546 results about "Pressure sensor array" patented technology

The invention relates to the technical field of pressure sensing, and discloses a pressure mapping method and device for a high-precision pressure sensor array. The method comprises the steps that known standard pressure is applied to a high-precision pressure sensor array, and an original pressure distribution matrix of each sensing unit is collected; executing bicubic spline interpolation operation of tension coefficient compensation to obtain a continuous pressure distribution matrix; inputting a depth separable convolutional network to perform spatial feature extraction and channel feature fusion to obtain a pressure feature description matrix; carrying out confidence coefficient propagation iterative calculation to obtain a pressure confidence coefficient matrix; carrying out reliability grouping and weight coefficient calculation on the sensing units to obtain a pressure data fusion weight matrix; according to the method, the pressure mapping precision is improved, relatively high real-time performance is ensured, and the problems of data distortion, low calculation efficiency and insufficient reliability in a traditional method are solved.

The invention relates to the technical field of fluid control, and discloses a fluid control intelligent adjusting method and system for a micro-fluidic chip, and the method comprises the steps: carrying out the data collection of a self-adaptive fluid controller, a micro-fluidic channel pressure sensor array, a temperature sensor array and a flow sensor array based on the micro-fluidic chip; obtaining real-time fluid parameter monitoring data; performing feature extraction to obtain a multi-dimensional fluid feature matrix; establishing a three-dimensional fluid model of the microfluidic channel, and solving to obtain flow field distribution data; inputting the flow field distribution data into a Kriging agent model, establishing a mapping model of channel width, depth, length and fluid control performance, and calculating to obtain an optimal geometric parameter combination; and performing multi-level calculation on the fluid pressure uniformity, the temperature distribution uniformity and the flow stability to obtain a hierarchical fluid parameter control strategy. According to the invention, the problem of multi-physics field coupling is effectively solved, the calculation complexity of the control system is reduced, and the execution efficiency of the control strategy is improved.

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 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.

The invention relates to the technical field of high-precision pressure sensing, and discloses a pressure response data calibration method and device and computer equipment, and the method comprises the steps: collecting the output response data of a pressure sensor array, and constructing a spatial feature matrix, a time feature matrix and an environment feature matrix based on the output response data; performing trilinear least square separation to obtain dynamic response data and time characteristic data; performing symmetric geometric mode decomposition to obtain linear response component data, periodic fluctuation component data and nonlinear characteristic component data; inputting a multi-branch gating circulation unit network model to carry out dynamic calibration strategy prediction to obtain a first dynamic calibration strategy; performing particle swarm iterative optimization to obtain a second dynamic calibration strategy, and generating a progressive calibration parameter set; static and dynamic pressure sensing calibration is performed on the pressure sensor array to obtain a comprehensive pressure sensing calibration result, so that the accuracy of pressure sensing calibration is improved.

The invention discloses an underground coal bunker unblocking system. The underground coal bunker unblocking system comprises a spiral conveying drill rod, a drill rod driving device, an intelligent monitoring module and a control module, the drill rod is arranged on the inner wall of a coal bunker, the gap between the outer edge of a drill rod blade and the inner wall of the coal bunker is smaller than 10 mm, and the drill rod driving device is connected with the drill rod to drive the drill rod to rotate. The intelligent monitoring module integrates a pressure sensor array, an infrared coal flow detector and an image recognition camera and is used for monitoring the blocking state in a coal bunker in real time, and the control module dynamically adjusts the rotating speed and the rotating direction of the spiral conveying drill rod according to monitoring data. According to the underground coal bunker unblocking system, through the collaborative design of spiral drill rod structure optimization, anti-explosion power driving, a multi-mode sensing network and intelligent decision control, the unblocking efficiency of the coal bunker and the safety of unblocking operation are improved, the monitoring means are comprehensive, the blocking state can be accurately judged in real time, control response is timely, and the unblocking efficiency of the coal bunker is improved. And complex working conditions can be adapted.

