5106 results about "Pressure sensor" patented technology

The invention relates to the technical field of industrial automation control, in particular to a container liquid level measurement method, system and equipment of a pressure sensor and a medium, and provides a method for eliminating gas phase pressure influence based on a double-sensor differential measurement mechanism and dynamically correcting liquid density and sensor drift errors in combination with a temperature compensation model. The temperature data are linked in real time through a three-dimensional compensation function, density calculation and drift correction are synchronously adjusted, and multi-parameter dynamic decoupling and self-adaptive compensation are achieved; a collaborative measurement mechanism is adopted to integrate bottom and top sensor data, and a built-in temperature probe and a preset threshold are combined to complete multi-source signal fusion and compensation calculation; a dynamic calibration method is designed, and system errors are eliminated through reference pressure point calibration and structure coefficient correction; constructing a closed-loop signal processing flow, and integrating high-precision analog-to-digital conversion, digital filtering and real-time algorithm to output a compensated liquid level value; the method improves the measurement precision and stability, and is suitable for temperature change, gas phase pressure fluctuation and multi-medium scenes.

The invention relates to the technical field of slope stability data identification, and particularly provides a multi-sensor fusion slope stability intelligent analysis system and an edge calculation method.The system comprises an environment sensing subsystem, a data processing subsystem and an edge calculation subsystem, the environment sensing subsystem monitors the change of the soil moisture content through a soil humidity sensor, and micro movement data of a slope are obtained through a displacement sensor; using a pressure sensor to sense the change of the ground pressure; meanwhile, pre-screening out abnormal data to form a fused data set; the data analysis subsystem is used for converting abnormal data of the fusion data set into a quantitative index of slope stability, and deducing a potential sliding risk of the slope by analyzing the relevance of the soil water content, the tiny movement data or the ground pressure; and the decision support subsystem provides specific reinforcement countermeasures according to the analysis result of the potential sliding risk. According to the method, the potential sliding risk of the side slope is comprehensively deduced by analyzing the relevance of the soil water content, the tiny movement data and the ground pressure.

The invention relates to the technical field of parameter adjustment, and discloses a low-temperature evaporative crystallization machine parameter adjustment method, device and equipment and a storage medium, and the method comprises the steps: collecting M groups of temperature sensor data and N groups of pressure sensor data of a low-temperature evaporative crystallization machine, calculating a first uncertainty representation of temperature parameter measurement and a second uncertainty representation of pressure parameter measurement; performing data fusion to obtain an optimal estimated value of a temperature state and an optimal estimated value of a pressure state; parallel prediction is carried out through the thermodynamic equilibrium model, the crystallization kinetic model and the system response model, and a crystallization process prediction result is obtained; according to the technical scheme of the invention, the interference of the feeding fluctuation, the environmental change and the like can be effectively handled, and the real-time updating of the control strategy and the accurate adjustment of the temperature and pressure parameters can be realized.

The invention relates to the field of building settlement monitoring, and discloses a multi-source data-artificial intelligence fused building deviation rectification settlement prediction method and system, and the method comprises the following steps: multi-source data collection: obtaining multi-class sensor data related to building settlement, the multiple types of sensors comprise a level gauge, a total station, an underground water level sensor and a soil body pressure sensor, and multi-modal data input is formed; the invention also discloses a multi-source data-artificial intelligence fused building deviation rectification settlement prediction system. The system comprises a data acquisition module, a data processing module, a deep learning prediction module, a model optimization module, an intelligent early warning module and a user interaction module. According to the invention, by dynamically adjusting the settlement risk threshold and introducing a multi-stage early warning signal and an intelligent decision support system, accurate early warning and real-time decision support of the settlement risk are realized, and the adaptability, accuracy and response efficiency of the system are significantly improved.

