1128 results about "Strain sensor" patented technology

The invention belongs to the technical field of water conservancy and hydropower engineering, and discloses a water conservancy and hydropower engineering construction safety supervision system based on multi-source data fusion. The system comprises a multi-source sensing acquisition module, a heterogeneous data fusion processing module, a risk identification and early warning module, a safety behavior evaluation and feedback module, and a command scheduling and visualization module. According to the invention, by fusing multi-dimensional data such as image monitoring, environment sensing, personnel positioning, equipment state and the like, a space-air-ground three-dimensional sensing network is constructed, and in a high slope area, the distributed optical fiber strain sensors are linked with thermal imaging data of the unmanned aerial vehicle, so that millimeter-level deformation and temperature field abnormity can be captured in real time; a video stream is analyzed in real time by means of a YOLOv8 algorithm, illegal operation behaviors of personnel can be accurately identified, a cross-modal fusion model of a Transform architecture is combined, the system can dynamically capture potential correlation among data, and millisecond-level response to risks such as side slope landslide, equipment faults and personnel dangerous operation is achieved.

The invention provides a multi-source heterogeneous data fusion side slope digital twin modeling method, which comprises the following steps of: acquiring side slope multi-dimensional monitoring data by arranging a GNSS (Global Navigation Satellite System) sensor, a multi-point displacement meter, a distributed optical fiber strain sensor, an accelerometer, an osmometer, a monocular camera and satellite remote sensing image equipment; the collected data is converted into a unified format through time alignment, space registration and standardization processing and serves as modeling input; the method comprises the following steps: constructing an initial digital twinborn model reflecting the real form and physical characteristics of a slope by utilizing a three-dimensional modeling and finite element simulation technology; in combination with real-time sensing data, model evolution is dynamically driven based on a space-time fusion algorithm, boundary conditions and material parameters are automatically corrected through actual measurement deviation feedback, and continuous twin iteration updating of the model is achieved; and finally, extracting a landslide risk index to realize real-time early warning of the side slope. According to the invention, multi-source sensing and digital twinborn fusion is realized, and the accuracy, real-time performance and intelligent level of slope monitoring are improved.

A robotic surgical system includes one or more robotic actuators configured to interact with biological tissue during a surgical procedure. A plurality of sensors include at least one of fiber Bragg grating sensors, piezoelectric strain sensors, or magnetostrictive sensors to capture real-time mechanical, elasticity, or deformation data from biological tissues. deep learning engine trained on a dataset comprising tissue mechanical responses across multiple tissue types, pathological states, and patient demographics. Pre-contact predictive adjustment profiles are generated for anticipated tissue interactions using preoperative imaging data registered to intraoperative coordinates. Intraoperative deviations are detected from predicted mechanical behavior and autonomously recalibrate actuator forces. Upcoming surgical maneuvers are anticipated based on prior task sequences and adjust actuator stiffness or damping properties in preparation for anticipated contact. An emergency override of actuator forces is provided via an anomaly detection module when real-time sensor data deviates beyond a threshold from the predicted safe mechanical response range. A feedback loop iteratively refines the deep learning engine during the procedure using supervised learning updates, anomaly detection, and reinforcement learning strategies. The reinforcement learning model is optionally shared across procedures to optimize distributed actuator force patterns for minimizing localized and cumulative tissue stress.

The invention discloses a power transformer arc discharge multi-parameter detection simulation platform and a fault diagnosis method, and relates to the technical field of power system equipment state monitoring and fault diagnosis. The platform comprises a transformer body, a replaceable discharge module, a multi-parameter sensing unit and a signal processing and diagnosis module, and can truly reproduce various typical arc discharge faults of a needle plate, an air gap, a creeping surface, turn-to-turn and the like. The sensing unit is integrated with ultrahigh frequency and ultrasonic sensing probes, high-frequency current and voltage sensors, optical fiber temperature / pressure / strain sensors and the like, so that synchronous acquisition of multi-physical field signals is realized. According to the diagnosis method, through wavelet denoising and multi-dimensional feature extraction, a feature vector of multi-state parameter fusion in the process from partial discharge to arcing is constructed, and accurate classification of fault types is realized by using a support vector machine (SVM) model. The diagnosis method has high accuracy and early warning capability, effectively overcomes the limitation of single parameter diagnosis, and provides reliable technical support for transformer fault research and intelligent operation and maintenance.