The invention discloses an AI intelligent control pressure sore prevention self-adaptive mattress system which comprises a mattress body provided with a polymer support column structure covering in all directions and designed into a plurality of areas, and the areas are accurately divided to support a human body and disperse pressure; the sensor array module is used for recording monitoring data of contact between each part of a human body and a plurality of areas of the mattress body in real time; the AI chip control module integrates an advanced algorithm and a processor and is used for receiving and analyzing the monitoring data from the sensor and sending out a control instruction based on an analysis result; and the database management module is used for storing monitoring data of patients with different weights, heights, ages and body positions and is used for predicting and early warning pressure sore risks. According to the invention, pressure sore risk areas can be accurately identified in a zoning manner, pressure, temperature and humidity information can be monitored in real time, and meanwhile, a proper pressure state is automatically adjusted, so that the occurrence of pressure sores is effectively prevented.

The invention relates to the technical field of steel structure welding assembly, and discloses a dynamic cooperative control steel structure welding assembly production line and an operation method thereof, which are used for automatic welding and deformation correction of H-shaped steel components. The production line comprises a feeding area, an assembling area, a welding station and a correction detection area. Global cooperative control is achieved through a distributed supporting system, a multi-dimensional sensor monitoring system and a cooperative robot system. The distributed supporting system is composed of dynamic roller bed units, the supporting height is adjusted in real time through a pressure sensor array and a micro hydraulic actuator, and workpiece droop is counteracted. The multi-dimensional sensor monitoring system collects temperature, strain and morphology data in real time; the welding robot and the correction robot synchronously apply electromagnetic stirring to optimize a welding seam during welding, and ultrasonic peening and laser heating are combined to reduce residual stress during correction. The industrial control computer dynamically adjusts welding parameters, supporting force and a correction strategy through sensor data, and high-precision straightness and low-residual-stress control is achieved.

The invention relates to the field of oral medical diagnosis, and discloses an intraoral image-based AI enhanced real-time occlusion detection system, which comprises a multi-source intraoral image acquisition module for acquiring dynamic oral image data through a high-definition oral endoscope and recording a three-dimensional structure of a tooth surface by combining a laser scanning device, meanwhile, force distribution of an occlusion contact point is collected through a pressure sensor array; the multi-source intraoral image acquisition module comprises a timestamp synchronization unit and is used for performing multi-source synchronization on an oral image frame sequence and occlusal force distribution data by utilizing a unified timestamp; through the multi-source in-port image acquisition module, synchronous acquisition of dynamic images, three-dimensional structure data and bite force distribution is realized, and time sequence consistency of the data is ensured through timestamp marking. Compared with a traditional single data source collection mode, the multi-source collection can comprehensively record dynamic characteristics in the occlusion process, rich and accurate input is provided for subsequent AI analysis, and data missing or collection deviation is avoided.

The invention discloses a hydropower station expansion tank water level prediction alarm method and system, belongs to the technical field of hydropower station automatic control, and aims to solve the technical problems of limited monitoring points, high false alarm rate, response delay and the like of a traditional hydropower station expansion tank water level alarm system. According to the invention, the multi-mode sensing network is constructed, and data of the pressure sensor array, the radar level meter and the float switch group are fused, so that space continuous monitoring is realized; a three-level sensing architecture is adopted, heterogeneous data is subjected to normalization processing, and dimensional differences are eliminated; the LSTM network is used for liquid level prediction, and a self-adaptive window adjustment mechanism is combined, so that the prediction flexibility and accuracy are improved; a DQN algorithm is adopted to optimize a control strategy, fine adjustment of the liquid level is achieved by adjusting the opening degree of the valve, the accuracy, timeliness and intelligent level of water level monitoring and alarming of the expansion water tank of the hydropower station are remarkably improved, the stability of the liquid level of the water tank is ensured, the system operation efficiency is optimized, the manual intervention requirement is reduced, and safety is improved.