According to the technical scheme, the automatic feeding system comprises a feeding bin, a pneumatic conveying pipeline, an air source device and a discharging bin, and further comprises a distributed sensor set used for monitoring the flux, pressure, temperature and vibration frequency spectrum of a preset point of the pneumatic conveying pipeline; comprising a flow sensor, a pressure sensor, a temperature sensor and a vibration acceleration sensor which are arranged at a plurality of preset points of a conveying pipeline, and a digital twin model building module which is used for building three-dimensional modeling of the pneumatic conveying pipeline and mapping state parameters of all positions of a pipeline distribution sensor group in real time; the blockage analysis module is used for marking a blockage position to three-dimensional modeling in real time based on data acquired by the distributed sensor group, extracting a multi-parameter change curve in a time period T before blockage, constructing a blockage feature library, and generating a blockage risk level through a weight change rate difference value of a feeding bin and a discharging bin; and the graded dredging execution module is configured with a differentiated dredging strategy, and the differentiated dredging strategy is started according to the blockage risk grade.

The invention relates to the technical field of directional drilling track control, and discloses a coal mining underground directional drilling track control method and system, and the method comprises the steps: carrying out the fusion track analysis of a drilling machine based on sensor data, drilling parameters and pre-obtained geological hardness parameters, and obtaining a reference track of the drilling machine, a sensor, an azimuth angle sensor and a bit pressure sensor are used for synchronously collecting drill bit attitude data of a drilling machine to generate a real-time track of the drilling machine, then track offset calculation is carried out to obtain inclination angle deviation and azimuth angle deviation, and dynamic gain adjustment analysis is carried out on the drilling machine to obtain adjustment parameters of the drilling machine. And finally, the drill bit posture of the drilling machine is adjusted based on the adjusting parameters. According to the method, the directional control accuracy of the underground drilling track can be improved.

The invention discloses a lower limb exoskeleton gait track prediction method based on an LSTM-KAN fusion model, and the method comprises the steps: collecting human motion data through a sensor assembly, and carrying out the filtering, missing value processing and normalization of the human motion data; then constructing an overall architecture of a prediction model based on an LSTM-KAN network, optimizing parameters of the prediction model by using a particle swarm optimization (PSO) algorithm, extracting key features in the preprocessed data as a training data set, and inputting the training data set into the prediction model for training; and finally, collecting current human body motion data, pre-processing the current human body motion data, inputting the pre-processed current human body motion data into the trained prediction model, and outputting future human body gaits and tracks by the prediction model. And the controller takes a future gait track generated by the prediction model as a reference track to generate a driving signal and sends the driving signal to the actuator so as to realize accurate control of the actuator. By adopting the gyroscope sensor, the acceleration sensor and the pressure sensor for gait estimation, exoskeleton motion control can be effectively improved, and man-machine interaction experience is effectively improved.

The invention relates to the technical field of mine equipment monitoring and maintenance, and discloses a mine equipment state monitoring and maintenance method based on the Internet of Things, which comprises the following steps: S1, multi-source data acquisition: synchronously acquiring equipment operation parameters and environmental parameters through vibration, temperature and pressure sensors and environmental sensors deployed on mine equipment; s2, edge calculation processing: performing filtering and anomaly detection on the sensor data at a mine edge gateway to generate a compressed data packet; s3, online learning and model dynamic updating; s4, new equipment is accessed; s5, maintenance decision and resource scheduling; and S6, performing closed-loop feedback optimization. High-error historical sub-trees are dynamically eliminated, new sub-trees are generated, model parameters are adjusted in combination with maintenance feedback data, on the basis that historical effective knowledge is reserved, equipment dynamic features are extracted, accurate matching of prediction results and maintenance strategies is ensured, and the self-learning ability and maintenance decision reliability of the model are remarkably improved.

The invention provides a multichannel gas ultrasonic flowmeter, which relates to the technical field of flow measurement and comprises a hardware layer and a software layer, the hardware layer comprises a pipeline, a connecting mechanism, a multichannel ultrasonic transducer, a pressure sensor, a temperature sensor, a wiring terminal box and a control box with an LCD display screen; the software layer comprises a data acquisition module, a preprocessing module, a multichannel speed measurement module, a data fusion module, a dynamic parameter compensation module, a flow calculation module, a man-machine interaction module, a communication module and a storage module. Pipeline section flow velocity information is collected through a multichannel ultrasonic transducer array, and a complex flow state is fitted in combination with a weighted fusion algorithm; the flow is dynamically compensated and corrected based on pressure and temperature; reliable operation of the system is guaranteed by means of hardware redundancy and a software verification diagnosis mechanism, the problems that a traditional flowmeter is low in measurement precision and poor in working condition adaptability are solved, and high-precision and stable gas flow measurement is achieved.