The invention relates to the technical field of intelligent medical treatment, and discloses an intelligent knee joint rehabilitation system based on Internet of Things, comprising: a flexible multi-parameter sensing module for collecting a multi-modal biological signal of a knee joint; the edge calculation module is used for processing and analyzing sensing data in real time; the dynamic impedance adjusting module is used for dynamically adjusting impedance parameters of rehabilitation training according to the real-time data; the cloud-side collaborative decision module is used for realizing efficient transmission and collaborative decision of data; and the self-adaptive rehabilitation strategy engine is used for optimizing rehabilitation training parameters and comprises a real-time intensity adjustment module based on an improved TD3 reinforcement learning algorithm. According to the system, the flexible strain sensor array unit, the 9-axis inertial measurement unit and the surface myoelectricity sensing unit are integrated through the flexible multi-parameter sensing module, and multi-dimensional real-time monitoring of knee joint strain distribution, three-dimensional acceleration, angular velocity, magnetic field data and myoelectricity signals is achieved.

The invention relates to an intelligent soft rock tunnel surrounding rock deformation automatic monitoring and early warning system, and belongs to the field of tunnel construction safety monitoring. According to the system, multi-source data of surrounding rocks are synchronously acquired through a micron-sized laser displacement sensor, a fiber grating strain sensor, a pore water pressure sensor and a three-dimensional micro-seismic sensor array which are distributed; the edge calculation node fuses the data in real time and calculates the displacement rate, the strain gradient and the osmotic pressure coupling coefficient, and local early warning is triggered in combination with a dynamic threshold value; the cloud early warning platform predicts a deformation trend based on an LSTM-Transform fusion model, generates a multi-stage early warning signal through a risk grading engine, and is linked with the supporting equipment to regulate and control pressure; and meanwhile, a self-calibration device, an explosion-proof shell and a piezoelectric-thermal energy self-powered system are integrated. According to the method, closed-loop control from millimeter-level deformation sensing to active supporting can be achieved, and tunnel construction safety is remarkably improved.

The invention belongs to the technical field of civil engineering monitoring, and discloses an optical fiber strain sensor performance verification method and system for highway infrastructure monitoring, and the method comprises the steps: analyzing the influence rule of the parameter change of a coupling layer on the strain transmission efficiency of a measured sensor based on a layered material coupling mechanical model; based on the three-dimensional entity numerical model, analyzing an influence rule of layout process parameters of the tested sensor on the strain transmissibility; verifying the performance of the sensor in a laboratory environment by using a reduced scale model; on a real highway infrastructure or a constructed full-scale model, the performance of the sensor on an actual structure is verified through monitoring data. According to the invention, by constructing an integrity performance verification system from a theoretical model to numerical simulation and then to a reduced scale model test and entity structure verification, multi-dimensional and progressive performance verification of the performance of the optical fiber strain sensor for highway infrastructure monitoring is realized.

The invention provides a parameter monitoring method and system in a composite material preparation process based on optical fiber sensing, computer equipment and a medium, and belongs to the field of composite material detection. Center wavelength signals in the resin diversion stage are continuously collected through optical fiber strain sensors in a distributed optical fiber grating sensing array, and the distributed optical fiber grating sensing array is embedded into the multiple layers of dry carbon fiber cloth in the fiber preform in advance; the flowing position and time of the resin in the fiber prefabricated body are determined according to the minimum value of the central wavelength signal offset in the resin flow guide stage, and the flowing front edge of the composite material is constructed according to the flowing positions and time of the resin corresponding to the optical fiber strain sensors in the fiber prefabricated body. According to the method, the change of the structure state of the composite material in the resin diversion process can be continuously monitored in a complex variable-temperature environment, and the accurate monitoring of the three-dimensional resin flowing front edge in the composite material liquid forming process is realized.

