139 results about "Fbg sensor" patented technology

The invention provides a decoupling and Kalman filtering temperature strain demodulation method and system for double fiber gratings, and relates to the technical field of optical fiber sensing. The method comprises the following steps: firstly, designing an FBG sensing module for measuring environment temperature change and strain information; the FBG sensing module comprises a two-channel sensing system composed of an FBG1 sensor and an FBG2 sensor, and is used for measuring environment temperature change and strain information at the same time. Then, aiming at optical signals which are acquired by the two FBG sensors and contain physical quantity information, a wavelength demodulation module is used for acquiring the central wavelength drift distance of reflection spectrums of the two FBG sensors; temperature sensitivity coefficients and strain sensitivity coefficients of the two FBG sensors are obtained, and a linear equation set is constructed for independent variation of temperature and strain to perform matrix decoupling so as to distinguish the influence of the temperature and the strain on the change of the central wavelength; and performing optimization estimation on the decoupled temperature and strain by using the prior information of the temperature and the strain and combining a real-time measurement value by adopting a Kalman filtering method.

The invention discloses a dam leakage monitoring system and method based on optical fiber sensing and time-space fusion. The dam leakage monitoring system comprises an optical fiber sensing system, a data processing and analyzing system, a dam leakage data management system and a real-time monitoring platform. According to the invention, the distributed optical fiber realizes continuous strain and temperature monitoring of the whole length of a dam, a leakage area can be roughly positioned, an FBG sensor is deployed at a key position, local tiny deformation is accurately monitored, a cooperative mode is formed by combining wide-area screening of the distributed optical fiber and key diagnosis of the FBG, and the monitoring efficiency is improved; the all-fiber passive design is adopted, the environmental adaptability is high, the anti-interference performance and the long-term stability are high, frequent maintenance is not needed after the fiber is embedded into the structure, and the operation and maintenance cost is reduced; finally, the leakage risk is displayed through a trend curve of a visual data platform, alarm pushing and emergency plan functions are automatically triggered, the closed-loop time of monitoring, decision making and response is shortened, and the real-time performance and decision-making force are improved.

The invention discloses an embedded fiber grating sensor self-calibration strain monitoring system and method.The system comprises a fiber grating sensor, an optical fiber demodulator and a stress buffering type self-calibration mechanism, and the fiber grating sensor is embedded into a propeller blade prefabricated mounting groove through a metal embedded part and a gradient modulus adhesive layer; the plurality of fiber grating sensors are symmetrically distributed in a propeller blade prefabricated mounting groove in pairs, and infrared rays of each pair of symmetrical fiber grating sensors are converged at the circle center of a propeller hub to form a dynamic reference point; the optical fiber demodulator is integrated on the propeller hub and is connected with the plurality of optical fiber grating sensors; the stress buffering type self-calibration mechanism integrates a double-shaft flexible hinge and a shape memory alloy, and interface stress buffering and fiber grating sensor position collaborative self-calibration are achieved. The interface stress is effectively reduced through the gradient modulus glue layer, and the shape memory alloy drives the double-shaft flexible hinge to efficiently correct the offset of the fiber grating sensor in real time and buffer the vibration.

The invention provides a self-adaptive fitting method and system for a substrate deformation measurement system based on a fiber bragg grating (FBG), and the method comprises the steps: reading an output signal of an FBG sensor network, respectively collecting the wavelength data of a grating sensor and the stress data of a stress sensor at the same position as the grating sensor, and constructing a stress-wavelength data set; fBG data points with most sensitive deformation response are automatically identified, and a dynamic sensitive point set is formed and then preprocessed; a set needing to be continuously monitored is analyzed and determined, a specific point is selected to execute an adaptive segmentation fitting algorithm, segmentation points and fitting polynomial coefficients of all subintervals are output, and a final fitting model is constructed; according to the sub-interval of the wavelength value measured by the FBG sensor, calling a sub-interval fitting model, calculating a corresponding stress value, and further obtaining the deformation quantity of the measured object. According to the invention, the contradiction between the monitoring efficiency and precision of the traditional uniform layout in a complex stress scene is solved, and the technical path and the application target have remarkable industry uniqueness.

