4857 results about "Pressure sensing" 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 automatic welding control, and particularly discloses a multi-station automatic welding cooperative control method for electric iron accessories, which realizes full-closed-loop accurate control of a welding process through multi-sensor data fusion and an intelligent optimization algorithm. According to the method, an infrared thermal imager, an acoustic emission sensor and an ultrasonic thickness measuring device are adopted to collect molten pool temperature field, sound wave frequency spectrum and fusion depth data in real time, after feature extraction, the data are input into a multi-target optimization model, and a Pareto optimal solution set is generated with the fusion depth, the width of a heat affected zone and phase change latent heat as optimization targets; dynamically adjusting a segmented welding-back path and process parameters on the basis of an optimization result, and triggering model iterative correction through ultrasonic online monitoring; the central control unit adopts space voxelization monitoring and a three-level collision avoidance strategy to coordinate operation of the multiple mechanical arms, and collision emergency protection is achieved in combination with flexible pressure sensing.

The invention discloses a touch control method based on a pressure sensor, which relates to the technical field of sensor equipment, and comprises the following steps: designing a touch control panel; distributing and calibrating a sensitivity area; designing a multi-layer touch pressure sensing fusion algorithm; designing a dynamic pressure feedback mechanism; designing a nonlinear pressure interval classification mechanism; and performing pressure sensing and dynamic gesture recognition. According to the touch control method based on the pressure sensor, through multi-level design and innovative model optimization, innovative technologies such as differential sensitivity design, a dynamic sensitivity adjusting mechanism, pressure sensing and gesture recognition are introduced into the touch control technology of the pressure sensor, so that the precision and efficiency of complex gesture analysis can be remarkably improved; and the false touch rate is effectively reduced. The design can adapt to various environment changes, the service life of equipment is prolonged, the user interaction experience is improved, and the defects in the prior art are overcome.

The invention provides a seat comfort optimization calculation method based on a sensor and AI modeling, and the method comprises the steps: collecting the pressure distribution data of the sitting posture of a passenger and a spine contact area in real time through an attitude sensor and a pressure sensor which are disposed on a seat; a seat supporting area is divided into a cervical vertebra area, a thoracic vertebra area, a lumbar vertebra area and a sacrococcygeal area, and a pressure distribution prediction model of each area is established; constructing an input vector based on the average pressure, the maximum pressure, the pressure gravity center, the body type parameter and the pathological weight factor, and outputting a target support pressure value, a pressure avoiding curve and a neighbor cell migration proportion of each partition by using an artificial intelligence model; dynamic adjustment is achieved through the partitioned air bag and the driving unit, and secondary fine adjustment and protection are achieved in combination with feedback monitoring. The system comprises a posture sensing module, a pressure sensing module, a data processing module, a model building module, a regulation and control execution module and a feedback monitoring module, and self-adaptive regulation and control of different areas of the spine of a passenger can be achieved.

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

The invention relates to the technical field of air pressure intensity adjustment, and discloses a pressure control method and device for accurately adjusting air pressure intensity, and the method comprises the steps: carrying out the digital conversion and temperature and humidity compensation of an original pressure signal collected by a pressure sensing array, and obtaining a pressure data matrix and a pressure gradient matrix; calculating a pressure distribution mass center and a pressure fluctuation frequency spectrum to obtain a pressure space distribution characteristic matrix and a pressure time domain characteristic matrix; inputting a three-state Markov model for dynamic state identification to obtain a pressure state transition probability matrix and a pressure response prediction matrix; constructing an objective function containing a pressure tracking error term and an organization safety constraint term, and solving to obtain a PID control parameter matrix and a pressure safety limit matrix; and constructing a three-stage control system comprising a basic controller, an interference compensator and a safety protector, and outputting an air pressure regulation driving signal. According to the method, high-precision pressure sensing control is realized.