The invention relates to the technical field of intelligent forming, in particular to an intelligent adjusting type medical cotton ball forming method and system.The intelligent adjusting type medical cotton ball forming method comprises the following steps that pressure data are collected through a distributed pressure sensor array, pressure feature vectors are generated through Gaussian filtering denoising, a pressure change trend is analyzed based on the feature vectors, and a gradient adjusting instruction is output; and controlling the valve to adjust air pressure to obtain compensation parameters, driving the servo motor to adjust a mold gap, collecting offset data to generate a feedback signal, and inputting a neural network to evaluate a forming result in combination with feedback and adjustment instructions. According to the method, a distributed sensor array collects data, multi-dimensional denoising improves feature extraction, a dynamic function analyzes a pressure trend, an offset adjustment parameter is identified, closed-loop compensation is realized through cooperative control, a displacement sensor feeds back gap change, parameter modeling optimizes precision consistency, a convolutional network extracts time sequence features, and a self-adaptive system is constructed through fusion analysis. And intelligent prediction and optimization of the forming quality are realized.

The invention discloses a pressure injury risk early warning method and equipment, and relates to the technical field of medical monitoring instruments. The pressure sensor array layout can be self-adaptive to the body shape of a patient, a key osseous process part is covered, no monitoring dead angle is ensured, a temperature compensation mechanism is built in, environmental interference is reduced, the measurement precision is improved, an abnormal pressure threshold value can be dynamically set based on individual medical record data, data verification is performed before early warning is triggered, false alarm is avoided, and the array structure is light, thin and flexible. The mask is comfortable to fit skin, supports long-term wearing and is easy to disinfect and maintain; environment temperature and humidity parameters and pressure data are subjected to fusion analysis, the influence of a high-temperature and high-humidity environment on skin microcirculation can be recognized, the risk of pressure sores can be evaluated in an auxiliary mode, a calibration algorithm is built in a sensor, environment fluctuation interference is reduced, and data reliability is ensured; and the early warning unit comprises sound-light alarm equipment which supports a multi-stage alarm mode and is used for triggering an early warning signal and pushing information when the risk index exceeds a threshold value, so that the early warning timeliness is ensured and the false alarm risk is reduced.

The invention provides an intelligent pillow and a control method thereof, and belongs to the technical field of intelligent home furnishing.The intelligent pillow comprises a pillow body, the pillow body is provided with a snore stopping air bag, a pressure sensor array, a microphone line array and a control box, the snore stopping air bag is connected with an air pump through an air pipe, and the control box is in signal connection with the air pump; the pressure sensor array is in signal connection with the control box, and the pressure sensor array is used for collecting head pressure signals of a user and transmitting the head pressure signals to the control box; the microphone line array is in signal connection with the control box, and the microphone line array is used for collecting sound signals of a user and transmitting the sound signals to the control box so as to judge the snoring state of the user; the snore stopping air bag corresponding to the head position of the user is adjusted to change the external form of the pillow body, so that the head position of the user is changed. The snore problem of the user can be effectively relieved, and the sleep quality of the user is improved.

The invention discloses an oil storage tank oil-water interface measurement system and method and a storage medium, and relates to the technical field of oil-water interface measurement, and the system comprises a data acquisition module, a data processing module, a decision support module and a data security module. According to the oil-water interface measuring system and method for the oil storage tank and the storage medium, a three-dimensional sensing network (distributed sensor network) is constructed by adopting a pressure sensor array and phased array ultrasonic scanning technology and combining dielectric property detection of a microwave dielectric constant sensor; the pressure, the dielectric constant, the liquid level and the vibration data in the tank body are obtained, basic data are provided for subsequent processing, the comprehensiveness of data obtaining can be improved through the sensing network, the pressure data are dynamically calibrated through Takagi-Sugeno fuzzy logic, the influence of temperature drift is effectively eliminated, and the accuracy of data obtaining is improved. The ultrasonic signals are subjected to feature enhancement through the generative adversarial network, and the emulsion layer boundary is accurately recognized.