A thermal measurement system enables high-resolution sub-surface temperature monitoring during additive manufacturing processes through machine learning demodulation of chirped fiber Bragg grating (C-FBG) sensors. An optical sensing subsystem includes a C-FBG sensor that encodes spatial temperature information in wavelength for high-temperature operation. A neural network model transforms complex reflection spectra into spatial temperature profiles with micrometer-scale resolution, overcoming limitations of traditional demodulation methods. A calibration subsystem generates synchronized spectral and thermal imaging data for training the neural network using controlled thermal profiles. The system captures steep thermal gradients and rapid cooling rates during laser powder bed fusion operations. A fiber embedding technique maintains the sensor in a strain-free condition at controlled sub-surface depths. The integration of high-temperature C-FBG sensors with machine learning signal processing achieves significant improvement in spatial resolution compared to traditional fiber optic thermal measurement approaches.

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 invention relates to the technical field of monitoring devices, and discloses an FBG sensor-based filter bag damage real-time monitoring device, which comprises an FBG sensor, an upper sealing cover, a lower sealing cover, an upper support ring fixedly mounted at the bottom end of the upper sealing cover, a lower support ring fixedly mounted at the top end of the lower sealing cover, and an elastic sleeve sleeving the upper support ring and the lower support ring, a cavity is formed among the upper sealing cover, the lower sealing cover and the elastic sleeve, an upper connecting port communicated with the cavity is formed in the top of the upper sealing cover, and a lower connecting port communicated with the cavity is formed in the bottom of the lower sealing cover; according to the invention, the fiber bragg gratings of the plurality of FBG sensors are wound and pasted on the elastic sleeve, and the wavelength change of the fiber bragg gratings is monitored in real time by combining the demodulator, so that the damage and blockage states of the filter bag are accurately identified, and the damage and blockage states of the filter bag are accurately identified by arranging the fiber bragg gratings outside the elastic sleeve and matching with the elastic rubber material of the elastic sleeve. Fine dust in industrial tail gas is prevented from being attached to a monitoring element, the maintenance frequency of the device is reduced, and the service life is prolonged.

The invention discloses a composite hose structure for fuel gas transmission, and relates to the technical field of fuel gas transmission and distribution equipment, the composite hose structure comprises a dual-mode quick sealing assembly, dual-mode monitoring is formed by an FBG sensor, a phase-sensitive optical time domain reflectometer and a carbon tube composite filament, the FBG sensor can capture fine strain of a reinforced fiber layer in real time, and the phase-sensitive optical time domain reflectometer can capture the fine strain of the reinforced fiber layer in real time; the phase-sensitive optical time domain reflectometer detects and captures stress waves generated by crack propagation in a material through broadband sound waves, early recognition of millimeter-level damage in a pipe is achieved, grids woven by carbon tube composite filaments are utilized, continuity of the grids is monitored in real time through alternating-current impedance measurement, and the detection accuracy of the millimeter-level damage in the pipe is improved. When local grid resistance is increased due to breakage of the reinforced fiber layer, a micro-damage area can be accurately positioned, when leakage occurs, the memory alloy spring receives an electric signal monitored by a dual-mode, then axial thrust is generated to push the outer side of the fluororubber sealing ring, the fluororubber sealing ring expands in the radial direction under the thrust action of the memory alloy spring, and the leakage is prevented. And rapid and effective mechanical hard sealing is realized.