The invention provides a dynamic monitoring method for a soil mass seepage field of a power transmission tower slope. According to the method, related data of the slope are acquired through multi-source data acquisition and technologies of pressure sensing and static pressure measurement, displacement monitoring, multi-sensor fusion, Beidou / GPS positioning, resistivity method exploration, soil moisture content monitoring and the like; fusing the collected multi-source data, analyzing the dynamic change of the seepage field by using a risk assessment model and a machine learning algorithm, and predicting the evolution trend of the seepage field; a lightweight model is deployed at a monitoring terminal to realize local rapid processing of data, alarm information is immediately sent out once an abnormal state is monitored, and scientific and reasonable decision support is provided for protection and treatment of a transmission tower slope according to early warning information in combination with a pre-made decision scheme; according to the invention, the accuracy and timeliness of transmission tower slope soil seepage field monitoring can be effectively improved, and the threat of landslide and other disasters to a transmission line is reduced.

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 sickbed control, in particular to a control system of an intelligent bed and a control method thereof. The method comprises the following steps: acquiring structural data of the intelligent bed; carrying out human body fitting area gravity sensor deployment on the intelligent bed structure data to obtain sickbed sensor deployment data; performing gravity sensor data acquisition on the sickbed sensor deployment data to obtain an initial gravity sensor data set; carrying out data matrix processing on the gravity sensor data set to generate a multi-dimensional pressure sensing matrix; acquiring user pain part data and bed board motor initial position data; and performing pressure distribution mode recognition on the multi-dimensional pressure sensing matrix to obtain a uniform distribution mode and a concentrated distribution mode. According to the invention, through the personalized support regulation, global attitude optimization and real-time feedback mechanism of the intelligent bed, the control accuracy and intelligence of the intelligent bed are improved.

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 relates to the technical field of signal analysis and processing, in particular to an underground flow switch control method based on vibration signal analysis. The method comprises the steps that 1, vibration signals of a pump are collected through a three-axis vibration sensor, and acceleration time domain signals in the three-axis direction are obtained; performing multi-dimensional vibration spectrum component decoupling on the acceleration time-domain signal to obtain a time-frequency characteristic matrix of three-axis vibration; 2, calculating a Reynolds stress tensor based on the turbulence intensity; calculating a flow state transition criterion value according to the turbulence intensity and the Reynolds stress tensor, and establishing a flow estimation model; 3, according to the flow estimation model, dynamic response of underground flow switch control is generated; and according to the dynamic response, a self-adaptive control law for controlling the underground flow switch is generated by using a self-adaptive control method. According to the invention, the limitation of a traditional pressure sensing and flow sensing technology in a complex underground flow state is effectively overcome, and the real-time performance, the accuracy and the environmental adaptability of flow control are remarkably improved.

The invention discloses an energy-saving control method based on a building group spatial form, which relates to the technical field of energy-saving control, and comprises the following steps: constructing an airflow track analysis region based on a region with hot pressure difference direction change in a spatial pressure covering sensing matrix, and collecting continuous wind direction and wind speed data; judging whether the airflow direction is abnormal or not according to the change of the flow direction consistency entropy; performing spatial coincidence processing on the spatial pressure shielding sensing matrix and the airflow direction abnormal region, and generating an air outlet ventilation and heat extraction efficiency evaluation index based on the heat conduction rate in the coincidence region and the stability of an airflow output path; and on the basis of the ventilation and heat removal efficiency evaluation index of the exhaust outlet, an exhaust response condition matrix containing a space pressure shielding parameter, an airflow disturbance level and a heat retention level is constructed, and a ventilation control judgment sequence is generated. According to the method, the problem of air exhaust failure under pressure shielding interference is solved, ventilation efficiency accurate judgment and energy-saving regulation and control optimization are achieved, and the ventilation stability and the energy utilization efficiency of the building group are guaranteed.