The invention provides a low-temperature-resistant performance evaluation method for a composite material, and belongs to the technical field of material performance determination.The method comprises the steps that firstly, in a low-temperature environment box, a temperature sensor is used for accurately controlling the temperature of a sample, and meanwhile, a high-frequency strain sensor is used for collecting data; then, wavelet transform is adopted to carry out denoising and decomposition on the strain signals, and key low-temperature characteristic parameters are extracted; and constructing a performance evaluation model based on deep learning, inputting the temperature field, the strain characteristics and the material basic parameters into the model, and predicting the low-temperature strength. A prediction result is verified through a standard test, a prediction error is calculated, an error distribution matrix is established, and an improved back propagation algorithm is adopted to optimize the model. Finally, a fuzzy comprehensive evaluation method is applied, indexes such as strength retention rate and strain stability are comprehensively considered, and the low temperature resistance grade of the composite material is scientifically evaluated. The method solves the problem that the actual mechanical properties of the composite material in the low-temperature environment are difficult to comprehensively reflect in the prior art.

The invention relates to a flexible strain sensor for ship cable safety monitoring and a preparation method and application thereof. The flexible strain sensor comprises a flexible substrate layer, a composite conductive sensitive layer and an environment protection packaging layer. The flexible substrate layer is an elastomer grid with a three-dimensional microstructure pattern and is used for bearing and transmitting mechanical stress. The composite conductive sensitive layer is attached to the surface of the three-dimensional microstructure of the flexible substrate layer and used for forming a conductive path changing along with deformation and converting mechanical deformation into a resistance signal. And the environment protection packaging layer coats the flexible substrate layer and the composite conductive sensitive layer, adopts an elastomer component which is homogeneous with the flexible substrate layer, and is used for forming an integrated sealing structure. Compared with the prior art, the problem that a traditional laminated structure is prone to stripping and losing efficacy in seawater is solved, and accurate and lag-free monitoring of the ship mooring rope tension force is achieved through modulus matching.

The invention discloses a large-area concrete pouring vibrating and leveling device and a using method, and belongs to the field of concrete pouring construction. Comprising a walking and stabilizing system, accurate positioning is achieved through four-wheel independent driving, and a hydraulic supporting column and a sliding rail weight box cooperate to dynamically balance overturning moment; the multi-degree-of-freedom telescopic arm system drives an end effector to perform three-dimensional positioning through a multi-stage hydraulic telescopic sleeve and covers a large-area operation area; the intelligent vibrating-leveling execution system and the modularized vibrating system are adopted, eight groups of high-frequency vibrating rods are carried on a main / expansion plate, an ultrasonic sensor is embedded in a rod body protection cylinder to generate a compactness cloud picture in real time, and a hose is driven to integrate a strain sensor to invert the slump; the self-adaptive leveling system and the laser grid scanner construct a three-dimensional elevation model, and the hydraulic elevation regulator realizes + / -0.1 degree grade gradient control. According to the method, traditional layering limitation is broken through, efficiency is improved, porosity and flatness errors are reduced, and manual safety risks are thoroughly eliminated.

The invention discloses a bionic finger, a hand motion control device, a bionic hand control method and a robot, and belongs to the technical field of bionic robotics.The device comprises a plurality of flexible electric actuators which comprise electric actuating materials capable of actively deforming under excitation of an electric field; one end of the flexible electric actuator serves as a fixed end to be connected to the finger adaptation base, and the other end of the flexible electric actuator serves as a free end to be connected to the knuckle structure through a force transmission path. Wherein each flexible electric actuator can be independently controlled, and the plurality of flexible electric actuators cooperatively drive the knuckle structure to generate bionic motion; the passive constraint structure is configured to provide anisotropic mechanical constraint for active deformation of the flexible electric actuator, so that the active deformation is guided and converted into driving displacement or driving force in the first preset direction; and the guide structure is used for guiding the deformation direction of the flexible electric actuator. The device can integrate a strain sensor, an angle sensor and a touch sensor, and realizes closed-loop cooperative control through a controller.