The invention relates to a ship buoyant raft structure deformation high-precision reconstruction method based on a multistage domain segmentation PINN, and the method comprises the steps: 1, carrying out the measurement through an FBG sensor, obtaining the real strain at an arrangement measurement point, and obtaining any strain curve on an elastic support buoyant raft structure through an interpolation method; and 2, converting the strain curve obtained in the step 1 into curvature through a strain-curvature equation calculation model. And finally, embedding the curvature-displacement equation into the neural network by constructing a PINN network, ensuring that an output result of the neural network automatically meets a boundary condition by constructing a loss function of a physical equation and a data compensation condition and constructing a mandatory boundary condition, and obtaining displacement of any curve on the plate. In the initial stage, a first-order optimization algorithm is used for iterative training, then a second-order optimizer is used for network adjustment, optimal network parameters are obtained, and a multilevel domain segmentation PINN proxy model using local observation data of a finite strain sensor and a displacement sensor is established.

The invention discloses a microstructure sensor for monitoring stress and temperature of a charging interface of a solid engine, which comprises a flexible packaging layer, an elastic conversion unit and a fiber bragg grating sensing unit, and is characterized in that the elastic conversion unit is a standard arc with a preset length-width ratio; the fiber grating sensing unit comprises a fiber strain sensing unit and a fiber temperature sensing unit; the optical fiber strain sensing unit and the optical fiber temperature sensing unit are two FBG (Fiber Bragg Grating) sensors which are arranged in parallel and are spatially isolated; the optical fiber strain sensing unit is used for indirectly measuring interface stress; the optical fiber temperature sensing unit is used for measuring the environment temperature and compensating the influence of the temperature on strain measurement; when the sensor is stressed, the elastic conversion unit is deformed under the action of the stress, so that the optical fiber strain sensing unit records the strain along the extension direction of the optical fiber; the flexible packaging layer wraps the elastic conversion unit and the fiber grating sensing unit. The micro-structure sensor realizes stress monitoring on the charging interface of the solid engine.

The embodiment of the invention provides an online detection method, device and equipment for a fiber-wound composite gas cylinder and a medium, and belongs to the technical field of fatigue detection. The method comprises the following steps: acquiring a grating sensing signal of a target gas cylinder in an operation process, wherein the grating sensing signal is acquired by an FBG sensor pre-embedded in a fiber layer of the target gas cylinder; extracting a strain detection signal according to the grating sensing signal; determining a predicted damage area of the target gas cylinder according to the strain detection signal; determining a scanning path according to the predicted damage area, and obtaining ultrasonic detection data through ultrasonic phased array scanning based on the scanning path; and based on the predicted damage area, damage information of the target gas cylinder is determined according to the strain detection signal and / or the ultrasonic detection data, and the damage information comprises a damage position and a damage type. The invention aims to realize the damage state detection of the gas cylinder in the operation process and improve the use safety of the gas cylinder.

The invention discloses a wind power plant current collection line fault diagnosis and positioning method based on multi-dimensional physical quantity, belongs to the field of power system fault diagnosis, and aims to solve the problems of weak anti-electromagnetic interference, insufficient multi-fault identification capability and low positioning precision in traditional monitoring of a 35kV current collection line of a wind power plant. A multi-fault diagnosis positioning method based on FBG sensing and adaptive VMD-ELM is provided. The method comprises the following steps: deploying an FBG sensor array at a key node of a current collection line, and synchronously collecting strain, temperature and vibration signals; the permutation entropy is introduced to dynamically adjust the VMD penalty factor to realize adaptive feature extraction, and the ELM is combined to construct a multi-dimensional feature vector classification model, so that a normal state and four faults of short circuit, insulation aging, partial discharge and icing can be identified, the fault position can be accurately positioned, the complex working condition of a wind power plant current collection line can be adapted, and an electric power system can be effectively protected.