The invention discloses a dynamic geological survey system and a construction simulation method. The dynamic geological survey system comprises an intelligent sensing and data acquisition module and a multi-source data fusion processing module, the intelligent sensing and data acquisition module comprises a Raman scattering optical fiber strain sensor array, a three-component seismometer monitoring network and a distributed optical fiber pressure sensing subsystem; the Raman scattering optical fiber strain sensor array, the three-component seismometer monitoring network and the distributed optical fiber pressure sensing subsystem form a multi-dimensional sensing network for shield construction geological monitoring. By means of the integrated intelligent sensing and data acquisition module, geological changes in the shield construction process can be monitored. The Raman scattering optical fiber strain sensor array, the three-component seismometer monitoring network and the distributed optical fiber pressure sensing subsystem jointly form a multi-dimensional sensing network, geological strain, microseismic events, pore water pressure and other key information can be captured, and comprehensive geological data support is provided for construction.

The invention relates to the technical field of gas cylinder detection, in particular to a gas cylinder airtightness detection device which comprises a base, a clamping rotating structure is arranged at the upper end of the base, a gas cylinder is clamped on the clamping rotating structure, a lifting structure is arranged at the upper end of the base, and a sealing shell arranged on the outer side wall of the gas cylinder in a sleeving mode is installed on the lifting structure. An air pressure sensing structure is installed at the upper end of the sealing shell, four air bag shells are arranged on the bottom of an inner cavity of the sealing shell in a circumferential array mode, the outer wall of a gas cylinder is clamped through the four sealing gaskets and the air bags, effective sealing can be conducted when the outer wall of the gas cylinder is uneven, and the detection accuracy is improved; and meanwhile, the outer surface of the gas cylinder is cleaned by the cylindrical gas bag through expansion rotation of the cylindrical gas bag, when the gas bag is wizened, self-cleaning can be achieved when the gas bag rotates through sagging of the gas bag, gaps between the sealing gaskets can be filled when the gas bag is subjected to secondary expansion, and the result stability is improved.

The invention provides a multi-signal fusion massage glove teaching system and a control method, and the system comprises a glove body, and a pressure sensing module, a motion sensing module and a myoelectricity sensing module which are disposed on the glove body, and is in electric signal connection with the pressure sensing module, the motion sensing module and the myoelectricity sensing module through a control unit. The control unit is used for analyzing the collected massage pressure, motion trail and electromyographic signals, and synchronous and in-situ collection of force-motion-physiology multi-dimensional information of massage manipulation in a real clinical environment is achieved. The design overcomes the limitation that in the prior art, a real operation scene is separated, and only single-aspect measurement can be carried out, and a hardware foundation is laid for comprehensive and objective quantitative evaluation of the massage manipulation. The integrated structure greatly facilitates the use of an operator, and the system can evaluate the manipulation quality online and give guidance immediately, thereby greatly improving the teaching efficiency and the training effect.

The invention discloses a high-precision pressure sensing and self-calibration system, and relates to the technical field of pressure sensing, the system comprises a pressure sensing module, an environment monitoring module, a data processing module, a digital twinning module and a self-calibration module, the pressure sensing module collects and converts pressure signals through a high-precision sensor, and the environment monitoring module obtains environment parameters in real time; the data processing module carries out amplification, filtering, analog-to-digital conversion and timely frequency domain analysis on the initial electric signal, and outputs preprocessed data in combination with environmental parameter dynamic compensation. The digital twin module constructs a sensor virtual model, and simulates and outputs an ideal pressure predicted value; and the self-calibration module compares the predicted value with the preprocessed data, generates a final pressure value through deviation calculation, iterative learning and data fusion, and can also calculate the health index of the sensor and perform early warning maintenance. The system realizes high-precision pressure induction and real-time self-calibration, improves the measurement accuracy and prolongs the service life of the sensor.

Ultrasound probes, ultrasound systems, and ultrasound methods with pressure measurement capabilities for detecting and determining if bodily tissue is over-compressed during ultrasound imaging procedure. An ultrasound probe can include a probe body, an articulating probe head attached to the probe body, and a pressure-sensing device housed in an articulating area between the articulating probe head and the probe body. A method can include placing the articulating probe head of the ultrasound probe on a skin surface of a patient and moving the articulating probe head of the ultrasound probe over the patient while ultrasound signals are emitted into the patient from the articulating probe head. The method can also include monitoring for measured pressure values induced on the patient by the articulating probe head to determine whether a threshold pressure value has been exceeded.

