255 results about "Pressure sensor array" patented technology

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 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 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 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 relates to the technical field of ice engineering measurement, and discloses an underwater special-shaped structure surface floating icebreaking load spatial and temporal distribution test system, which comprises a flexible high-density distributed pressure sensor array, a high-speed synchronous data acquisition module, an underwater data transmission system and a shore data processing platform, the flexible high-density distributed pressure sensor array is attached to the surface of an underwater target special-shaped structure; the high-speed synchronous data acquisition module is mounted in a sealed cabin in the special-shaped structure of the underwater target, is close to the flexible high-density distributed pressure sensor array and is used for digitalization; the underwater data transmission system is used for communication between the high-speed synchronous data acquisition module and the ashore data processing platform; and the ashore data processing platform is used for reconstructing and visually displaying the pressure field of the special-shaped structure of the underwater target. According to the method, more comprehensive and accurate ice-structure interaction load information can be obtained, and fine structure design is served.

The invention relates to the technical field of ice engineering measurement, and discloses an ice pool underwater special-shaped structure icebreaking load simulation test method comprising the following steps: test preparation: carrying out test preparation, and attaching a flexible pressure sensor array to the surface of an underwater test piece; data acquisition: synchronously acquiring data acquired by the flexible pressure sensor array in the icebreaking process; and data processing: reconstructing the data acquired by the flexible pressure sensor array by adopting a hybrid interpolation algorithm based on physical constraint and adaptive weight to obtain a simulated icebreaking evolution track. According to the method, the precision and reliability of ice load reconstruction are remarkably improved, and the method is particularly suitable for identification and analysis of local peak load on the surface of a special-shaped structure.

The invention relates to the technical field of disease monitoring, in particular to a multi-device collaborative disease risk prediction system. The system comprises a non-contact type signal receiving and transmitting device, a gait collecting device, an intelligent bracelet and a central processing unit, the non-contact type signal receiving and transmitting device captures macroscopic movement data of a user through a millimeter wave signal transmitting and receiving module, and the macroscopic movement data comprises periodic characteristics of gaits, movement tracks of four limbs and posture changes; the gait acquisition device acquires plantar pressure distribution data of a user through a pressure sensor array; the smart bracelet collects motion data of a user through an accelerometer and a gyroscope; and the central processing unit carries out space-time alignment on data of the non-contact signal transceiving device, the gait acquisition device and the intelligent bracelet through a timestamp synchronization algorithm, so that the disease risk is predicted according to the analysis data. The system supports all-weather and multi-scene monitoring, is suitable for disease risk assessment, and can early warn cardiovascular events and other health problems.

The invention discloses an intelligent exoskeleton bone auxiliary conduction hearing aid system capable of being remotely controlled and having an electroencephalogram control function, and relates to the technical field of intelligent rehabilitation robots and hearing aid devices. The wearable mechanical part comprises a flexible actuator, an elastic fabric base material, an inertial measurement unit IMU, a plantar pressure sensor array, a surface myoelectricity EMG sensor and an electroencephalogram EEG sensor. And the information processing communication part comprises a central controller, a bone conduction hearing aid module, a multi-mode sensor, an embedded SoC, a DSP / AI accelerator, a 4G / 5G / Wi-Fi module and a power management unit. The flexible exoskeleton walking aid system and the bone conduction hearing aid module are integrated, the electroencephalogram EEG sensor is additionally arranged to achieve the electroencephalogram control function, and cooperation of the three functions of movement assistance, auditory perception and neural intention recognition is achieved. A user can directly control the exoskeleton action mode through electroencephalogram signals, meanwhile, intelligent assistance of lower limb joints is obtained in the walking process, and environment sounds and voice prompts are clearly received in a bone conduction mode. According to the system, the perception ability, the control flexibility and the social participation degree of old people or rehabilitation patients who are inconvenient to move and accompanied with hearing impairment in a complex environment are remarkably improved, and more natural and convenient man-machine interaction experience is provided for users.