The invention discloses a temperature and hydrogen concentration dual-parameter synchronous detection system and method, and the system comprises an ASE broadband light source, the output of the ASE broadband light source is divided into two paths through a coupler, one path enters a first circulator, the other path enters a second circulator, the output of the first circulator enters a first FBG sensor, the output of the second circulator enters a second FBG sensor, and the output of the first FBG sensor enters a second FBG sensor. The two FBG sensors are arranged in the gas chamber, the first FBG sensor and the second FBG sensor are provided with FBG topological optical fiber structures with different working wavelengths and have temperature sensitivity and gas selective response, and reflected signals of the two FBG sensors are coupled to one path through the dual-channel wavelength division multiplexer and are sent to the spectrum analyzer for wavelength demodulation. The temperature sensitivity and the gas selective response are integrated in the same sensing unit by utilizing the wavelength coding characteristic of the fiber bragg grating, so that precise decoupling and real-time output of double parameters are realized, and the detection efficiency and the data consistency are improved.

The invention discloses a material conveying and drying integrated system based on field energy coupling and a control method, and belongs to the technical field of material drying and conveying. Comprising a flexible composite conveying belt, an electromagnetic-microwave composite heating module and an ORC power generation system, and the flexible composite conveying belt is formed by compounding a graphene base material layer and a piezoelectric ceramic surface layer; the memory alloy hinge is located in the graphene base material layer, the FBG sensor optical fiber is embedded into the neutral axis plane of the graphene base material layer, the water content of materials is reduced to be lower than 5% through the synergistic effect of an electromagnetic field and a microwave field and waste heat power generation, the comprehensive energy efficiency ratio of the system is larger than or equal to 2.0, the ORC power generation technology is combined, efficient material drying and energy recovery are achieved, and the energy efficiency of the system is improved. And the device is suitable for green conveying of high-water-content coal slime, copper concentrate and other scenes.

This invention discloses a multi-channel programmable miniaturized high-speed FBG demodulation system and method based on an AWG (Optical Fiber Optic Generator), belonging to the field of fiber optic sensing technology. The AWG-based multi-channel programmable miniaturized high-speed FBG demodulation system includes a high-stability broadband light source module, a low-loss isolation module, a miniaturized programmable fiber optic amplifier, a circulator, a two-stage miniaturized high-speed optical switch, a high-crosstalk AWG module, a photoelectric conversion module, a programmable A / D conversion module, and a core control module. The AWG-based multi-channel programmable miniaturized high-speed FBG demodulation method involves the optical signal entering an FBG sensor array, the FBG sensor reflecting the optical signal, the reflected optical signal entering the AWG module, and the output light undergoing photoelectric conversion to calculate the center wavelength of the FBG sensor. This invention, based on an AWG, improves demodulation accuracy while ensuring the demodulation range, achieving continuous wavelength demodulation within the AWG wavelength range.

The present invention relates to the field of optical fiber sensing technology, and more specifically to a MOMES and FBG fusion sensing system based on an adjustable laser array. A multi-wavelength tunable laser array light source is used to generate fast broadband frequency-sweeping laser light, which is split into M outputs via a multi-path planar optical waveguide splitter coupler. Each output end is connected to N FBG sensor arrays and one MOMES sensor, and the reflected light of the sensing signal is received by the corresponding photodetector. After data processing by a photoelectric converter, a logarithmic amplifier, an analog-to-digital converter, and an FPGA-compatible algorithm platform, the peaks and troughs of the reflected spectrum data at each wavelength point are simultaneously found. The peak data is used to demodulate the FBG sensor array, and the trough data is used to demodulate the MOMES sensor. The optical path structure and algorithm design of the system achieve synchronous demodulation of the FBG and MOMES sensors, significantly improving the system's compatibility and computational efficiency.