The invention discloses an unmarked motion capture system integrating a pressure sensor array and a depth camera, which belongs to the field of computer vision and comprises a depth camera module, a plantar pressure sensor array module, a data summarization module, a joint point calibration module, a three-dimensional force prediction module and a posture simulation module. The system collects and summarizes positions of human body joint points and pressure distribution data of planta pedis, extracts foot feature points, calibrates the human body joint points to obtain kinematics data, predicts ground reaction force in combination with planta pedis pressure distribution, and uses the calibrated kinematics data and predicted three-dimensional ground reaction force data to predict the three-dimensional ground reaction force. And carrying out human kinematics and dynamics simulation. The system provided by the invention can accurately position the spatial position of the human body joint point, accurately collect the pressure distribution and the ground reaction force in the human body movement process, and improve the accuracy of kinematics and dynamics analysis of the human body.

The invention relates to the technical field of health care, and discloses a bath chair self-adaptive adjusting system based on multi-modal sensing. According to the system, a pressure sensor array, an infrared thermal imager and an inertial measurement unit are used for collecting multi-dimensional real-time data, and the multi-modal sensing fusion module is used for processing the multi-dimensional real-time data to generate a structured physiological feature vector. The user intention recognition module predicts user behavior intention and gives a comfort level score on the basis, and the posture self-adaptive adjustment module optimizes seat supporting curved surface parameters according to the comfort level score to achieve real-time adjustment. In addition, the safety monitoring module evaluates the slip risk, the closed-loop control module guarantees safety, the online learning module optimizes the adjustment strategy, and the abnormal response module deals with the emergency situation. According to the system, the comfort and safety of the bath chair are improved, personalized adjustment is achieved, and the system has high practical value.

The invention discloses an adaptive multi-angle elbow airtightness detection method, which comprises the following steps: arranging a flexible pressure sensor array and a micro inertial measurement unit on the inner wall of an elbow, collecting multi-point sealing pressure and attitude signals in real time, fusing geometric parameters and a spatial mapping relation, and completing denoising, normalization and multi-curvature region mapping of pressure data; a distributed pressure-attitude database is combined, a function model associated with sealing pressure and pipeline geometric parameters is established, inflation, exhaust and deformation of each node are dynamically adjusted through an intelligent closed-loop regulation and control algorithm, collaborative optimization of multi-node pressure and a fitting state is achieved, and the sealing performance of the pipeline is improved. According to the method, the accuracy and the self-adaptive adjusting capacity of sealing pressure distribution under a complex bent pipe structure are effectively improved, the tiny leakage real-time positioning and self-learning optimization capacity is achieved, and the method is suitable for sealing quality guarantee of various types of curved surface pipelines.

The invention relates to the technical field of medical treatment, in particular to a multi-parameter collaborative infusion process intelligent monitoring and priority calling method, which comprises the following steps of: acquiring four-dimensional monitoring data through a liquid level pressure sensor array, an infrared dripping speed detection module, a flexible temperature patch and a photoelectric heart rate sensor, and combining an LSTM (Long Short Term Memory) anomaly prediction model, and outputting the pipeline state score, the allergy risk index and the infusion progress prediction value in real time. And generating a real-time risk value through a weight configuration mechanism and stage identification logic, judging a risk level according to a dynamic threshold value, and outputting a corresponding early warning level signal. And the system further maps the early warning level signals into common, emergency and critical call instructions, and distributes the common, emergency and critical call instructions to a multi-channel execution terminal to construct a multi-level linkage response mechanism of closed-loop feedback. According to the invention, the accuracy and response efficiency of infusion risk identification can be significantly improved, and the method is suitable for intelligent reconstruction and automatic early warning response scenes of a clinical nursing information system.