The invention relates to a sleeping posture recognition and self-adaptive pillow height adjustment system and method and a storage medium, and the sleeping posture recognition and self-adaptive pillow height adjustment system comprises a data collection module, a sleeping posture recognition module, a pillow height adjustment module and a user interaction module; the user interaction module is used for acquiring personalized prior data and historical sleep comfort score of a user; the data acquisition module is used for acquiring a pressure data set of the pressure sensor array in real time; the sleeping posture recognition module is used for constructing a plurality of groups of time domain data slices for the pressure data set according to a preset time window, inputting the time domain data slices into a time domain feature model to obtain a plurality of groups of low-dimensional pressure data feature parameters, and further recognizing an effective sleeping posture state; and the pillow height adjusting module is used for calculating and calibrating the pillow height based on the personalized prior data of the user, the effective sleeping posture state and the historical sleeping comfort score, and adjusting the pillow surface. According to the method and the device, the problems of high computing power consumption and difficulty in meeting precise and personalized sleep requirements of the user in related technologies are solved.

The invention discloses an autoclave forming method which comprises the following steps: dividing a component into a stress sensitive area and a conventional area through finite element simulation analysis on the basis of geometrical characteristics of a three-dimensional model of the component to be formed, establishing a thermal-mechanical coupling finite element analysis model of each area, and presetting a differential temperature-pressure-time process curve; secondly, a distributed optical fiber sensor is arranged in the composite material prefabricated body, a micro pressure sensor array is arranged at the key position of the surface of the mold, and the distributed optical fiber sensor and the micro pressure sensor are both connected with a central control system; then, performing differential pressure and temperature control on each area by adopting closed-loop control in sequence; and finally, the central control system collects sensor data in real time, judges whether the forming process is abnormal or not through a defect recognition algorithm, automatically starts a grading early warning mechanism when detecting that the forming process is abnormal, and executes a self-adaptive adjustment strategy, including inter-region cooperative pressure compensation, so as to eliminate forming defects.

The invention discloses a bedridden patient sign measurement and medication assisting system based on multi-sensor fusion, which belongs to the technical field of medical instruments and comprises a multi-sensor fusion measurement module, a self-adaptive calibration compensation module, an intelligent evaluation decision module, a medication assisting calculation module and a closed-loop feedback optimization module. A pressure sensor array, an ultrasonic sensor and an acceleration sensor are used for cooperatively measuring the height and weight of a patient, a deformation compensation model and a body position correction model are adopted for accurate calibration, a BMI index is automatically calculated, a VTE risk score, a falling risk score and a self-care ability score are generated, and the medication dosage is intelligently recommended according to medicine characteristics and patient physique. And continuously optimizing system parameters through an incremental learning algorithm to form a measurement-evaluation-medication-optimization deep coupling closed-loop system, so that the physical sign measurement precision, clinical evaluation efficiency and medication safety of the bedridden patient are remarkably improved, and the nursing labor intensity and the medical error risk are reduced.

The invention discloses an intelligent mattress control method based on height, an intelligent mattress and related products. The method comprises the steps of obtaining height parameters of a human body; according to the height parameters, through a preset micro-partition mapping algorithm, to-be-activated micro-partitions, corresponding to all the body parts of the human body, on the mattress are determined, a preset number of micro-partitions are pre-divided in the length direction of the mattress, and a plurality of air bags are distributed in each micro-partition; activating the air bag of the micro-partition to be activated to obtain a current activated micro-partition, and collecting a plurality of pressure values of the micro-partition through a pressure sensor array of the mattress; according to a preset air pressure adjusting strategy, the air pressure of the air bag in the current activation differential area is adjusted according to the pressure value. According to the method, the air bag supporting subareas can be dynamically adjusted according to the heights of the users, the problem that traditional mattress subareas are fixed and are difficult to adapt to the users with different heights and weights is solved, accurate supporting and personalized adjustment are achieved, and the supporting effect and sleep comfort are improved.

This invention relates to the field of intelligent molding technology, specifically to an intelligent adjustable medical cotton ball molding method and system, comprising the following steps: collecting pressure data through a distributed pressure sensor array and generating a pressure feature vector through Gaussian filtering for noise reduction; analyzing the pressure change trend based on the feature vector and outputting a gradient adjustment command; controlling a valve to adjust the air pressure to obtain compensation parameters; driving a servo motor to adjust the mold gap and collecting offset data to generate a feedback signal; and combining the feedback and adjustment command inputs to a neural network to evaluate the molding result. In this invention, data is collected through a distributed sensor array, multi-dimensional noise reduction enhances feature extraction, dynamic functions analyze pressure trends, offset adjustment parameters are identified, collaborative control achieves closed-loop compensation, displacement sensors provide feedback on gap changes, parameter modeling optimizes accuracy and consistency, convolutional networks extract temporal features, and fusion analysis constructs an adaptive system to achieve intelligent prediction and optimization of molding quality.