This invention relates to a high-precision reconstruction method for the deformation of ship floating raft structures based on multi-level domain segmented PINN. The first step involves measuring the actual strain at the designated measuring points using FBG sensors, and then using interpolation to obtain an arbitrary strain curve on the elastically supported floating raft structure. The second step transforms the strain curve obtained in step one into curvature using a strain-curvature equation calculation model. Finally, a PINN network is constructed, embedding the curvature-displacement equation into the neural network. By constructing physical equations, a loss function for data compensation conditions, and mandatory boundary conditions, the output of the neural network is guaranteed to automatically satisfy the boundary conditions, thus obtaining the displacement of any curve on the raft. Initially, a first-order optimization algorithm is used for iterative training, followed by a second-order optimizer to adjust the network parameters and obtain the optimal network parameters. This establishes a multi-level domain segmented PINN surrogate model using local observation data from finite strain and displacement sensors.

The invention discloses an FBG sensor suitable for slope monitoring in a plateau environment, the FBG sensor comprises a flexible substrate and a plurality of FBGs, the FBGs are all arranged to be rod structures, each FBG comprises an optical fiber core, an optical fiber cladding and an outer cladding, and a grating array is arranged in the optical fiber core; the surface of the flexible substrate is symmetrically provided with two rectangular grooves along the axis, the plurality of fiber Bragg gratings are uniformly arranged in the two grooves, the flexible substrate is divided into a plurality of micro-segments, each micro-segment is set as a detection unit, each detection unit is connected with the data processing module, and the data processing module is connected with the data processing module. The detection unit comprises two vertically corresponding fiber bragg gratings installed in the two grooves, compared with the prior art, various influences of the plateau environment can be overcome, and the change condition of the slope can be accurately monitored; the temperature change is sensed by coating a special coating, so that the temperature coverage range is wide; the device is small in size, light in weight and convenient to install, and has the characteristics of long-term stability, wavelength multiplexing and the like.

The application discloses an integrated circuit packaging material stress test system and method, and belongs to the field of integrated circuits. The system comprises a multi-axis stress applying device, an environment control unit, a deformation data acquisition unit and a data analysis module. By applying multi-axis composite stress and using high-precision DIC or FBG sensors to acquire strain data, real-time analysis and prediction are carried out in combination with CNN, LSTM and reinforcement learning algorithms, and the loading path is dynamically optimized. The application realizes complex working condition simulation, accurate capture of micro-deformation and intelligent optimization of the test process, and significantly improves the test precision and efficiency.

The utility model relates to the technical field of fiber bragg grating demodulation, in particular to a multichannel high-speed fiber bragg grating demodulation device, which comprises an optical path module and an electric signal module, the optical path module comprises a tunable laser unit, a PLC (programmable logic controller) unit and a plurality of FBG (fiber bragg grating) sensors, the PLC unit comprises an optical splitter and a plurality of couplers, the electric signal module comprises a main control unit, a photoelectric conversion unit, a DC / DC unit, a 485 communication unit and an Ethernet communication unit, optical signals emitted by the tunable laser unit pass through an optical splitter and a multi-path coupler and then enter an FBG sensor, light is reflected by a grating and then is connected to a photodiode through the coupler, and the photoelectric conversion unit is connected to the Ethernet communication unit. And after photoelectric conversion, AD conversion and peak searching algorithm processing, the optical wavelength is demodulated. According to the utility model, a chip-level data acquisition design is adopted, the scanning speed of the demodulator is improved, fusion with a field system is facilitated through the 485 communication unit, and a heterogeneous system of the master control unit and the FPGA unit is adopted, so that the edge computing capability is enhanced.

System for detecting injuries suffered by passengers in a vehicle after an accident or a strenuous situation, the system comprising: one or more FBG sensors (1) arranged on a safety belt (2; 10) of a vehicle seat (6); an FBG interrogator (7) configured to obtain strain measurements from the one or more FBG sensors (1); and a detection unit (8) configured to compute a load distribution map (9) using the strain measurements.