The invention relates to the technical field of engineering performance intelligent detection, in particular to a concrete main tower circumferential prestressed reinforcement anti-cracking prediction method based on machine learning, which is characterized in that fiber grating strain sensors are arranged on the sections of main tower circumferential prestressed reinforcements, and strain data and environmental parameters in tensioning and operation stages are acquired; marking a cracking state to construct a sample data set; carrying out adaptive segmentation and abnormal value elimination operation on the strain sequence to realize data cleaning; constructing a cracking probability prediction model to process the cleaned data to obtain a cracking prediction probability; and calculating the total loss of the model, training the model, inputting newly collected data into the trained model, outputting a cracking prediction probability, and judging whether to carry out early warning or not. According to the method, online, real-time, intelligent and accurate prediction of the cracking risk of the circumferential prestressed steel bars of the concrete main tower can be realized, the monitoring false alarm rate is effectively reduced, and reliable technical support is provided for bridge operation maintenance and safety management and control.

The invention discloses a cable GIS terminal stress-strain sensor and a strain monitoring method thereof, and belongs to the technical field of stress-strain monitoring, and the sensor comprises a sensor structure unit which comprises a metal housing, a fixed contact, a movable contact and a piezoelectric element; the signal processing unit is integrated in the integrated circuit shell and comprises a charge collector used for converting a charge signal of the piezoelectric element into an analog voltage signal; the pulse charge discharger is connected to the output end of the charge collector in parallel; the analog-to-digital converter is connected with the output end of the charge collector and is used for converting the analog voltage signal into a digital signal; the serial communication interface is used for outputting digital signals after analog-to-digital conversion; the mounting unit comprises a fixing hole position and an adhesive base which are arranged on the metal shell; the cable GIS terminal stress strain monitoring device is used for monitoring the stress strain of the cable GIS terminal in the operation process so as to reflect typical structure defects appearing in the cable GIS terminal, and online monitoring of the cable GIS terminal equipment is achieved.

The invention discloses a vibration suppression and surface quality control method for part cutting of a numerical control machining center, which relates to the technical field of numerical control machining and comprises the following steps: multi-modal sensor fusion monitoring: mounting multi-modal sensors on key parts such as a main shaft, a cutter and a workbench of the numerical control machining center, comprising an acceleration sensor, a strain sensor and an acoustic emission sensor and monitors a vibration signal, a cutting force signal and an acoustic emission signal in the machining process in real time; self-adaptive machining parameter optimization is carried out, and machining parameters are preset according to machining task requirements; dynamic adjustment and intelligent feedback control of machining parameters are realized by adopting a vibration prediction model based on deep learning and an adaptive optimization algorithm; according to the technology, the automation level of the machining process is improved, machining errors and surface quality defects caused by vibration are effectively reduced, and the surface roughness and size precision of the workpiece are remarkably improved.

A sensor device (3) for detecting strains in a linear infrastructure component (12), in particular a track rail, comprises a first sensor unit (16, 16') with a first support (28) and at least one strain sensor mounted on the first support (28) for detecting a strain at the first measuring point (19), a second sensor unit (17) with a second support (29) and at least one strain sensor mounted on the second support (29) for detecting a strain at the second measuring point (20), a coupling means (18) connected to the first support (28) and the second support (29) for defining a measuring distance (d) between the first measuring point (19) and the second measuring point (20) along a longitudinal direction (21) of the linear infrastructure component (12), a measuring arrangement (19) with the sensor device (3), a method, and an application device for applying the sensor device (3).

The invention relates to an airlift pump system for conveying solid particles in underwater mining. The airlift pump system comprises a material collecting system, a lifting system, a pneumatic regulation and control system, a recycling system and the like. The material collecting system collects solid particles and guides the solid particles to a lifting opening of the lifting system, the material collecting system comprises a material containing hopper, a material guiding groove, a material collecting table and the like, the lifting system lifts and separates the solid particles and a liquid mixture, and the lifting system comprises an inclined hole air lift pump and a lifting pipe; the pneumatic regulation and control system comprises an electromagnetic valve, a plurality of auxiliary gas injection chambers, an optical fiber strain sensor, a microwave concentration sensor and the like. The recovery system comprises a gas-liquid separator, an axial flow turbine generator, an energy storage device, a stock bin and the like. Pipeline vibration and ore pulp concentration are monitored in real time through the optical fiber strain sensor and the concentration sensor, a PLC control algorithm is combined, the conventional operation mode, the vibration suppression operation mode and the anti-blocking operation mode are automatically switched, and the safety and stability of the airlift pump are greatly improved. The micro axial flow turbine generator is additionally arranged at the exhaust end, and tail gas kinetic energy is converted into electric energy.