According to the reconfigurable flexible pressure sensor based on the magnetic ionic liquid drops and the preparation method of the reconfigurable flexible pressure sensor, the superparamagnetic nanoparticles and the ionic liquid drops are combined to prepare the magnetic ionic liquid drops which are high in fluidity and can be magnetically controlled, and the magnetic ionic liquid drops serve as a pressure sensitive layer of a pressure sensing device; and the flexible stretchable pressure sensor based on the magnetic ionic liquid drop array is constructed. The invention also provides a distributed / combined non-contact multi-element in-situ reversible reconstruction method of the flexible pressure sensor, and an external magnetic field is utilized to control the magnetic ion liquid drops in the sensor to carry out programmable low-resistance rapid movement and deformation between the super-hydrophobic interconnected microfluid channel and the chamber array. The spatial distribution, component / volume and geometrical shape changes of the magnetic ionic liquid drops in the array are regulated and controlled, and distributed / combined non-contact multi-element in-situ reversible reconstruction of the flexible stretchable pressure sensor in the performances of spatial resolution, sensitivity, detection limit, pressure response mode and the like is realized through one or more change combinations.

The invention discloses a surgical operation system with a training or auxiliary function, particularly relates to the field of intelligent surgical operation systems, and cooperatively works through five modules including multi-modal sensing, layered AI decision making, dynamic feedback, closed-loop learning and an expansion interface. MEMS pressure sensing and biological signal fusion sensing are adopted, strategic layer three-dimensional navigation and execution layer magneto-rheological damping control are combined, and an operation whole-process optimization system is constructed; a multi-source data persistent evolution model is integrated through federal learning, and precise man-machine interaction is realized by matching eye movement tracking AR and a variable stiffness touch glove. According to the system, the intraoperative risk identification accuracy is improved, the operation efficiency is improved, third-party equipment extension and doctor skill quantitative evaluation are supported, and the operation safety and the training standardization level are remarkably improved.

The invention belongs to the technical field of shock insulation supports, and particularly relates to a composite thick laminated rubber shock insulation support with self-adaptive damping, a shock insulation method of the composite thick laminated rubber shock insulation support and an intelligent fluid preparation method. According to the technical scheme, the composite thick laminated rubber shock insulation support with the self-adaptive damping function comprises an upper connecting steel plate and a lower connecting steel plate, a steel plate layer, a rubber layer, a pressure sensing layer and a sensor network layer are arranged between the upper connecting steel plate and the lower connecting steel plate, and a plurality of fluid cavities communicated through pipelines are formed in the rubber layer; the pressure sensing layer is provided with an electromagnetic coil, a piezoelectric driving unit and a valve body, the valve body is connected with the fluid cavity through a guide pipe, the electromagnetic coil is arranged on the valve body in a sleeving mode, and the electromagnetic coil and the valve body are electrically connected with the piezoelectric driving unit. The invention provides a composite thick laminated rubber shock insulation support with self-adaptive damping, a shock insulation method of the composite thick laminated rubber shock insulation support and an intelligent fluid preparation method, and the composite thick laminated rubber shock insulation support has intelligent sensing and self-adaptive adjusting functions and can keep long-term stability.

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

The invention discloses a temperature and pressure sensor for a new energy automobile, and belongs to the technical field of sensor equipment, the temperature and pressure sensor comprises a plug assembly, a shell and a protective sleeve, a support seat, a circuit board, a temperature sensing probe and a pressure sensing element are arranged in the shell, the protective sleeve is arranged at the lower waist part of the support seat, and the temperature sensing probe is located in the protective sleeve and is in electric signal connection with the circuit board; a square groove for containing the pressure sensing element and the circuit board is formed in the top of the support base, the pressure sensing element is arranged at the bottom of the circuit board and is in electric signal connection with the circuit board, and a pressure transmission channel is further arranged in the shell. The pressure transmission channel comprises a gap part defined by a protective sleeve and a shell and a special-shaped channel formed in the support base, a circular pressure groove is formed in the square groove, the circular pressure groove is matched with the pressure sensing element to form a pressure cavity which is eccentrically designed relative to the shell in the axial direction, and the special-shaped channel is formed in a medium leading-in area. Therefore, the medium entering surface area can be increased through the eccentric design, and the response speed of medium pressure measurement is ensured.

