87 results about "Fbg sensor" patented technology

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 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.

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.

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 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 application discloses a double FBG ice accumulation and deicing detection system embedded between an airplane primer and a topcoat and a signal processing method thereof, and belongs to the technical field of airplane state monitoring. The method comprises the following steps: embedding a double FBG sensor structure containing a temperature compensation grating and a strain sensing grating in an airplane wing coating and performing temperature-strain decoupling to obtain a pure strain component; performing intelligent filtering processing on the component to obtain a smooth strain signal; based on the signal and a change rate thereof, in combination with a preset threshold, dynamically identifying ice layer growth, peeling, stability or residual state; and finally, quantitatively evaluating a deicing effect based on sequence similarity analysis. A corresponding system comprises a sensing module, a signal demodulation module and a data processing and decision module. Through in-coating embedded sensing and multi-stage signal processing, the application realizes high-precision and dynamic monitoring of the airplane ice accumulation and deicing process, and effectively solves the problems of temperature interference and noise influence.

This invention relates to the field of fiber optic grating demodulation technology, and provides a peak-finding method for FBG spectra based on VMD fusion denoising. The method includes: performing VMD-WT-SG fusion denoising on spectral data; separating the noise-dominant component and the signal-dominant component through threshold judgment; performing wavelet denoising on the noise-dominant component, followed by reconstruction with the signal-dominant component; performing spectral smoothing of the reconstructed signal through S-G filtering to achieve spectral denoising; segmenting the peak region of the denoised spectral signal; calculating the center wavelength of the multi-peak spectral signal using a perpendicular bisector intersection peak-finding algorithm; obtaining the perpendicular bisectors connecting the peak point and the left and right second-largest points; and quickly calculating the x-coordinate of the intersection point of the two perpendicular bisectors to determine the center wavelength of the fiber optic grating. This achieves fast and accurate demodulation of FBG peaks. This invention improves the denoising capability and peak-finding speed of the demodulation system, and is applicable to the rapid detection of multiple peaks in noisy FBG sensor networks.

The application discloses a kind of based on time series convolution network's multi-parameter coupling ground collapse risk identification and early warning method, comprising: layout FBG sensor array and parallel electric method system, respectively gather pipeline and surrounding soil one-dimensional strain time series data and two-dimensional resistivity spatial distribution data;Two branches of deep learning network are constructed, and one-dimensional time series convolution network and two-dimensional convolution network are used respectively to extract modal specificity features to two types of data;Introduce cross attention feature deep fusion mechanism to extract sensitive feature information in two types of data to ground collapse, establish reliable mapping relationship between monitoring data and collapse risk;Through the risk identification and early warning framework based on attention mechanism, risk level is output and early warning signal is generated, to realize the accurate identification and early warning to ground collapse.The method of the application significantly improves the accuracy of ground collapse risk identification and the timeliness of early warning, effectively overcomes the high false alarm rate, early warning delay and other deficiencies in traditional methods.

The utility model relates to the technical field of shield tunnel health monitoring, and particularly discloses an underwater shield tunnel health monitoring device based on an FBG (Fiber Bragg Grating) sensor, which comprises an intelligent host, the FBG sensor, a grating joint measuring sensor assembly, a fiber grating osmotic pressure sensor assembly and a gas sensor assembly, the grating joint measuring sensor assembly is fixedly connected with the top end of the intelligent host through a connecting column, the fiber grating osmotic pressure sensor assembly is arranged above the grating joint measuring sensor assembly, and the fiber grating osmotic pressure sensor assembly is connected with a protective top through a supporting column; one side of the intelligent host is connected with the gas sensor assembly through a cantilever, and the other side of the intelligent host is provided with a sensor connecting assembly which is connected with the FBG sensor through a connecting line or a wireless network. According to the device, the FBG sensor is combined with other types of sensors for cooperative work, comprehensive and accurate health monitoring of the underwater shield tunnel is achieved, and stable operation of the tunnel is guaranteed.