The invention relates to the technical field of urban drainage management, and discloses a municipal sewage pipe network dynamic drainage system and a control method, and the system comprises a sewage pipe network, a central controller, a pump station, a valve and an edge control terminal; the control method comprises the following steps that real-time data are obtained from a plurality of sensors arranged in a sewage pipe network, the plurality of sensors comprise a flow sensor, a water level sensor, a pressure sensor and a rainfall sensor, and the obtained real-time data comprise the sewage flow, the water level, the pipeline pressure and the external rainfall inflow in the pipe network; based on the collected real-time data, dynamic hydraulic modeling is carried out on the sewage pipe network through a central controller, a mathematical model for describing the hydraulic state change of the pipe network is established, and the mathematical model comprises spatio-temporal evolution of flow, water level and pressure. According to the invention, by constructing a drainage scheduling mechanism based on real-time data modeling and edge control linkage, dynamic adjustment and stable control of the running state of the sewage pipe network are realized.

The invention relates to the technical field of water supply pipeline detection, and discloses an underground water supply pipeline health grade evaluation and risk prediction method, which comprises the following steps: sensor arrangement: arranging a flow sensor, a pressure sensor and a sonic sensor at key positions of an underground water supply pipeline; and data acquisition: acquiring signals of the sensor in real time through a data acquisition module, wherein the signals comprise flow, pressure and sound wave signals. Preprocessing the data: carrying out preprocessing such as denoising and normalization on the collected signals; and multi-source data fusion: inputting flow, pressure and sound wave signals into a deep neural network model, and performing feature extraction and fusion analysis. And health level assessment: assessing the health level of the pipeline based on the output result of the deep neural network model. And risk prediction: predicting abnormal working conditions possibly occurring in the future and risk levels of the abnormal working conditions by analyzing the current pipeline state and historical data. And abnormal positioning: accurately positioning an abnormal position in combination with the propagation time of the sensor signal and a positioning model of the deep neural network.

The invention discloses a device judging whether or not an earth pressure balance shield earth chamber is full. The device comprises a pressure detector disposed on the upper portion of a front shield earth chamber of the earth pressure balance shield; the signal output end of a pressure sensor is connected with an upper computer; the upper computer judges whether or not the chamber is full; if not, a warning signal is sent to an alarm unit. The device has the advantages that whether or not the earth chamber is full can be judged anytime during earth pressure balance shield tunneling, full-chamber shield tunneling can be ensured and the application of full-chamber tunneling decreases the danger of collapse ahead.

The invention discloses a near-infrared on-line intelligent detection system and method for material moisture of a conveying belt, and relates to the technical field of material moisture detection.The system comprises a material and environment information acquisition module, a data processing module and a data processing module, meanwhile, temperature, humidity and air pressure sensors are used for monitoring changes of environmental factors in real time, equipment is calibrated and maintained regularly, and parameters are initialized before detection; according to the invention, material characteristic pre-identification and environmental factor real-time sensing functions are integrated, and parameters of the near-infrared detection module are dynamically adjusted by using an intelligent algorithm so as to adapt to changes of different material characteristics and environmental factors, so that the detection system can accurately detect various material characteristics in a complex and changeable industrial field environment. And high-precision and high-stability moisture detection can still be maintained.

