29 results about "Fiber strain" patented technology

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 application discloses a kind of test device and method for testing the bonding performance of inorganic fiber-concrete, the device includes anchoring section, the skeleton for maintaining loading process fiber axial tension, mold, baffle and displacement sensor;The middle part of the baffle is provided with a hole, a plurality of inorganic fibers are inserted in the hole, the concrete is poured in the space surrounded by the mold and the baffle, the two ends of the inorganic fibers are embedded in the concrete, and the mold is removed after the concrete hardens to make the baffle complete debonding;The displacement sensor is used to monitor the strain condition of inorganic fiber.The method is implemented based on the above test device.The application has the advantages of simple structure, easy operation, high testing precision, etc.

The invention belongs to the technical field of communication optical cables, and particularly relates to a high-fiber-density compact air-blowing micro cable. The high-fiber-density compact air-blowing micro-cable comprises a light-cured non-metal reinforcing piece, at least one optical unit twisting layer and an outer sheath layer which are sequentially arranged from inside to outside, the optical unit twisting layer is obtained by twisting optical units on the outer side of the non-metal reinforcing piece; the optical unit is composed of a small-diameter optical fiber layer, a fiber paste layer and a loose tube which are sequentially arranged from inside to outside, and plastic coating adopts a secondary pre-coating process to realize plumpness of the fiber paste; the cable has excellent mechanical performance, and can meet the laying requirements in a complex environment, the tensile force is 1000N in a short period of 1min, and the strain of the optical fiber is 1t; and under the conditions of stretching, flattening and impacting, the residual additional attenuation of the optical fiber is less than or equal to 0.1 dB at 1550nm. The maximum attenuation change of the micro cable under high and low temperature circulation is 0.033 dB / km, the air blowing distance can reach 1.5 km or above, and the micro cable shows good laying performance.

The invention relates to the technical field of intelligent weaving control, and discloses a four-way stretch gray fabric weaving control method and system based on intelligent control. The method comprises the following steps: acquiring elastic deformation data through an optical fiber strain sensor, and identifying an elastic fiber fatigue state to obtain characteristic parameters; performing correlation analysis and coupling calculation on the opening angle, the weft insertion speed and the beating-up force according to the characteristic parameters to obtain a multi-mechanism coordination parameter table; inputting the parameter table into a fuzzy controller for intelligent reasoning, and matching a control rule to obtain a mechanism adjusting instruction; warp and weft tension is synchronously adjusted according to the instruction, and tension balance control data is obtained through correlation optimization; inputting the control data into a weaving execution system, and feeding back and correcting according to a fabric elasticity quality detection result to obtain four-side elastic gray fabric weaving output. The control precision of four-way stretch gray fabric weaving and the product quality consistency are improved.

The application discloses a CT-fiber combined testing system and testing method for CO2 imbibition process in fractured caprock, and belongs to the technical field of caprock sealing property evaluation for CO2 geological storage. The method uses a fractured core as a sample, and a distributed fiber ring and a spiral are arranged on the outer surface of the core and are subjected to vacuum water saturation treatment. The method synchronously carries out a high-temperature and high-pressure seepage test and CT scanning under a plurality of confining pressures, establishes a calibration relationship among the confining pressure, the fiber strain and the crack opening degree and the permeability, calculates the permeability change by combining the flow and the pressure difference, and quantitatively evaluates the leakage process by monitoring and characterizing CO2 migration and crack deformation through the CT and the fiber. The method obtains multi-source coupling information such as the confining pressure, the crack opening degree, the strain response, the permeability evolution and CO2 breakthrough and leakage behavior under the same core and unified loading path, has high time and space resolution, complete process characterization, and can directly support fine evaluation of the sealing property and leakage risk of the CO2 storage caprock, and provides an experimental basis for caprock integrity evaluation and field fiber monitoring calibration for CO2 storage.