The invention discloses a multi-component injection molding machine mold clamping force dynamic cooperative adjusting system and a control method. The adjusting system comprises a movable mold plate, a fixed mold plate and four tiebars connected between the movable mold plate and the fixed mold plate. One end of each of the four tiebars is connected with an adjusting piece for adjusting the tiebars; the distributed sensor unit comprises strain sensors which are respectively arranged on the surfaces of the four tie bars and is used for monitoring the stretching deformation quantity of each tie bar in real time and converting the deformation quantity into a mold clamping force numerical value; the intelligent executing mechanism comprises mold adjusting servo motors which are arranged on the adjusting pieces of the four tiebars respectively, the mold adjusting servo motors are used for driving the adjusting pieces to rotate so as to adjust the pre-tightening force of the tiebars, and the adjusting precision can reach + / -0.01 mm; and the central controller is in signal connection with the distributed sensor unit and the intelligent execution mechanism, and is used for receiving signals of the strain sensors and controlling the intelligent execution mechanism to cooperatively adjust the mold clamping force of the four tie bars.

In certain examples, methods and semiconductor structures are directed to a strain sensor integrated with a membrane substrate, a pressure sensor, and a plurality of material layers. The material layers are to integrate the strain sensor, the pressure sensor and the membrane substrate, with the pressure and strain sensors operating co-operatively to indicate, in response to a force applied to or towards the pressure sensor, characterization information of the force applied and of deformation of the membrane substrate. In a more specific example, the strain sensor and the membrane substrate are integrated with the aforesaid at least one of the material layers, and at least a portion of the pressure sensor and the membrane substrate are stacked to permit sensing of the force concurrently by the strain sensor and the pressure sensor.

The invention relates to the technical field of flexible electronic materials and devices, and discloses a multilayer composite fiber membrane, a preparation method and application thereof, and a flexible strain sensor. The multi-layer composite fiber membrane comprises a polymer membrane and a conductive sulfonated SEBS (Styrene-Ethylene-Butylene-Styrene) membrane which are used as matrix layers, wherein the polymer film is doped with a conductive filler. The flexible strain sensor prepared by using the multilayer composite fiber membrane provided by the invention has high sensitivity and short response recovery time, not only has a monitoring capability for a stretching signal, but also has sensitive response to a pressing signal, can identify weights with different weights, and has very reliable sensing capability.

The invention discloses a linkage regulation and control method and system for a vacuum environment, and belongs to the technical field of vacuum environment regulation and control, and the method specifically comprises the steps: collecting time sequence data of a crystal growth environment in real time, constructing a temperature-vacuum-growth stage three-dimensional mapping relation, and dynamically correcting a vacuum threshold value by combining a furnace body material thermal expansion deformation compensation algorithm. Generating a multi-parameter coupling vacuum regulation and control model; generating a dynamic vacuum threshold curve of each growth stage based on a vacuum regulation and control model, and outputting a cooperative control signal through real-time deviation calculation; a three-level linkage control strategy is adopted to maintain the vacuum degree stable, a long-short-term memory network is utilized to predict the change trend of the vacuum degree, and a standby vacuum unit is activated in advance; a distributed optical fiber strain sensor is used for detecting leakage sound wave characteristics of a sealing surface, positioning a failure point and driving a magnetic compensation plug to perform dynamic plugging, and meanwhile, leakage information is fed back to a vacuum regulation and control model, so that closed-loop optimization is realized; the vacuum degree control precision and the equipment reliability in the crystal growth process are improved.

