501 results about "Pressure sensor array" patented technology

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 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 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 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 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 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.

The invention relates to the technical field of fabric testing, in particular to an experimental testing method and device for determining the impact resistance of fabric, and the method comprises the following steps: S1, initial calibration: installing the fabric to be tested on a fabric frame, adjusting the tension of the fabric to be tested to a set value through a first electric push rod, starting an electromagnetic suction table to compress a spring to an energy storage state, and starting a second electric push rod; the pressure sensor array module is impacted by a bullet launched in a no-load mode, the process is repeated three times, an impact force calibration value is obtained, and the speed measurement sensor is synchronously calibrated, and S2, testing position switching is conducted, and liquid agar gel is injected into the transparent gel cylinder. According to the invention, through a unique spring system, the linear transmission module is utilized to drive the electromagnetic suction table to move, and the stretching amount of the spring is accurately controlled, so that the accurate adjustment of the projectile launching speed is realized, and the impact at various speeds can be simulated when the impact resistance of the fabric is tested.

The invention relates to the technical field of hot stamping equipment, and discloses a digital plane and curved surface dual-purpose image-text hot stamping machine system for the surface of a cylindrical product, which comprises a modular structural design, a dual-mode positioning system and a digital control unit, the self-adaptive hot stamping head adopts a flexible stamping module driven by air pressure and hydraulic pressure, and the dual-mode positioning system comprises a plane mode and a curved surface mode. According to the hot stamping machine system, a self-adaptive hot stamping head adopts a pneumatic / hydraulic driven flexible stamping module, a pressure sensor array is arranged in the self-adaptive hot stamping head to adjust local pressure in real time, a dual-mode positioning system is adopted, a vacuum adsorption platform is adopted in a plane mode, a curved-surface mode programmable rotary clamp is adopted, 0-300 rpm stepless speed regulation is supported, a dual-mode hot stamping mechanism is initiated, and the self-adaptive hot stamping head is applied to the hot stamping machine system. The plane / curved surface mode is switched within 10 seconds through the quick-change interface, the hot stamping track is adjusted in real time based on workpiece three-dimensional scanning data, and the waste film recovery rate is increased to 95% or above through the environment-friendly hot stamping film recovery system.

The invention provides an intelligent vein closing system and a control method thereof, and belongs to the technical field of medical instruments.The intelligent vein closing system comprises a radio frequency generator host and a closing catheter, and the radio frequency generator host is used for generating and controlling output of radio frequency energy; the closed catheter comprises a handle, a catheter body and a heating working end which are connected in sequence, and the handle is detachably connected with the radio frequency generator host; wherein an infusion pump is integrated on the radio frequency generator host, and the infusion pump is used for infusing swelling liquid to a surgical site and is controlled by a control unit in the radio frequency generator host; a pressure sensor array is arranged outside the heating working end of the closed catheter and used for detecting the attaching pressure between the heating working end and the blood vessel wall in real time. The device is high in integration, and vein closing effectiveness, stability and treatment consistency are improved.

The invention provides a bending-adjustable balloon micro-catheter, and belongs to the technical field of balloon micro-catheters.The bending-adjustable balloon micro-catheter comprises a catheter body, a balloon, a bending mechanism and a feedback mechanism, the catheter body is of a slender tubular structure, and an inner cavity of the catheter body is used for conveying therapeutic drugs or embolism materials or other media; the balloon is located at the far end of the catheter body, is in an ellipsoidal shape and is used for blocking blood flow or expanding blood vessels. The multiple bending mechanisms are sequentially located at the middle section position of the catheter body and are composed of shape memory alloy wires, and the shape memory alloy wires are spirally wound around the outer wall of the catheter body, connected to the catheter body and used for adjusting the bending angle and direction of the catheter body; the feedback mechanisms are pressure sensor arrays, and the number of the feedback mechanisms is eight. The problems that an existing balloon micro-catheter is difficult to accurately reach a target position in a complex blood vessel or cavity, and the blood vessel is prone to being damaged can be solved.

The invention discloses a pressure mapping method based on a pressure sensor array, and the method comprises the steps: carrying out the gradient direction analysis of an original pressure matrix outputted by the pressure sensor array in real time, carrying out the matching with the motion direction of a material, and generating a direction sensitive pressure feature matrix; direction sensitive pressure feature matrixes generated at different collection time points are obtained in a preset time window, a track sequence is obtained, a pressure distribution kinematics feature vector sequence is generated and input into a pressure evolution state prediction model, and evolution state information is output; generating a single-point-global pressure evolution feature vector of each sensor unit, inputting the single-point-global pressure evolution feature vector into a sensing unit pressure mapping anomaly recognition and evaluation model, and outputting a local risk value of the sensor unit; and generating a risk thermodynamic diagram according to the local risk value of each sensor unit in the pressure sensor array, and identifying a pressure mapping abnormal region. Therefore, accurate monitoring, analysis and abnormal mapping of pressure distribution in the material movement process are realized.