The application relates to a ZYNQ-based fiber grating demodulation device and a gigabit Ethernet data transmission method thereof, and relates to the fields of optical fiber communication and sensing. The device takes a ZYNQ control module as a core, and is matched with a laser driver board, a laser, a beam splitter, an FBG sensor, a filter, a balanced photoelectric detector, a signal amplification module and an AD conversion module. The process is as follows: a terminal writes a filter characteristic curve into a PL end BRAM; the ZYNQ drives a laser, and the generated optical signal is reflected to the balanced photoelectric detector after passing through the beam splitter and the FBG sensor, is input into the PL end after photoelectric conversion, amplification and AD conversion; the PL end calculates and looks up a table to obtain a center wavelength; data is stored in a DDR3 through AXI and FIFO, and is uploaded to the terminal through a network port. Compared with a traditional MCU scheme, the application has the characteristics of fast operation speed, high integration degree and low transmission delay, and can be widely used in the fields of optical fiber communication and sensing measurement.

The application discloses a kind of manufacturing methods of structural conformal FBG sensing array, it is related to 3D printing and fiber sensing technical field, the method includes: FBG material is loaded into printing needle tube and is fixed on the mechanical arm of five-axis printer;Viscous film is laid on the motion platform of five-axis printer, start five-axis printer and print FBG material on platform surface according to pre-designed path, and control the rotation parameter of motion platform in the printing process, to increase the bending angle of FBG material when printing grating area;The translation parameter of mechanical arm is controlled simultaneously, so that the distance between needle and viscous film in vertical direction is greater than minimum preset distance;The method is based on determining the minimum preset distance between needle and platform when printing, the minimum bending radius of array bending part on viscous film, realizes the plane or curved surface manufacturing of FBG using five-axis printer, with the advantages of low cost, high efficiency, high manufacturing precision, suitable for large-scale sensing array rapid manufacturing.

The invention provides a substrate deformation measurement system based on a fiber bragg grating (FBG) and a self-adaptive layout method thereof. The substrate deformation measurement system comprises an FBG sensor network, a data acquisition module, a signal preprocessing and data analysis processing module and a visual interface, the FBG sensor network comprises a measured substrate and a fiber grating string; the data acquisition module comprises a tunable broadband light source, an optical isolator, an optical circulator, a signal transmission optical fiber, a spectrum analyzer and a corresponding demodulation algorithm; the signal preprocessing and data analysis processing module comprises hardware equipment and computer software; and the visual interface uses Labview to write a front-end interface, and is used for performing three-dimensional real-time display on a substrate shape reconstruction result and realizing an alarm function for special situations. According to the invention, through fusion of real-time data and a prior model, focusing monitoring and resource optimization configuration of a key area are realized, and the problems of high calculation complexity, low data processing efficiency and the like in a traditional distributed fiber grating morphology sensing technology are solved.

The present invention discloses a tactile sensor device, comprising a sliding bracket driven by a robotic arm, a sensing link, a spring, an FBG tactile sensor, and an optical path system. The FBG tactile sensor comprises at least three bionic fingers, each containing an FBG sensor encapsulated within a flexible structure; a sliding bracket having an internal groove for accommodating the sensing link and the spring; the sensor link comprising a thin rod and a thick rod, with a slider positioned laterally above the thick rod, the lower portion of which extends out of the internal groove of the sliding bracket; a slideway mateable with the link slider positioned laterally within the internal groove of the sliding bracket, and a hole formed above the groove for allowing the thin rod to pass through. The present invention also provides a method for analyzing the hardness and flatness of an object using the aforementioned tactile sensor device.

Provided in the present invention are an FBG sensor and an FBG-based vascular thrombus detection simulation system and method. The FBG sensor comprises a single-core fiber optic-form FBG multi-point grating array, the multi-point grating array comprising a plurality of grating areas and a plurality of interval areas, and the grating areas being arranged between any two interval areas. The design of the single-core multi-grating array FBG sensor solves the problem that a universal FBG sensor is not adaptable to thrombus detection. Vascular deformation caused by thrombi acts on the FBG sensor and thus stretches or compresses gratings to generate strain information which is used for constructing the vascular thrombus detection simulation system and, on the basis of two experimental results corresponding to the relative position relationship between the grating areas of the FBG sensor and the thrombi, the vascular thrombus detection method is provided.