The invention provides a solution concentration real-time detection method based on focusing offset of a compound lens, which comprises the following steps: step A, laser emitted by a laser diode is collimated into parallel light through a plano-convex lens, the parallel light is emitted into a sample cell through a glass window, and then the parallel light is emitted by the compound lens to be imaged on an image sensor; step B, the parallel light is emitted to an image sensor through a compound lens to be imaged into two light spots, the distance # imgabs0 # between the two light spots on the image sensor is recorded, and the solution concentration is inversed through the distance # imgabs1 # between the two light spots; step C, respectively detecting the temperature and the pressure intensity of the solution to be detected through a temperature sensor and a pressure sensor, and compensating the influence of the temperature and the pressure intensity on measurement through an algorithm; on the basis of light spot form analysis of the compound lens, the solution concentration is inversed, the resolution capability of a low-concentration transparent solution is improved, and the detection stability of transparent solutions such as alcohol is improved.

The invention relates to the technical field of agricultural management, in particular to a smart farm environment regulation and control method and system based on big data analysis, and the method comprises the following steps: obtaining an instantaneous temperature value of the upper surface of a leaf and an instantaneous temperature value of the lower surface of the leaf through an infrared temperature sensor, obtaining an instantaneous value of stomatal conductance through a stomatal conductance sensor; and acquiring a water vapor pressure difference value of the air cavity through a water vapor pressure sensor, aligning a time sequence by adopting a multi-source data fusion algorithm, eliminating noise, and generating a dynamic physiological data set. According to the method, the leaf temperature difference, the air hole conductance and the air cavity water vapor pressure difference are collected, a real-time dynamic data set is constructed, a temperature difference amplification signal is extracted, transpiration enhancement triggering, wind speed increasing, water mist particle size decreasing and wind speed and particle size linkage regulation and control are analyzed in combination with the trend, a regulation and control weight is constructed by introducing multiple regression analysis, and the wind speed and the particle size are dynamically regulated according to the weight. A leaf temperature difference regression base line is guaranteed, the regulation and control accuracy and physiological adaptability are improved, and the environment self-adaptive regulation capability is enhanced.

The invention discloses a temperature compensation method and system, and the method comprises the steps: receiving a valve block temperature signal collected by a temperature sensor integrated with a pressure sensor in a closed gas supply unit, and an electronic element temperature and environment temperature signal collected by a temperature sensor on a control unit PCB, generating an initial temperature-working condition data set by combining the power of the air pump and the working duration of the electromagnetic valve; performing thermal resistance network modeling on the initial temperature-working condition data set, constructing a multi-node thermal characteristic matrix, and decomposing the matrix into a plurality of sub-matrixes; performing real-time operation on the sub-matrix by using a dynamic heat balance algorithm to generate a temperature estimation result of the key component; and generating a temperature compensation control instruction according to the temperature estimation result of the key component. According to the embodiment of the invention, the temperature of the key component can be accurately estimated, dynamic compensation is realized, and the control precision and stability of the closed gas supply unit are improved.

The invention provides grouting and filling equipment for water-preserved mining of a coal mine, and relates to the technical field of mining equipment, and the grouting and filling equipment comprises a base frame piece, a grouting guide pipe piece, a slurry post-processing assembly and a plugging driving assembly. A plurality of groups of outer ring parts with hole wall pressure sensors are arranged on the outer wall of the grouting guide pipe piece, and a pipe end micro sensor is arranged at the grout outlet end; the inserting and pulling driving assembly drives the stirring assembly to push the outer ring part through the motor, and inserting and pulling of the grouting guide pipe piece are controlled. During working, the guide pipe piece is inserted into a grouting hole to a goaf, the sensor monitors rock mass pressure, temperature and sound wave signals in real time, the grouting pressure is dynamically adjusted in combination with formation resistance, and grout fluid channeling or insufficient filling is avoided. Through precise pressure regulation and automatic insertion and extraction, the problems of material waste, underground water pollution and insufficient goaf filling in traditional grouting are solved, and the environmental protection property and the engineering efficiency of water-preserved mining are remarkably improved.