The invention provides an intelligent detection method and system for an urban sewer pipeline, and the method comprises the steps: synchronously collecting pipeline data through laser, vision, ultrasound and a pressure sensing array, and generating aligned multi-source data through space-time registration; edge end defect preliminary screening is realized by using a lightweight AI model, and high-risk data is screened and uploaded to a cloud end; a pipeline digital twin model is constructed based on point cloud splicing and feature recognition, a multi-modal fusion neural network is adopted to realize accurate defect diagnosis, and a detection path is dynamically optimized in combination with an ant colony algorithm. According to the method, the technical problems that the adaptability is poor and the omission ratio is high in a complex sewer pipeline environment and multi-source data fusion analysis and active early warning cannot be realized by a traditional method can be solved.

The invention discloses a river water level detection method, and relates to the technical field of computer processing, and the method comprises the following steps: S01, presetting a distributed pressure sensor array in each target collection region to obtain underwater pressure data k and real-time water flow data v of a plurality of target collection regions of a river to be detected; s02, establishing a dynamic pressure water level model based on the water flow direction pressure conduction quantity estimation of the plurality of target acquisition areas in combination with real-time water flow velocity and wave period parameters; s03, performing signal attenuation compensation on the underwater pressure data according to the dynamic pressure water level model to obtain initial water level data; s04, multi-source data fusion calibration is carried out on the preliminary water level data, a river water level detection result is generated, and the result comprises a wave height frequency spectrum and a water level change curve after peak elimination correction; and S05, generating a wave energy spectral density map according to the calibrated water level data, performing real-time comparison according to the wave energy spectral density map and a preset threshold value, and performing result return according to a comparison structure. The small-wave-height short-period wave measurement precision and the water level detection reliability are remarkably improved, the intelligent flood prevention early warning and dynamic adjusting capacity is achieved, and it is guaranteed that data collection is accurate and consistent.

The invention discloses a wide-temperature-range three-dimensional pressure field measurement method in an extreme wind tunnel environment, and the method achieves the high-precision reconstruction of a three-dimensional pressure field in a whole temperature range from low temperature to high temperature through the fusion of a digital image correlation (DIC) technology and a multi-mode sensing technology, specifically, in a low-temperature environment, pressure-sensitive paint and temperature-sensitive paint are used for joint calibration, and the measurement precision of a wide-temperature-range three-dimensional pressure field is improved. A laser light source and double cameras are synchronously triggered through a binocular vision system, fluorescence lifetime signals are captured, temperature interference is eliminated through a double-gating gain function ratio, a three-dimensional shape is reconstructed in combination with a DIC technology, and non-contact pixel-level pressure field mapping is achieved. In a high-temperature environment, pressure measuring point layout is optimized through CFD simulation, discrete pressure data are acquired by adopting a high-temperature-resistant pressure sensor array, sensor space coordinates are acquired in combination with a binocular DIC system, a two-dimensional pressure field is reconstructed by utilizing a Kriging interpolation algorithm, and a three-dimensional pressure field is obtained through pixel-level mapping and three-dimensional point cloud fusion. And a high-resolution three-dimensional pressure field in a high-temperature environment is generated.

The embodiment of the invention provides an AI intelligent monitoring scoliosis pressure adjusting brace. The AI intelligent monitoring scoliosis pressure adjusting brace comprises a bandage system, an air bag pressure inner pad and an artificial intelligence AI background management system. A pressure sensor array is integrated on the surface of the air bag pressure inner pad; the pressure sensor array is in communication connection with the AI background management system; the AI background management system is used for acquiring pressure distribution information detected by the pressure sensor array after detecting that the user wears the brace; according to the pressure distribution information, whether the wearing position of the user has deviation or not is judged through a preset posture analysis algorithm; and if the deviation exists, sending first reminding information. According to the technical scheme, the pressure distribution information detected by the pressure sensor array can be obtained, so that whether deviation exists in the wearing position of the user or not is judged through the preset posture analysis algorithm, and if deviation exists, the first reminding information is sent so that the user can adjust the position of the brace through the bandage system when receiving the reminding information.

The invention relates to the technical field of dredging of coal discharging pipes of coal conveying systems, in particular to a coal discharging pipe dredging device and system, solves the difficult problems of dynamic detection and real-time elimination of caking blockage caused by sudden change of physical properties during conveying of high-humidity or viscous pulverized coal, and improves the self-adaptive capacity of the system to coal quality fluctuation. The device comprises a blockage detection module, an execution module and a control module, wherein the blockage detection module collects gas-solid two-phase flow pressure data through a pressure sensor array, and analyzes and identifies flow state abnormity in combination with a flow state model; the execution module comprises an insertion rod driving device, an air cannon device and a flow guide plate adjusting unit, and cooperatively destroys a blocking structure and removes residual pulverized coal; and the control module dynamically optimizes execution parameters based on a historical working condition database to form detection, dredging and flow field correction closed-loop control. According to the system, through multi-module cooperation, the risk of coal conveying interruption caused by caking blockage is effectively reduced, and gas-solid two-phase flow dynamic balance is maintained.