The invention discloses a space laser load thermal deformation real-time measurement and compensation device which comprises an optical axis offset real-time monitoring module which is composed of a laser collimator array, an FBG sensor network, an autocollimator and a data acquisition preprocessing unit and is used for carrying out coupling monitoring on multiple parameters of three-dimensional space offset. And the optical axis offset compensation module comprises a flexible hinge supporting seat, a PZT driver array, a ball screw pair fine tuning mechanism and a feedback control unit, combines the laser collimator array, the FBG sensor network and the autocollimator, and realizes multi-dimensional and all-directional monitoring of optical axis offset. The laser collimator array directly measures the position and the angle deviation of an optical axis, the FBG sensor network indirectly obtains the deviation information of the optical axis by monitoring the temperature and the strain of the optical element and the supporting structure, the autocollimator accurately measures the angle change of the optical element, and the three sensors complement each other, so that the limitation of monitoring of a single sensor is overcome, and the monitoring precision is improved. The precision and reliability of optical axis offset monitoring are greatly improved.

The invention relates to a motor bearing fault diagnosis method, in particular to a motor bearing fault diagnosis method based on a fiber bragg grating (FBG) sensing technology, which comprises the following steps of: S1, acquiring a motor bearing vibration signal by using an FBG sensor, and then performing temperature compensation and signal conversion on the vibration signal; s2, preprocessing the signal processed in the step S1; s3, performing vibration feature extraction on the preprocessed high-dimensional data to obtain a final feature vector of the bearing fault; and S4, classifying the final feature vectors through machine learning and deep learning algorithms to obtain a final bearing health state classification result. And S5, deploying a fault diagnosis model at the edge device and the cloud, and carrying out intelligent fault early warning. The bearing vibration signal detection precision is improved, the bearing fault classification is optimized, the early fault detection capability is enhanced, and the remote monitoring and intelligent early warning level is improved.

The invention discloses a multi-parameter coupling surface collapse risk identification and early warning method based on a time sequence convolutional network, and the method comprises the steps: arranging an FBG sensor array and a parallel electrical method system, and collecting the one-dimensional strain time sequence data and the two-dimensional resistivity space distribution data of a pipeline and a surrounding soil body; constructing a double-branch deep learning network, and performing modal specific feature extraction on the two types of data by using a one-dimensional time sequence convolutional network and a two-dimensional convolutional network respectively; introducing a cross attention feature deep fusion mechanism to extract feature information sensitive to surface collapse in the two types of data, and establishing a reliable mapping relationship between the monitoring data and the collapse risk; a risk level is output and an early warning signal is generated through a risk identification and early warning framework based on an attention mechanism, so that accurate identification and early warning of surface collapse are realized. According to the method, the accuracy of surface collapse risk identification and the early warning timeliness are remarkably improved, and the defects of high false alarm rate, early warning delay and the like in a traditional method are effectively overcome.

The present application relates to the field of optical fiber sensing technology, and more particularly to a kind of FP-FBG fusion spectrum demodulation method based on discrete spectrum analysis, comprising: driving tunable laser quasi-continuous scanning FP-FBG sensor and obtaining discrete reflection spectrum sequence through photoelectric acquisition circuit, determining the index of FBG peak in the sequence and obtaining FBG center wavelength by using centroid method fitting, selecting target neighborhood with the index as center and replacing the neighborhood sequence value with the intensity mean of spectrum sequence to obtain processed FP spectrum sequence, performing autocorrelation transformation on the processed FP spectrum sequence to obtain autocorrelation sequence, and finding the peak-to-peak distance between main peak and adjacent peak in the autocorrelation sequence, and finally calculating the sensing demodulation result according to the calibration relationship.The present application can effectively remove the shielding of narrow-band FBG to FP spectrum period information, suppress random noise and significantly improve the demodulation accuracy of low-quality spectrum.

The invention discloses a detection method for a space temperature field. An optical fiber uniform distribution path is determined through CAD modeling, a bamboo joint type capillary copper pipe is processed into a holder, an FBG (fiber bragg grating) is in a free telescopic state after penetrating into the copper pipe, and a complete temperature measurement system is formed by matching with a broadband light source, an optical fiber link, a spectrum demodulator and a data processing unit. During working, incident light of the broadband light source is transmitted to the FBG sensor through the optical fiber, Bragg wavelength shift is caused by temperature change, after offset is detected by the demodulator, the Bragg wavelength shift is converted into a temperature value through a temperature sensitivity coefficient, and finally a space temperature field is periodically inverted and reconstructed through software. The temperature sensor has the advantages of electromagnetic interference resistance, corrosion resistance and high temperature measurement precision (+ / -0.1 DEG C to + / -1 DEG C), can optimize technical indexes by adjusting the grating arrangement density, the sampling period and the like, and is suitable for space temperature field detection in severe environments such as high temperature, high pressure and the like, such as engine cylinders, pressure vessels, welding processes and the like.