The invention discloses a gas pipeline operation risk dynamic evaluation system based on big data analysis, and relates to the technical field of gas pipeline safety monitoring, and the system comprises a multi-source data processing module, a feature extraction module, a local risk modeling module, a risk evolution prediction module and a dynamic early warning module. The multi-source data processing module is used for acquiring original multi-source time sequence data from a pressure sensor, a flow sensor, a temperature sensor, a geological monitoring device and a third-party construction disturbance data interface of a gas pipeline network, and performing time alignment, abnormity elimination, normalization and characteristic standardization processing on the data; a uniform input feature vector is formed; and the feature extraction module is used for decomposing the normalized time series data into a low-frequency trend component and a high-frequency residual signal by using discrete wavelet decomposition. The gas pipeline risk assessment system solves the problems of low gas pipeline risk assessment precision, insufficient risk propagation modeling and lack of dynamic early warning and emergency strategies in the prior art.

The disclosure relates to the technical field of air pumps, and particularly relates to an air pump having a reminding function. The air pump includes a pump cylinder provided with a first hollow cavity and a push rod assembly that is pullable. The push rod assembly is movably inserted into the pump cylinder. The air pump further includes an air pressure sensor and a reminding mechanism. The air pressure sensor and the reminding mechanism are both mounted in the pump cylinder or the push rod assembly. The air pressure sensor is connected with the reminding mechanism. An objective of the disclosure is to solve a problem that an existing manual air pump cannot give a reminder when air extraction is completed, and provide an air pump having a reminding function when air extraction is completed.

The invention relates to the technical field of wind tunnel tests, in particular to a large-scale model wind tunnel test device and a debugging method thereof. The scale model wind tunnel test device comprises a supporting device which comprises an upper supporting truss, a lower supporting truss and a plurality of supporting stand columns, the upper supporting truss and the lower supporting truss are composed of main beams and anchoring structures, the supporting stand columns are connected with the upper supporting truss and the lower supporting truss, and sliding rails are symmetrically arranged on the upper supporting truss and the lower supporting truss. The large-scale model is connected between the two sliding rails through a line spacing adjusting device and an inclination angle adjusting device, large-scale model assemblies are fixed to the upper end and the lower end of the large-scale model through detachable force transmission plates, and the force transmission plates are connected with a force measuring balance; the large-scale model is provided with a pressure measuring hole, and the scale ratio of the large-scale model is greater than 1: 20; a wind pressure sensor is arranged in the data acquisition device, the data acquisition device is connected with the pressure measuring hole of the large-scale model through a pressure measuring pipe, and wind pressure is transmitted to the wind pressure sensor of the data acquisition device through the pressure measuring pipe. The large-scale model wind tunnel test device and the debugging method thereof are convenient and fast to install and flexible to adjust.

The invention relates to the technical field of engineering construction, and particularly discloses a pavement flatness measuring device for engineering construction, which comprises an eight-wheel instrument for measuring the flatness of a pavement; the detection mechanism is installed in the eight-wheel instrument support, and the detection mechanism detects the friction coefficient of the road surface before the device runs; the road surface friction coefficient is detected in advance through the adjusting mechanism, the adjusting mechanism dynamically adjusts the position of a pressure sensor and the ground clearance of a detection wheel according to the friction coefficient, and a fixed motor is started to drive a rotating ring to rotate through a rotating roller and a synchronous belt to drive a second lead screw to rotate; the movement of the second moving member can drive the eight-wheel instrument supporting seat to move up and down, thereby adjusting the ground clearance of the detection wheel, effectively compensating the data deviation caused by the wear of the detection wheel, and improving the accuracy and stability of the measurement result.

The invention discloses an active anti-floating drainage model test device and test method considering saturation change, and belongs to the technical field of active anti-floating of buildings. The test device comprises a boundary model box, a building model box, a plurality of pore pressure sensors, a plurality of dielectric constant sensors, a pressure limiting drainage pipe for simulating active anti-floating equipment in an actual building, a water head control device and a rainfall simulation device, and can simulate a seepage field of an underground space under the condition of active anti-floating measures during rainfall. The drainage condition of the underground space under the condition is reproduced; the pore pressure sensor and the dielectric constant sensor monitor the saturation change of the soil body in real time, the vacancy of the existing test device in the saturation change factor of the soil body is filled up, the drainage condition of the active anti-floating measure and the seepage law of the soil body in the unsaturated-saturated transition process of the soil body under different rainfall and different stratum conditions can be demonstrated, and the test device has a wide application prospect. Scientific basis and data support are provided for optimization application of active anti-floating measures under different saturation working conditions.

