied to the crash test dummy using a capacitive sensor grid. The system determines the position of the seatbelt based on the pressure data from the pressure sensing garment and may apply various algorithms to automatically determine the angle and centerline of the seatbelt based on the pressure data.

The invention provides a method and a device for evaluating and measuring microscopic mechanical properties of TC4 alloy, relates to the technical field of microscopic mechanical properties, and realizes accurate evaluation of material properties through combination of multi-scale characterization and numerical simulation. Firstly, a standard sample is prepared through selective laser melting, and residual stress field distribution is obtained through X-ray diffraction; dividing a stress field into sub-regions, and establishing a quantitative relationship between microscopic structure parameters and residual stress by combining SEM and EBSD analysis; the method comprises the following steps: acquiring local mechanical properties through a nanoindentation test, and constructing a stress-performance correlation model; and finally, establishing a finite element model, transmitting stress and tissue parameters by adopting trilinear interpolation and an inverse distance weighting method, verifying data reliability through a stress difference criterion, and calculating mechanical properties of each unit. According to the method, multi-scale correlation from microstructure characteristics to macroscopic mechanical properties is innovatively realized, so that the mechanical property distribution of the material is accurately evaluated.

The invention discloses a preparation and measurement method of a polymer-based multi-point force flexible sensor for knee joint pose measurement, and relates to the technical field of polymer-based flexible sensors and soft measurement. The structure of the multi-point force polymer-based flexible sensor shaped like a Chinese character'ao 'is designed for knee joint stress and posture state measurement, and the flexible sensor is prepared and packaged through a silk-screen printing method. A flexible sensor strain input-output knee joint stress data mapping set and a flexible sensor strain input-pose angle output data mapping set required by modeling are completed through a flexible sensor, a thin film force sensor corresponding to multi-point force and an inertial sensor corresponding to pose angle measurement of installed multi-point force polymers. And establishing a neural network soft measurement model based on an MLP algorithm, and carrying out training and verification. And the knee joint pose angle with reliable precision and the maximum stress state of the knee joint are obtained. The sensor has the advantages of being flexible, thin, skin-friendly, high in sensitivity and stable in signal output.

The present application discloses an anti-crosstalk sensing circuit of a capacitive pressure sensing array and a sensing method thereof, which relates to the field of capacitive pressure sensing technology. The circuit alternately inputs a positive excitation voltage and a negative excitation voltage at the driving end of each row of pressure sensing capacitors through a row selection state, and the detection end of each column of pressure sensing capacitors is respectively connected to the inverting input end and the reference voltage of the corresponding operational amplifier according to the column selection state, and obtains a first detection voltage and a second detection voltage corresponding to the positive excitation voltage and the negative excitation voltage output by the output end of the operational amplifier, respectively, and calculates the capacitance value of the pressure sensing capacitor of the target row based on the amplitude of the positive excitation voltage and the negative excitation voltage, the first detection voltage and the second detection voltage, and the capacitance value of the reference capacitor. The present application can prevent the crosstalk phenomenon between the same row or the same column of the capacitive pressure sensing array, and significantly improve the detection accuracy of the sensing circuit of the capacitive pressure sensor array for the sensing capacitor.