The invention discloses an intelligent control method and system for an ophthalmic surgical robot, a prediction model and a cooperative control method, and belongs to the technical field of medical robots. The system comprises a 3D display system, an OCT information system, a micro-touch system, an information comprehensive processing system, a control system, a mechanical arm and special inner boundary membrane tweezers. The core of the method is that an augmented reality surgical navigation model is constructed through preoperative and intraoperative OCT data fusion; the micro-operation force is monitored in real time through the novel inner boundary membrane tweezers integrated with the FBG sensor; the visual sense information and the force sense information are fused through an information comprehensive processing system, and a personalized control strategy is generated based on a pre-trained deep learning decision model; and finally, the control system adopts a self-adaptive impedance control algorithm to drive the mechanical arm to execute accurate and smooth force-position closed-loop operation. The problems that in the ophthalmologic operation, the visual depth is lost, the tactile feedback is deficient, and the operation precision depends on the experience of doctors are solved, and the safety, the precision and the standardization level of the retina inbound membrane stripping operation can be remarkably improved.

This invention provides a multi-contact force sensing device and method for a continuum robot based on fiber optic gratings (FBGs). The device includes multiple sequentially connected unit bodies, each comprising a rigid segment and a flexible segment. A positioning block is mounted on the rigid segment of each unit body. A central cavity is formed in the center of the positioning block, and driving cavities are formed around the periphery of the positioning block. Multiple driving cavities are spaced apart circumferentially along the positioning block. A multi-core optical fiber with multiple FBG sensors is disposed within the central cavity, and a single-core optical fiber etched with multiple FBG sensors is disposed within each driving cavity. By reconstructing the tension along the entire driving filament using FBG sensors, explicit modeling of the friction between the driving filament and the driving channel is eliminated, overcoming the errors and excessive computational resource consumption caused by modeling. This method can simultaneously estimate the magnitude of multiple contact points and contact forces on the continuum robot body, providing significant assurance for the safe intervention of surgical robots.

The application provides a large-aspect-ratio wing bending and torsion deformation dynamic monitoring method which can be used in actual engineering. The method comprises the following steps: installing fiber Bragg grating (FBG) sensors and torsion strain gauges on a large-aspect-ratio wing girder; measuring bending and torsion strains by using the FBG sensors and the torsion strain gauges; establishing a strain-displacement relationship model, and determining the geometric parameters required by the strain-displacement relationship model through experiments; and calculating the deformation of the large-aspect-ratio wing in actual flight by using the strain-displacement relationship model and the real-time measured strain data. The application can avoid the influence of external environmental factors on the measurement. In addition, by combining the use of the torsion strain gauges, the flexibility of arranging the measuring points is improved, so that the measurement system can adapt to beams with different geometrical shapes, and is particularly suitable for unmanned aerial vehicles with large-aspect-ratio wings in actual engineering, and can realize the measurement of the dynamic response of the large-aspect-ratio wing in actual flight state in a complex flight environment.

The invention discloses a ground surface settlement control method based on multi-source muck properties. The method comprises the steps that the strain distribution condition of a ground surface settlement to-be-detected area under an initial grouting material is obtained; based on the strain distribution condition, determining a target connection relation matrix used for describing strain abnormity; if the number of the target connection relation matrixes is 0, ending the step; inputting the target connection relation matrix into a trained graph neural network, and determining a corresponding secondary grouting material; and taking the secondary grouting material as the initial grouting material again. According to the invention, the FBG sensor is used to monitor and accurately describe the stress distribution in the earth surface in real time; a graph neural network is further introduced to carry out optimization selection on the secondary grouting material, and the problems that loss functions are not matched and verification is difficult in the training process are solved.