The invention discloses a multifunctional leg sleeve for auxiliary treatment of lower limb lymphedema, which comprises a leg sleeve body, a pressure sensing unit, a temperature and humidity sensing unit, an air bag pressure unit, a heating unit, an electrical stimulation unit, an impedance measuring unit and a portable force-electricity-heat cooperative intervention controller, the leg sleeve is characterized in that the pressure sensor and the temperature and humidity sensor monitor internal environment parameters of the leg sleeve body, drive the air bag pressure unit to perform self-adaptive pressurization, and drive the heating element and the electrical stimulation electrode to perform intelligent heating medicine application and muscle stimulation at the same time; the main control unit is driven to adjust the pressure, the temperature and the stimulation intensity of the air bag pressurizing unit, the heating unit and the electrical stimulation unit; in the wearing period, the device uploads data to a mobile phone and a cloud server terminal for data analysis, optimal pressure, temperature and electrical stimulation regulation prescriptions are provided for a user, and a good treatment effect is achieved.

The invention provides a warp-knitted interval sensing fabric and a preparation method and application thereof, a pressure sensor, a pressure sensing foot pad and a plantar pressure value acquisition system, and belongs to the technical field of flexible sensors. The warp-knitted interval sensing fabric comprises an electrode layer, a monofilament interval layer and a sensing layer which are sequentially laminated; the warp-knitted interval sensing fabric is of an integrally formed structure; the electrode layer is provided with a full-penetrating double-comb structure and comprises a plurality of conductive strips which are arranged in parallel, and an insulating strip is arranged between every two adjacent conductive strips; the monofilament spacing layer is formed by mutually connecting fiber coils, and the electrode layer and the sensing layer are connected through the fiber coils; the sensing layer has a full-penetration double-comb weave and is obtained by weaving sensing yarns. According to the warp-knitted spacer sensing fabric pressure sensor, the electrode layer, the monofilament spacer layer and the sensing layer are integrally formed, the process is simple, the cost is low, and large-scale production and practical application are facilitated.

The invention discloses a fluid pressure monitoring method and system, and relates to the technical field of pressure monitoring, and the method comprises the steps: determining a hydraulic circulation path, configuring a pressure sensing module, carrying out the real-time pressure monitoring of a first hydraulic oil path, a second hydraulic oil path and a third hydraulic oil path, and generating pressure distribution prediction information through the analysis of a hydraulic control module; through comparison of monitoring data and prediction information, an abnormal pressure distribution path and characteristics are accurately identified, abnormity judgment and dynamic correction are performed based on a reversible abnormity correction model, a correction hydraulic control signal is generated, and closed-loop control is implemented after the correction hydraulic control signal is input into a hydraulic control module. The method solves the technical problem that an existing hydraulic system is difficult to accurately recognize abnormal pressure distribution and carry out real-time dynamic correction under complex working conditions, and the system operation stability is affected, and achieves the purposes of accurately recognizing abnormal pressure distribution and carrying out real-time dynamic correction through multi-path pressure monitoring and a reversible abnormal correction model, and improving the system operation stability. And the operation stability of the system is improved.

The invention provides a packaging and sintering control method and device for a power semiconductor device, and the method comprises the steps: achieving the monitoring of a dynamic stress field of a chip and a substrate interface through an embedded pressure sensing array, and obtaining the real-time stress distribution data. And in combination with a material characteristic database, multivariable collaborative optimization is performed on sintering process parameters, so that dynamic adjustment of the parameters is realized. The temperature and pressure curves of all the areas of the sintering platform are dynamically adjusted according to the optimized technological parameters by means of the micro induction heating element and the piezoelectric actuator, and refined self-adaptive multi-area sintering control is achieved. The sintering interface is subjected to real-time nondestructive testing, the interface quality index is obtained and serves as a feedback parameter to be input into the optimization process, closed-loop control is formed, and the accuracy of the sintering process is improved. The problems of uneven stress distribution and inconsistent bonding strength in the prior art are solved through a comprehensive real-time monitoring and dynamic regulation and control method, and the packaging quality and reliability of the power semiconductor device are remarkably improved.