The application discloses a high-precision FBG sensing device and method based on optical signal frequency shift modulation, relates to the fields of fiber Bragg grating sensing and optical signal frequency shift modulation, and comprises a light source (1), an optical frequency shift modulator (2), a sweep frequency radio frequency source (3), a 90-degree electric bridge (4), a probe light output optical fiber (5), an optical circulator (6), an FBG sensor (7), an FBG sensor array (8), a sensing light receiving optical fiber (9), a high-speed photoelectric detector (10), a data acquisition device (11), a data processing device (12), a light source synchronous control signal line (13) and a radio frequency source synchronous control signal line (14). The high-precision FBG sensing method of the application replaces the vibration applied at the sensor by constructing the frequency shift modulated incident light signal, avoids the problems of complex sensor structure and temperature sensing only, and thus directly improves the strain and temperature sensing precision on the FBG sensor without special design or the FBG sensor already completed.

This utility model discloses a performance testing device for fiber Bragg grating (FBG) sensor design, relating to the field of FBG sensor testing technology. It includes a test bench, with a test controller fixedly mounted on one top side. A test chamber is fixedly connected to the bottom back side of the test controller. A test connection plate is fixedly mounted on the inner wall of the test chamber near the test controller, and a test connection hole is formed inside one side of the test connection plate. Multiple limiting platforms are set at various positions within the test chamber to place the FBG sensors to be tested. The sensors are placed within the limiting platform to ensure stability and prevent them from touching each other. One end of each FBG sensor is inserted into the test connection hole on the test connection plate. The test controller uses a data display and control setting panel to simultaneously test multiple FBG sensors.

The invention relates to the technical field of tunnel deformation monitoring and supporting, and discloses a monitoring, early warning and supporting linkage system for large deformation of a hard rock tunnel, which comprises a data acquisition module, a dynamic early warning module, a self-adaptive supporting module and a linkage control module. The data acquisition module is used for acquiring multiple parameters such as deformation area depth, fracture radius, deformation release energy and rock mass real-time stress through cooperation of an FBG sensor, an AE acoustic emission sensor and a rock mass stress sensor; the dynamic early warning module is used for calculating a dynamic threshold value by combining rock lithology and integrity data based on a Hook-Brown intensity criterion, and generating a graded early warning signal; the self-adaptive supporting module adopts an electro-hydraulic control bracket and force-position double-closed-loop control, so that the supporting force and the stroke are accurately adjusted; and the linkage control module realizes real-time data interaction, feedback optimization and abnormal emergency processing of each module. According to the system, the early warning accuracy and the supporting accuracy are improved, and the linkage delay time is shortened.

An apparatus for monitoring three-dimensional strain in landslide slip zone includes a strain sensor, a data control module, and a magnetic positioning device. The strain sensor includes a protective shell, a slidable rotating cover, a fiber Bragg grating (FBG) sensor, and a telescopic rod. The telescopic rod is configured to push the FBG sensor into contact with a stratum to monitor strain information of soil and rock mass in the slip zone. The data control module is electrically connected to a switch of the slidable rotating cover via data cable and is configured to preprocess data collected by the FBG sensor. The magnetic positioning device is configured to correct displacement detection orientation errors of the FBG sensor caused by landslide deformation.

The application discloses a kind of ground subsidence control methods based on multi-source nature of slag, comprising: obtaining the strain distribution of initial grouting material under ground subsidence area to be measured;Based on the strain distribution, determine the target connection relationship matrix for describing strain anomaly;If the number of target connection relationship matrix is 0, end the step;The target connection relationship matrix is input into the trained graph neural network to determine the corresponding secondary grouting material;The secondary grouting material is used as the initial grouting material again.The application uses FBG sensor to monitor and accurately describe the internal stress distribution of the ground;Further introduce graph neural network to optimize the selection of secondary grouting material, and solve the problem of loss function in the training process and verification difficulty.