The application discloses a compressor internal flow field synchronous measurement system based on PIV and pressure sensing, relates to the technical field of compressor experimental aerodynamics measurement, and is suitable for accurate measurement of flow field parameters in a diffuser modeling test of a compressor. The system comprises a dynamic pressure sensor array, a signal conditioning module, a multichannel dynamic pressure acquisition card, a double-pulse laser, a high-speed CMOS camera, an FPGA synchronous controller, a PIV post-processing server and a multi-source data fusion workstation. The FPGA synchronous controller is used as the only time sequence reference of the double-pulse laser, the high-speed CMOS camera and the multichannel dynamic pressure acquisition card, the traditional software trigger is replaced by a hardware trigger, and system delay jitter is eliminated. The timestamp marking pulse and the first pulse trigger signal are output simultaneously, the pressure data stream obtains a sampling point index corresponding to the laser emission moment directly, and the time synchronization accuracy of the velocity field and the pressure field reaches the nanosecond level.

The application discloses a circulating water pump drag-reducing and pressure-increasing device and a motor regulating system thereof, relates to the technical field of fluid machinery and automatic control, and constructs a flow field active control system of sensing, decision-making and execution. A high-frequency pressure sensor array continuously captures pressure pulsation frequency spectrums before and after an inlet flow guide unit. The frequency spectrums are directly mapped with the vortex intensity and flow state instability degree of the impeller inlet. An intelligent decision-making module performs real-time decoupling and analysis on the frequency spectrums, identifies the characteristic frequency and energy intensity of harmful vortexes, synchronously calculates the optimal deflection angle instruction of the flow guide vane, and drives the adjustable flow guide vane to move according to the instruction. An accurate pre-whirl flow with controllable intensity is actively generated in the inlet flow field in the opposite direction of the rotation direction of the impeller, so that the flow lines are greatly smoothed before the fluid enters the impeller, and the fluid can smoothly enter the working area of the impeller at the best attack angle.

This invention provides a belt conveyor turning device and control method, belonging to the field of mine conveying technology. It includes a steering frame and a redirecting frame. The redirecting frame is equipped with a redirecting roller, and the steering frame is equipped with a steering roller. An angle adjustment component includes an angle sensor, and a diameter adjustment component is installed on the steering roller. Tension data streams from the steering roller are acquired via a tension sensor, and an axial pressure distribution time-series matrix is ​​acquired via a pressure sensor array. Two sets of baffles are slidably mounted on the steering frame. A control module is installed on one side of the steering frame. It acquires the axial pressure distribution time-series matrix via the pressure sensor array and adjusts the roller angle based on the angle sensor data. The roller diameter is adjusted based on the tension sensor data. The material release point is determined according to the pressure field characteristics and the correction angle, and the baffle position is controlled. This solves the problems of belt misalignment and material ejection deviation caused by manual adjustment in traditional turning devices, ensuring stable belt operation.

This invention relates to the field of electric passenger vehicle ride comfort testing technology, specifically to a device and method for synchronously acquiring and eliminating motion sickness parameters in electric passenger vehicles. It includes: a full-area flexible pressure sensor array to acquire human contact pressure signals; a multi-modal motion vibration monitoring module to simultaneously acquire vehicle body and human motion and vibration signals; a data acquisition unit to receive and process raw sensor data; an intelligent calculation unit to calculate mechanical, kinematic, and vibration parameters; an adaptive calibration unit to calibrate sensor baselines and dynamically adjust sensitivity and calculation coefficients; a dual-linkage verification unit to verify data validity; an autonomous motion interference elimination unit to separate the vehicle-related motion and human autonomous motion components, eliminating interference data; and a data output unit to output valid raw data and calculated parameters to an external system. This technical solution can achieve accurate acquisition of multi-dimensional motion sickness parameters in electric passenger vehicles and intelligent elimination of interference data.

The present application relates to the technical field of medical devices, and discloses a multifunctional finger rehabilitation training device, which comprises a frame formed by an anti-skid base and a stand column, a hole plate training module installed on the frame, a surface of the hole plate training module being provided with through holes and being internally provided with a pressure sensor array, a grip strength training module, a rotating training module, an electric control module, and a micro-control unit, an analog-digital conversion interface, a storage unit and a communication interface of the electric control module being electrically connected with the pressure sensor array, the displacement sensor and the photoelectric encoder, and the electric control module being used for collecting, calibrating and analyzing training data and storing or transmitting the training data.