The invention discloses an embedded liquid metal microstructure electrode, a flexible pressure sensor array and a preparation method. The technical problems that an existing flexible pressure sensor array is low in sensitivity, large in crosstalk and the like are solved. Wherein the embedded liquid metal microstructure electrode comprises a first flexible substrate, a first liquid metal layer and a first packaging layer; the lower surface of the first flexible substrate is a plane, and a plurality of micro-cone structures arranged in an array are uniformly distributed on the upper surface of the first flexible substrate; the cone part of each micro-cone structure faces upwards and is flush with the upper surface of the first flexible substrate; the first liquid metal layer covers the upper surface of the first flexible substrate and all the micro-cone structures; the first packaging layer covers one surface, far away from the upper surface of the first flexible substrate, of the first liquid metal layer; meanwhile, the invention further provides a preparation method of the microstructure electrode, a flexible pressure sensor array based on the microstructure electrode and a preparation method of the flexible pressure sensor array, and the flexible pressure sensor array is high in sensitivity and low in crosstalk.

The invention discloses an intelligent cleaning robot dynamic negative pressure dust removal system based on pressure feedback. The intelligent cleaning robot dynamic negative pressure dust removal system comprises a centrifugal fan, a pressure sensor array and a control system. The centrifugal fan adopts a variable frequency speed regulation technology, so that the suction force of 500-3000Pa is dynamically adjustable; an array composed of six sets of miniature pressure sensors is arranged at a dust collection opening, and the airflow pressure difference between the air inlet end and the air outlet end is monitored in real time. The control system is integrated with a blockage self-detection algorithm, when the pressure difference exceeds a preset threshold value 0.5 kPa, a compressed air pulse back flushing program lasting for 0.2 second is triggered, and meanwhile the fan power is adjusted in a self-adaptive mode till blockage is removed. The system solves the problem that the efficiency is suddenly reduced after a traditional dust collector is blocked through a pressure feedback mechanism and an intelligent control strategy, and self-maintenance of the dust collection efficiency is achieved. Experiments show that in dust-intensive scenes such as station waiting halls, the dust removal efficiency is improved by 35% compared with that of a traditional system. The intelligent cleaning robot has the functions of real-time pressure monitoring, dynamic negative pressure adjustment and blockage self-repairing, the working efficiency and reliability of the cleaning robot in the complex environment are remarkably improved, and the intelligent cleaning robot is suitable for being used as intelligent cleaning equipment in families, public places and the industrial field.

The invention discloses an inductor assembling method, which relates to the technical field of electronic components and comprises the following steps: arranging a positioning disc with array holes on a positioning tray bracket, filling magnetic cores into the array holes and then fixing the magnetic cores through a magnetic plate, and detecting the positions of the magnetic cores by a visual system; a glue scraping screen plate covers the positioning disc and is aligned with the positioning disc through a three-point positioning mechanism, and multi-area synchronous gluing is conducted through an intelligent gluing control system; the intelligent gluing control system adjusts gluing parameters according to detection data of the visual system; a pressure sensor array and an elastic pressure mechanism are adopted to synchronously press the glued magnetic core, the pressure sensor array collects pressure distribution data, and the pressure distribution data are processed through a pressure equalization algorithm to control pressure distribution of batch assembly. The invention also discloses a method.

The invention relates to the technical field of mechanical vibration and fluid excitation coupling effect analysis, in particular to a runner crown modification pressure pulsation amplitude measurement method, which comprises the following steps of: extracting pressure gradient distribution and cavitation phase change characteristic parameters of a runner surface through fluid dynamics simulation; targeted arrangement of a high-frequency pressure sensor array in a vortex core area, a boundary layer separation critical position and a modification structure mutation area is guided, and the signal acquisition precision is improved by adopting an annular encryption and axial equal-interval arrangement strategy. And establishing a dynamic error feedback mechanism of actual measurement and simulation. And verifying an abnormal frequency band proportion through frequency domain kurtosis and analyzing envelope spectrum harmonic waves, and screening a modification parameter combination with the pressure pulsation amplitude decreasing to reach the standard and stable frequency band distribution. According to the method, the problem of measurement errors caused by multi-source high-frequency noise and effective signal frequency domain aliasing is solved, a high-precision quantification basis is provided for runner modification optimization, and the method is suitable for the field of mechanical system dynamic characteristic testing.