The invention discloses a device and a method for measuring the pile body stress of a rotary excavating implanted pile. The device comprises a composite pile inner core, a composite pile outer core, an inner core monitoring unit, an outer core monitoring unit and a bearing platform, the inner core monitoring unit is a first optical fiber string which is formed by connecting a plurality of first high-precision strain sensors in series in a segmented encryption manner, and the first optical fiber string is arranged in a channel formed in the inner core pile body of the composite pile; the outer core detection unit is a second optical fiber string formed by connecting a plurality of second high-precision strain sensors in series in a segmented encryption manner and is mounted in the composite pile outer core, and after mounting is completed, the first optical fiber string and the second optical fiber string are in one-to-one correspondence; the inner core monitoring unit and the outer core monitoring unit are both connected with the fiber bragg grating acquisition instrument and transmit acquired sensor data to a control center for pile body stress measurement; the bearing platform is simultaneously connected with the top of the inner core and the top of the outer core to eliminate stress lag of the outer core of the composite pile; a hole is formed in the center of the bearing platform and used for allowing a pile end settlement testing pipe to penetrate through and providing a pile end monitoring channel.

The invention discloses a power battery multi-field coupling in-situ test platform and method, and relates to the technical field of battery test.The power battery multi-field coupling in-situ test platform comprises a test module and a data acquisition module, and the test module comprises an explosion-proof box inner container and an explosion-proof box inner container partition plate arranged in the explosion-proof box inner container; the explosion-proof box inner container partition plate divides the interior of the explosion-proof box inner container into a test area and a temperature and humidity control area, and the temperature and humidity control area is communicated with the test area through the explosion-proof box inner container air outlet. A battery clamp for fixing a battery, an extrusion needling mechanism for executing an extrusion needling test on the battery, and a drop hammer mechanism for executing a dynamic impact test on the battery are arranged in the test area; the data acquisition module comprises charging and discharging equipment, an electrochemical workstation, a multi-channel data recorder, a camera, an infrared thermal imager, a displacement sensor, a mechanical sensor, a stress sensor, a strain sensor and a thermocouple. And the actual performance of the power battery under the multi-dimensional working condition is comprehensively evaluated.

Flexible and scalable miniature capacitive and inductive strain sensors, as well as methods for fabricating such strain sensors are described herein. According to an example, a flexible capacitive strain sensor can include a stretchable center core and two parallel wires wound about the stretchable center core, forming a double helix structure. Each of the two parallel wires can be embodied as an insulated or an uninsulated copper wire and the stretchable center core can be embodied as a polyester elastic string. The two parallel wires can be wrapped around the stretchable center core in a gapless fashion and with a winding angle of less than 45 degrees with respect to the stretchable center core.

The invention discloses a flexible phased-array antenna sensing regulation and control method and system based on array element mutual coupling, and mainly solves the problem of electrical performance deterioration caused by structural deformation of a phased-array antenna. Comprising the following steps: 1) acquiring strain information of a phased-array antenna in real time by using a fiber grating strain sensor; 2) constructing an electromagnetic calculation model considering mutual coupling, and calculating radiation characteristics of an antenna array through an array superposition principle; 3) building a neural network framework KAN, setting an input layer as a strain, and setting an output layer as an amplitude and phase adjustment amount; 4) constructing a physical information neural network by using the neural network output layer and the electromagnetic calculation model, and training the physical information neural network; 5) inputting the strain into the trained model, calculating the amplitude and the phase adjustment amount of the excitation current of the antenna unit, and sending the amplitude and the phase adjustment amount to a wave control circuit; and 6) adjusting each antenna unit by using the T / R assembly to realize regulation and control. According to the invention, the self-adaptive compensation of the phased-array antenna in service can be realized, and the regulation and control precision is effectively improved.

The invention discloses a multimodal transport cargo transportation state monitoring system based on a standardized intelligent tray group. The system comprises a modular tray group composed of a main control tray and at least one functional tray; the main control tray is integrated with an edge calculator, an RFID reader-writer, a temperature and humidity sensor and a power supply module; the functional tray comprises a strain sensor and an acceleration sensor; the tray groups are rigidly connected through electromagnetic lock catches, and a voltage sensor is arranged to monitor the connection state; the tray group transmits data through a mixed communication channel; LoRa wireless communication is adopted by default, and magnetic attraction wired connection is switched when the packet loss rate is greater than 1%; after being preprocessed by the edge calculator, the data are encrypted by the Beidou system and uploaded to the background server; the background server executes overload and unbalanced load analysis, vibration grade evaluation, environmental risk early warning and lock catch state monitoring; and triggering a user side to give an alarm when an exception is detected. The safety monitoring problem of goods transportation is effectively solved, the transportation safety is improved, and the accident risk is reduced.