An imaging system for imaging a tissue of a subject. The system comprises a first substrate, a second substrate, and X-ray imaging system, and a two-dimensional pressure sensory array. The second substrate is spaced a first distance from the first substrate. The first substrate and the second substrate are positioned in an imaging field. The first substrate and the second substrate are capable to move relative to one another to during a compression cycle. The X-ray imaging system capable to image the specimen in the imaging field. The two-dimensional pressure sensor array positioned on the first substrate, the second substrate, or both the first substrate and the second substrate, wherein the two-dimensional pressure sensor array is capable to measure a pressure distribution of the specimen during the compression cycle.

This application relates to pressure detection technology and discloses a flexible pressure acquisition system, device, and method based on a parallel architecture. It includes a signal acquisition and control module, a pressure sensor array, and an environmental monitoring module. The signal acquisition and control module includes an MCU and analog front-end circuitry. The analog front-end circuitry includes K parallel analog multiplexers. The MCU internally has K corresponding ADC channels. The pressure sensor array is electrically connected to the signal acquisition and control module, and its M×N pressure sensing units are divided into K parallel acquisition sub-regions. Each sub-region's column electrodes are connected to an analog multiplexer input channel. The environmental monitoring module acquires real-time environmental parameters. The MCU synchronously triggers all ADC channels to synchronously convert the pressure signals of the K sub-regions, and combines the environmental parameters with an adaptive filtering algorithm for compensation and correction, outputting pressure distribution data. This application can improve the sampling rate and measurement accuracy of the pressure acquisition system.

The invention relates to the technical field of medical instruments and clinical nursing, in particular to a radial artery puncture navigation system based on multi-modal sensing and digital projection, which comprises the following steps: a multi-modal blood vessel signal acquisition module, which is used for acquiring a blood vessel pulsation signal on the wrist of a patient through a photoplethysmography sensor array, the strongest pulsation line is positioned through the pressure sensor array, and the blood vessel depth and artery and vein distinguishing information are obtained through the bioelectrical impedance sensor array. According to the invention, through multi-modal blood vessel signal acquisition, blood vessel dynamic deformation modeling, personalized digital twinning construction and dynamic updating, projection path generation and control, and projection output and real-time error compensation, real-time visual projection of a blood vessel center line and local deformation is realized; therefore, the problem that puncture positioning is not accurate due to the fact that dynamic changes of blood vessels cannot be accurately reflected due to the fact that most traditional radial artery puncture adopts a hand feeling positioning method is solved.

The invention discloses a multi-modal environment dynamic adaptation method based on balance dysfunction of Alzheimer's disease, which comprises the following steps: acquiring three-dimensional attitude image data of a patient through an RGB-D camera, synchronously acquiring plantar pressure distribution of a pressure sensor array, and forming a composite original data set; processing data in real time by adopting an edge computing node, extracting gait key point coordinates and computing a gait stability index; performing multi-modal fusion on the indexes and the environmental parameters to construct a digital twinborn model, dynamically adjusting modal weights through federated learning, and outputting obstacle early warning; and the tactile feedback waistband activates the motor according to early warning grading and triggers an environment parameter adjustment strategy. According to the method, full-link dynamic adaptation from data collection to environment feedback is achieved, the patient balance ability is effectively improved, privacy data are protected, and the method has remarkable technical innovation and clinical application prospects.

This invention relates to the field of underwater robot technology, specifically to an autonomous recovery method and system for underwater robots based on binocular vision and multi-source fusion. The system includes an AUV and a recovery platform. The AUV is equipped with a binocular camera, IMU, DVL, and USBL. The recovery platform is equipped with a guide light array, an auxiliary light source, a pressure sensor array, and a recovery cage. The method includes four stages: long-distance repositioning, high-precision visual guidance, multi-source fusion control in the visual failure zone, docking determination, and fixation. In the visual failure zone, the system activates the bottom auxiliary light source and constructs a multi-source fusion framework. It deeply fuses the two-dimensional deflection angle of the auxiliary vision, the high-frequency attitude of the IMU, the three-dimensional velocity of the DVL, and the absolute position of the USBL, and outputs the six-degree-of-freedom pose of the AUV in real time. This ensures end-effector attitude stability, improves system robustness and environmental adaptability, and solves the problems of not being able to provide complete attitude information and poor anti-disturbance capability in the near-range visual failure zone.