The invention relates to the technical field of intelligent control of injection molding machines, in particular to an injection molding machine closed-loop mold adjustment control system and method based on multi-sensor fusion and a self-adaptive algorithm, and the system comprises a sensing layer which adopts a multi-sensor fusion closed-loop feedback architecture and comprises a pressure sensing array, a displacement sensing unit and a temperature sensing array. The data acquisition module is used for synchronously acquiring mold clamping force, position and temperature data of a mold, constructing a three-dimensional error compensation model and realizing dynamic correction of the parallelism of the mold through space force field analysis; the execution layer comprises a servo motor, a belt wheel and a ball screw and is used for adjusting the position of the template; a double-closed-loop control module is arranged in the control layer, the double-closed-loop control module comprises outer ring mold clamping force control and inner ring position control, mold clamping force deviation serves as input of an outer ring, position correction is generated through a self-adaptive PID algorithm, the inner ring converts the position correction into a servo motor rotation angle instruction, and therefore precise control over the mold clamping force is achieved.

The invention discloses an emotional interactive intelligent nursing system and method based on multi-modal perception, and belongs to the technical field of intelligent medical treatment and intelligent old-age care crossing. The matrix type pressure sensor array is integrated in the nursing mattress, multi-point pressure distribution of the body of the old people on the bed surface is obtained in real time, and high-resolution body pressure mapping is achieved. Compared with an existing single-point type or linear pressure monitoring structure, the system can accurately recognize the spatial position of a local pressed area, and early recognition and quantitative evaluation of a bedsore risk area are achieved. By fusing the pressure matrix, the heart rate, the blood oxygen, the environment temperature and humidity, the urine wetting and other multi-mode sensing data, the monitoring dimension is remarkably expanded, the health condition can be comprehensively evaluated from multiple physiological indexes, compared with a single physiological parameter monitoring mode, the more comprehensive information obtaining capacity is achieved, and the monitoring precision and the nursing efficiency are effectively improved.

The invention provides a multi-modal monitoring integrated intelligent massage bed sleep analysis method, and relates to the technical field of data processing, pressure information of a plurality of positions at a plurality of moments is collected through a pressure sensor array, pressure comfort analysis of a user is carried out, and a plurality of pressure comfort levels are obtained; electromyographic signals of a plurality of main body positions of a user at a plurality of moments are collected through an electromyographic signal sensor array, and a plurality of electromyographic signal arrays are obtained; according to the multiple pressure comfort levels, multiple electromyographic signal completion generation scales are configured, completion generation is conducted on the multiple electromyographic signal arrays, and multiple completion electromyographic signal arrays are obtained; and according to the plurality of complemented electromyographic signal arrays, performing electromyographic comfort analysis of the user, and calculating to obtain the comfort of the user. The technical problems that in the prior art, a sleep analysis detection signal source is single, deep analysis on the body state of the user is lacked, and evaluation on the sleep state of the user is not comprehensive enough are solved, and comprehensiveness and accuracy of sleep analysis are improved.

The invention provides an intelligent pillow control method and system, and belongs to the technical field of intelligent control. The method comprises the steps that an FPGA obtains a user sleeping posture data set collected by a pressure sensor array; and determining a current sleep stage based on the user sleep posture data set and a pre-trained sleep stage recognition model. According to the user sleeping posture data set, the historical sleeping posture data set and a preset cervical vertebra supporting curve, a first correction target parameter matrix corresponding to the current cervical vertebra curvature deviation value of the user is determined; wherein the first correction target parameter matrix comprises first correction target parameters corresponding to air bags in different areas of the intelligent pillow; the first correction target parameter is the airbag pressure adjustment amount dynamically constrained by the receptor dynamic frequency; and based on the current sleep stage and the first correction target parameter matrix, determining a corresponding airbag adjustment parameter group, operating an airbag driving module according to the airbag adjustment parameter group, performing airbag pressure adjustment, and updating the first correction target parameter matrix according to the real-time body movement frequency.