The invention relates to the technical field of power transmission line safety monitoring, and particularly discloses a self-adaptive calibration method for an ultrasonic wind speed sensor, which comprises the following steps of: arranging an orthogonal ultrasonic probe array at the top of a tower, and compensating probe offset caused by swinging of a tower body in real time through GNSS / IMU (Global Navigation Satellite System / Inertial Measurement Unit) fusion positioning; integrating a temperature, humidity and pressure sensor and vibration spectrum analysis to construct an environmental parameter compensation model; double-frequency ultrasonic waves are adopted to detect the ice accumulation thickness of the protective cover and correct the sound path distance; deploying a lightweight LSTM model at an edge computing unit to realize minute-level dynamic parameter adjustment; electromagnetic interference is suppressed by combining linear frequency modulation spread spectrum and beam forming technologies; and establishing a three-height-layer wind speed gradient model to generate a galloping early warning. The problem of measurement distortion caused by tower deformation, icing and parameter solidification of a traditional sensor is solved, all-working-condition operation from-40 DEG C to 60 DEG C is supported, and the monitoring reliability in a strong electromagnetic environment is remarkably improved.

The invention relates to the technical field of viscosity measurement, and discloses a verification system for a viscometer, comprising: a dynamic temperature compensation module for collecting temperature data inside and outside the viscometer in real time; the embedded controller is responsible for receiving the temperature data, executing a temperature compensation process and outputting a temperature compensation coefficient and an initial viscosity value; the multi-modal data fusion calibration module is used for receiving a temperature compensation coefficient provided by the multi-modal data fusion calibration module and data from a pressure sensor, a shear rate sensor and a vibration sensor, and carrying out joint modeling on the data by utilizing a weighted average method; the invention also discloses a verification method for the viscometer, which comprises the following steps: acquiring temperature data inside and outside the viscometer through the temperature sensor, and performing temperature compensation through the embedded controller. According to the invention, the multi-modal data fusion calibration module is introduced, and data from a plurality of sensors are integrated through a weighted average method, so that the optimized viscosity value is more comprehensive and reliable.

The invention relates to the technical field of intelligent robots, and discloses an automobile cabin intelligent robot arm device which comprises a multi-axis robot arm, a controller, an in-automobile space sensing device and an intelligent interaction device, and the multi-axis robot arm, the controller, the in-automobile space sensing device and the intelligent interaction device are all installed in an automobile cabin. The robot arm comprises a base rotating motor, an arm motor, a palm motor, a capacitance sensor, a pressure sensor, a USB / Type-C interface, a wireless charging interface, a magnetic attraction interface and the like. The in-vehicle space sensing device comprises a camera, a millimeter wave radar and the like. According to the intelligent robot arm device of the automobile cabin, the intelligent robot arm is controlled through voice or keys and the like, and the robot arm replaces personnel to complete object taking operation at a long distance or a view blind area position; distraction caused by the fact that a driver takes objects towards the back row can be avoided, and driving safety is improved. Meanwhile, the intelligent robot arm is controlled through voice or keys and the like, and the robot arm replaces personnel to complete service operations such as article storage, article fixing, games and caring; and the intelligent experience of the cabin is improved.

The invention discloses an industrial gas production monitoring system based on data processing, and relates to the technical field of online monitoring, and the industrial gas production monitoring system comprises a data acquisition module which uses a plurality of sensors with determined positions to acquire real-time parameters in the industrial gas production process; the raw material gas detection module is used for acquiring raw material gas data through various sensors arranged at a raw material gas inlet and a raw material gas outlet and carrying out raw material quality detection on the raw material gas; the parameter monitoring module is used for detecting process parameters of gas production through a temperature sensor, a flow sensor and a pressure sensor; the safety detection module is used for carrying out leakage detection on the industrial gas production device and carrying out factory environment detection by using a multi-gas composite detector; the quality detection module is used for detecting the quality of the produced industrial gas by using a high-sensitivity sensor and a mass spectrometer; and the early warning module is used for carrying out fault detection on the industrial gas production based on all the obtained data and sending out safety early warning according to a fault detection result.