The present application relates to a TAVR teaching model based on blood flow simulation and multi-modal image fusion and use method. The model comprises a simulated thoracic and abdominal cavity with a built-in heart wave beat simulation part that drives fluid to generate pulsatile blood flow, a simulated thoracic and abdominal body with pre-set vascular access, a bionic heart assembly with structures such as a ventricular cavity, a pathological valve module that can be detachably fitted to the aortic valve ring and contains a pressure sensor array and simulated calcification, a coronary circulation monitoring module that monitors the perfusion state of the coronary artery opening, a virtual fluoroscopy positioning module that generates real-time fluoroscopy images, and a central control console that electrically cooperates with each module. The scheme simulates the tactile sensation of calcification through the pathological valve module, the heart wave beat simulation part reproduces the physiological pressure difference with a closed loop blood flow, realizes image navigation training with non-radiation virtual fluoroscopy, integrates real-time simulation of complications with coronary monitoring and annulus pressure sensing, and solves the problems of existing models such as distorted hand feeling, inaccurate dynamics, dependence on radiation, and lack of complication training.

This invention provides a method and system for autonomous plunger hovering control based on an expansion mechanism in a natural gas well. The invention utilizes a multi-point pressure sensor array mounted on the plunger to monitor real-time pressure distribution changes on the wellbore. Noise is removed and the optimal expansion degree is predicted using an adaptive filtering algorithm and machine learning model in an edge computing node, generating an expansion diameter adjustment scheme. The plunger's expansion mechanism is adjusted according to this scheme, and a three-dimensional flow field simulation environment is constructed by combining fluid dynamics parameters and high-resolution environmental information. Particle swarm optimization and Kalman filters are used for modeling and prediction to determine the plunger's position and resistance, improving the plunger's operational accuracy and response speed in complex downhole environments, enhancing the system's flexibility and adaptability, and thus improving the safety and efficiency of natural gas extraction.

According to the intelligent clamping jaw dynamic control system based on multi-sensing feedback, through the technical scheme that the driving module, the detection module and the control module work cooperatively, on the basis that the driving module provides opening or tightening power for the intelligent clamping jaw, the intelligent clamping jaw is controlled to be opened or closed; a weight sensor, a temperature sensor, a torque sensor and a micro pressure sensor array in the detection module collect key data of the intelligent clamping jaw in real time from different aspects respectively, the control module analyzes the data, and the voltage and / or current of the intelligent clamping jaw is accurately adjusted according to the analysis result. According to the intelligent clamping jaw, the stability and accuracy of object grabbing of the intelligent clamping jaw can be effectively improved, the problem that grabbing fails due to the fact that a traditional clamping jaw cannot sense and adapt to working state changes in real time in the grabbing process is solved, the adaptability of the clamping jaw to different working scenes is enhanced, and the working efficiency and reliability of the whole system are improved.

A wearable device for measuring blood glucose and blood pressure for a user includes a main body including a first side and a second side formed on the opposite side of the first side; a first supporting frame protruding from the first side and a second supporting frame protruding from the second side; a belt portion having a first belt end detachably coupled to the first supporting frame, a second belt end detachably coupled to the second supporting frame, and at least one aligning mark, wherein the belt portion is positioned around a wrist of the user; wherein the main body includes at least one pressure sensor array assembly overlaid on a radial artery of the user; wherein the pressure sensor array assembly includes a plurality of apertures arranged one after another to form a cross-shaped pattern and at least four sensor elements arranged in a symmetrical configuration.

The application discloses an unmanned aerial vehicle intelligent adaptive load distribution and dynamic balance control system, and specifically comprises the following steps: A1, a 3D physical model of the load is constructed through laser radar scanning and visual identification, and the load mass distribution and the gravity center offset are calculated through a pressure sensor array; A2, based on a digital twin platform, real-time meteorological data and flight attitude are coupled to simulate the aerodynamic performance of the load distribution strategy; A3, a DRL model is locally trained through an edge computing node, and a global optimal distribution strategy is generated by a federal aggregation server, and the application relates to the technical field of unmanned aerial vehicles. The unmanned aerial vehicle intelligent adaptive load distribution and dynamic balance control system couples fluid dynamics simulation and real-time meteorological data through a digital twin platform, simulates the aerodynamic performance of the load distribution strategy, dynamically generates a global optimal strategy in combination with a federal learning decision engine, and significantly improves multi-task cooperation efficiency.