The invention provides an unmanned aerial vehicle group cooperative suppression method and system based on a distributed antenna array, electronic equipment and a storage medium, and relates to the technical field of unmanned aerial vehicle group cooperative suppression and anti-interference control. Obtaining airflow pressure distribution information; performing vortex field calculation processing on a fluid motion state by using the information to generate vortex field information containing a disturbance area; dynamically adjusting the phase of the antenna array element based on the eddy current field information, compensating the physical deformation of the array and outputting a compensation result; performing cooperative phase correction processing on distributed antenna array beam pointing by using the result to generate a beam phase compensation amount; and finally, cooperative regulation and control processing is performed on the unmanned aerial vehicle group emission signals based on the compensation amount, and an anti-disturbance suppression wave beam pointing to the target is generated. And continuous directional suppression on a moving target in a strong wind disturbance environment can be realized.

The invention discloses a dexterous hand perception control method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps that under the condition that a target multi-fingered dexterous hand grabs a target object is recognized through a pressure sensor array, pressure collection data are obtained from a pressure sensor array, and current joint data of all finger joints of the target multi-fingered dexterous hand are obtained from an encoder; according to the pressure collection data and the current joint data, the current grabbing state of the target multi-fingered dexterous hand is determined; when it is recognized that the current grabbing state does not meet the safe grabbing condition, dexterous hand pose data of the target multi-fingered dexterous hand are obtained from an inertial sensor, and a target grabbing mode of the target multi-fingered dexterous hand is determined according to the current space pose data, the pressure collection data, the current joint data and the dexterous hand pose data; and the target multi-fingered dexterous hand is controlled to grab in a target grabbing mode. According to the scheme, the sensing grabbing efficiency and accuracy of the dexterous hand are improved.

The invention discloses an aircraft airfoil pressure self-adaptive calibration method for a wind tunnel environment, belongs to the technical field of pressure sensors, and aims to solve the problem that the sensitivity of the sensors is reduced during aircraft airfoil pressure testing. Comprising the steps that a flexible pressure sensor array is installed in a matched mode according to the airfoil shape of a to-be-tested aircraft, the to-be-tested aircraft is placed in a wind tunnel, wind tunnel parameters are adjusted, and pressure signals in a multi-scene environment are generated; each pressure sensor unit is regarded as an independent agent, and a calibration model is constructed by using an MADDPG algorithm; an Actor-Critic network architecture of multi-agent cooperative training is designed and obtained; and performing model compression on the trained Actor network, deploying the Actor network to an embedded system, fitting a nonlinear mapping relation between output of a pressure sensor unit and a real pressure value in real time, correcting a nonlinear error, and performing dynamic compensation on zero drift. The method is used for aircraft airfoil pressure distribution testing.

The invention relates to the technical field of curtain walls, and discloses a curtain wall hyperbolic unit piece profiling jig framing method. Comprising the steps that a profiling backup plate and a profiling supporting plate are connected to form an integrated profiling base body; a pressure sensor array is arranged in the profiling supporting plate and used for detecting node stress distribution of the profiling supporting plate. A positioning U-shaped groove and a limiting steel plate are mounted on the profiling supporting plate; the structural supporting rods are vertically fixed to the surface of the standard part cast iron platform, so that a plurality of assembly supporting devices are arranged on the surface of the platform; the hyperbolic profile is embedded into the curved surface contour of the profiling backup plate of each assembly supporting device along the positioning U-shaped groove for profiling, leaning and positioning, and the clamping force corresponding to the limiting steel plate is adjusted according to the node stress distribution; and the hyperbolic profile is embedded into the curved surface contour of the profiling backup plate along the positioning U-shaped groove for profiling, leaning and positioning, the clamping force corresponding to the limiting steel plate is adjusted according to node stress distribution, framing positioning is completed, and the curtain wall hyperbolic unit piece profiling jig is obtained. The method is accurate in positioning and simple to operate.