The invention relates to the technical field of film strain, in particular to a preparation and installation method of a film strain sensor and a harmonic reducer. The preparation and installation method comprises the steps that the surface of a workpiece to be installed is coated with a polyamide acid solution, then heating is conducted, and polyamide acid is subjected to dehydration cyclization to form a polyimide film attached to the surface of the workpiece to be installed; and then, forming a laser-induced graphene electrode pattern on the polyimide film. The harmonic reducer comprises a wave generator, a rigid gear, a flexible gear and a thin film strain sensor, the flexible gear is connected into the rigid gear in a toothed mode, and the wave generator is arranged in the flexible gear; the film strain sensor comprises a strain film and a graphene electrode, the graphene electrode is formed on the strain film, and the strain film is in direct contact connection with the surface of the flexible gear. Through the film strain sensor adhered to the surface of the workpiece to be installed, in-situ torque detection can be achieved, measurement errors, hysteresis, instability and the like caused by a glue joint layer are avoided, and measurement is more accurate.

The invention discloses a real-time monitoring method for local corrosion of a copper base material based on a discrete FBG sensor, and belongs to the technical field of metal corrosion monitoring. FBG strain sensors and temperature compensation sensors are distributed on the surface of the copper base material, and a temperature compensation mechanism is matched to eliminate measurement errors caused by environment temperature changes, so that the real-time monitoring of local corrosion of the copper base material is realized. Bragg wavelength drift caused by corrosion product accumulation in the corrosion process is collected in real time, and then real-time and continuous tracking of the corrosion dynamic process is obtained. The method realizes early recognition, accurate positioning and quantitative evaluation of local corrosion of the copper base material, has the advantages of non-destructiveness, high sensitivity, long-term stability and the like, and is suitable for corrosion health monitoring of copper structures such as ocean engineering, buildings, pipelines and the like.

The present application relates to the technical field of flexible sensor, and discloses a flexible large-strain sensor, a preparation method and application, aiming to solve the problems of small range, poor adhesion of traditional sensors in large-strain monitoring of solid engine grain and other soft materials, and poor signal linearity and repeatability, complex preparation process and high cost of existing flexible sensors. A polymer film is used to make a flexible insulating substrate; a conductive film is prepared on the flexible insulating substrate to form a composite film layer structure; according to a preset pattern of the conductive film, laser etching and scribing are performed on the conductive film according to a first type of vector track, only penetrating the conductive film, to divide out strain resistance and other resistance, forming an off-axis serpentine structure; according to a preset pattern of the flexible insulating substrate, laser etching and scribing are performed on the composite film layer structure according to a second type of vector track, penetrating the composite film layer structure, to etch out the flexible insulating substrate of the sensor; lead-out wires are welded on the lead-out electrodes and encapsulated to obtain the flexible large-strain sensor.

A fabricated building construction monitoring method belongs to the technical field of buildings, and comprises the following steps: comparing temperature and humidity, wind speed and displacement values with preset thresholds, judging whether to calculate the reading fluctuation amplitude of a strain sensor, generating a sensitivity calibration value when the reading fluctuation amplitude exceeds a reference range, and calculating the temperature and humidity change rate based on the scanning of the coordinates of a key bearing member. And optimizing a transmission interval according to a standard rate threshold value, analyzing a construction stage coding reconstruction pressure threshold value interval, and generating a positioning early warning alarm instruction by integrating a dynamic pressure threshold value, a key area identifier, a connection node stress value, a wind speed value and a displacement value. The method has the advantages that data are read in real time and compared with a preset threshold value, whether high-frequency sampling is started or not is judged, a refined monitoring mechanism is triggered according to environmental conditions, strain data fluctuation can be captured in time in adverse environments such as high temperature and low humidity, and missing detection of abnormal working conditions caused by conventional fixed-frequency monitoring is avoided.