The invention belongs to the field of MEMS sensors, and particularly relates to a low-temperature-drift MEMS resonant pressure sensor sensitive chip and a preparation method thereof. Comprising a cap layer, a resonance layer, a pressure sensing layer and an isolation base which are sequentially bonded and connected from top to bottom, the cap layer is provided with an electrode through hole and a vacuum cavity groove, and a getter is sputtered in the vacuum cavity groove; two Si-SiO2 composite resonators and a plurality of lead wire discs are arranged on the resonance layer, and a metal electrode is arranged on each lead wire disc; the number of the metal electrodes is equal to that of the cap layer electrode through holes, and the metal electrodes are located under the electrode through holes; two groups of silicon islands are arranged on the front surface of the pressure sensing layer, and three rectangular sensitive films with the same size are arranged on the back surface; the isolation base is a glass table; according to the invention, the output sensitivity of the sensor is greatly improved, the chip processing complexity is reduced, and the introduction of additional stress and materials is reduced.

The invention relates to the technical field of middle and long distance running evaluation, in particular to a middle and long distance running evaluation method and system based on human face body weight recognition, and the system comprises a data acquisition module, an algorithm host, a cloud server and a terminal module. A camera group and a pressure sensing pad in the data acquisition module respectively acquire images and pressure data; the algorithm host module processes data, identifies human face body features, tracks personnel, calculates scores and analyzes violation; the cloud server stores various data; and the terminal module is used for information input and result display. The evaluation method comprises the steps of data acquisition, identity recognition and tracking, score calculation, illegal behavior analysis, data integration and storage, exception handling and correction and the like. According to the invention, many problems of an existing RFID and AI face recognition evaluation mode are solved, for example, the RFID cannot perform biological feature recognition and violation judgment, and AI face recognition is interfered by the environment. Accurate identity recognition, whole-course tracking, accurate score calculation, comprehensive violation detection and efficient data management are realized.

The invention discloses an intelligent pressure self-adaptive anti-bedsore nursing mattress system which comprises a flexible pressure sensing layer configured on the surface of a mattress and used for monitoring pressure distribution data of all parts of the body of a lying person in real time; the multi-air-chamber dynamic adjusting structure comprises a plurality of independent air chambers capable of being inflated and deflated, and the air chambers are distributed in the mattress and used for adjusting the supporting pressure of the corresponding areas according to instructions; the edge intelligent control module analyzes data based on a preset artificial intelligence algorithm to predict a bedsore occurrence risk area, and generates a control instruction according to a prediction result to drive the multi-air-chamber dynamic adjustment structure to adjust the pressure of each air chamber; and the environment regulation and control system comprises a temperature and humidity sensor and a microenvironment regulation device. Through real-time body pressure monitoring, AI risk prediction, dynamic pressure regulation and temperature and humidity coordinated regulation and control, local pressure can be remarkably reduced, a high-risk area can be early warned in advance, and a local microenvironment is improved, so that bedsores are effectively prevented, and nursing dependence is reduced.

The invention discloses a tactile glove array signal super-resolution reconstruction method based on a diffusion model. Low-resolution tactile array samples and high-resolution tactile array samples are collected from the self-developed flexible tactile glove and are used as a data set, super-resolution reconstruction from the low-resolution tactile array to the high-resolution tactile array is performed by using a deep learning method, and the super-resolution reconstruction aims at realizing super-resolution reconstruction from the low-resolution tactile array to the high-resolution tactile array through fewer pressure sensing points. And the distribution of more pressure sensing points is accurately reconstructed, so that the cost of hardware is greatly reduced in a software optimization mode. According to the method, super-resolution reconstruction is carried out on the array signal by using the diffusion model, and the method not only obtains a better effect than other traditional deep learning methods, but also is a primary attempt of the diffusion model in the field of array signals.