The invention is applicable to the technical field of concrete deformation measurement, and particularly relates to a non-contact concrete deformation testing system and method based on a laser ranging technology, and the system comprises a laser ranging unit which is provided with a double-frequency phase modulation laser, an optical transceiver antenna and a phase detection circuit; the environmental parameter acquisition unit comprises a temperature sensor, a humidity sensor and an air pressure sensor; and the data processing unit carries an atmospheric refractive index calculation module, a Kalman filtering algorithm and a three-level early warning module, and supports wired / wireless data transmission. The distance measurement precision is high, and the concrete micro-deformation monitoring requirement is met; non-contact characteristic: non-damage monitoring on the concrete surface is realized through a diffuse reflection target; intelligent data processing: structural deformation and environmental noise are effectively distinguished, and the early warning reliability is improved; automatic monitoring is achieved, and the manual inspection cost is greatly reduced.

The invention relates to the technical field of liquid level detection, in particular to a method for eliminating a false liquid level of a urea hydrolyzer, which comprises the following steps: S1, acquiring a liquid level sensor signal, a pressure sensor signal, a temperature sensor signal and an ultrasonic reflection signal of the urea hydrolyzer in real time; s2, performing weighted fusion to generate fused liquid level characteristic parameters; s3, identifying false liquid level characteristics caused by foam layer coverage or steam interference; s4, generating a calibration liquid level value according to the false liquid level characteristics; and S5, comparing the calibrated liquid level value with a preset liquid level-pressure-temperature relation model, and outputting a real liquid level value. According to the invention, by fusing various sensor signals in real time, dynamically adjusting the parameters of the liquid level sensor and combining the liquid level-pressure-temperature relation model, false liquid level interference is accurately eliminated, the accuracy and reliability of liquid level measurement are improved, meanwhile, the equipment safety is ensured, and abnormal operation caused by false liquid level signals is prevented.

The invention discloses a flexible pressure sensor with a multistage hemispherical structure and a preparation method thereof, the sensor comprises an electrode layer, and an upper friction layer, a separation layer and a lower friction layer which are sequentially arranged below the electrode layer from top to bottom, the separation layer is used for providing a space for full contact and separation of the upper friction layer and the lower friction layer, and the separation layer is used for providing a space for full contact and separation of the upper friction layer and the lower friction layer. And the lower friction layer is formed by a multi-stage hemispherical structure constructed on the surface of a flexible film. The sensor has the remarkable effects that benefited from the characteristics of a triboelectric sensing mechanism, the sensor has the advantages of self power supply, stable output and simple structure, and meanwhile, the upper friction layer and the lower friction layer of the sensor are in step-by-step contact under the action of pressure through the surface microstructure of the lower friction layer of the multi-stage hemispherical structure; the compressibility is enhanced, and the contact and separation process of the sensor is optimized, so that the sensitivity of the sensor is improved.

The invention relates to the technical field of sensitive elements, in particular to a sensitive element of a multi-gradient interlocking structure, a preparation method and a flexible pressure sensor. The sensitive element comprises a packaging layer and a functional layer, and the packaging layer is used for maintaining the form of the functional layer. The functional layer comprises an upper electrode layer, an ionic medium layer and a lower electrode layer which are sequentially arranged from top to bottom. A plurality of first protrusions are arranged on the side, facing the ionic dielectric layer, of the upper electrode layer, and a plurality of second protrusions are arranged on the side, facing the upper electrode layer, of the ionic dielectric layer. The heights of the first protrusions are gradually increased from left to right, and the heights of the second protrusions are gradually reduced from right to left. The first protrusions and the second protrusions are arranged in a staggered mode so as to form a capacitance change area of a multi-gradient interlocking structure. The flexible pressure sensor made of the sensitive element has high sensitivity on the basis of a wide detection range, and is suitable for application scenes such as human health information monitoring and wearable equipment.