The application discloses a kind of surrounding rock displacement monitoring device and method based on fiber grating array, including micro fine diameter oil cylinder, micro coarse diameter oil cylinder, temperature self-compensation sensing element, fiber grating array, steel wire rope buckle, plastic sleeve, installation box, bearing, bearing seat, steel wire rope.The application is converted into fiber strain by the structure-fluid transmission of spring, oil cylinder, and the intelligent perception of the state of multiple points in surrounding rock is realized by temperature compensation of symmetrical structure.The application is suitable for surrounding rock displacement monitoring, and can also be used for roadway surrounding rock stability analysis, with simple structure and easy installation, to help the safe and efficient production of coal mine.

This invention provides a method for diagnosing fracturing fracture parameters by combining adjacent well fiber optic strain and construction pressure. The method includes: deploying distributed fiber optic sensors in the adjacent wellbore to monitor strain signals; deploying pressure sensors in the fracturing well to monitor pressure changes; comparing and processing fiber optic strain data and pressure data on the same time axis to identify the correlation between pressure fluctuations and fiber optic strain, and identifying the strain signal at the fracture front; establishing a strain-fracture geometry parameter inversion model by combining fiber optic strain and pressure fluctuations to obtain fracture geometry parameters at different times; verifying the accuracy of the strain-fracture geometry parameter inversion model; substituting the fracture parameters obtained from the strain-fracture geometry parameter inversion model into the Barree conductivity model to obtain the fracture conductivity; and obtaining the three-dimensional geometric morphology and dynamic change process of the fracture based on the obtained fracture geometry parameters and fracture conductivity. This invention can obtain more accurate fracture parameters.

The application discloses a large-angle down-running long-distance curved belt conveyor capable of preventing jumping, and relates to the technical field of unmanned intelligent conveyors, comprising an unmanned yard intelligent control system, a jumping-preventing control module, an intelligent tensioning system and a composite braking system.The application adopts a distributed fiber strain sensor array with golden section interval distribution through the unmanned yard intelligent control system to accurately monitor dynamic tension distribution of the concave arc section, combines 10Hz high-frequency three-dimensional laser radar to scan material accumulation forms, constructs a real-time three-dimensional point cloud model, and integrates a variable parameter PID starting algorithm in the jumping-preventing control module to stabilize acceleration at 0.05-0.1 m / s 2 interval, cooperates with a variable-curvature bearing structure and a hydraulic adjusting roller group, and can reduce the risk of material centrifugal deviation during large-angle turning, thereby not only solving the jumping problem of long-distance curved conveying, but also improving equipment stability and transportation efficiency, and being suitable for high-strength continuous operation scenes of unmanned yards.

The invention provides a space manipulator actuator load optical fiber reconstruction method and system based on self-adaptive non-negative Bayesian regularization and application, and relates to the technical field of load reconstruction. The method comprises the following steps: arranging a plurality of fiber grating sensors on an end effector of the space manipulator; constructing a dynamic load model representing a reverse mapping relation between the external load of the end effector and the optical fiber strain response; constructing a load history reconstruction posterior probability density function of the end effector of the space manipulator, and performing variation approximate calculation on the load history reconstruction posterior probability density function; and carrying out iterative solution on the posterior probability density function to obtain dynamic load history data of the space manipulator end effector. According to the method, data fitting residual and parameter posteriori distribution are monitored in real time, regularization intensity is adjusted in a self-adaptive mode, the algorithm can accurately track the dynamic characteristics of the time-varying load, the defect that a fixed parameter method is insufficient in adaptability under complex working conditions is overcome, and high-precision dynamic load process data reconstruction is achieved.

The invention discloses a bridge deformation abnormity early warning device and an early warning method thereof, the device comprises a data acquisition and analysis device, an acquisition port of the data acquisition and analysis device is connected with a laser tilt angle sensor, an acceleration sensor and an optical fiber strain gauge, and an output port of the data acquisition and analysis device is connected with an audible and visual alarm; the early warning method comprises the following steps: determining a to-be-detected bridge, and obtaining original data of a sensor; performing feature extraction on the third environment parameter signal, and selecting an optimal model; performing abnormal point processing by using an LSTM time sequence prediction model; eliminating the temperature and vehicle load effect based on an auto-encoder in combination with an artificial neural network to obtain a corrected modal frequency after the temperature and vehicle load effect is eliminated; and formulating a scoring detailed rule, and scoring the dynamic characteristics of the bridge. According to the invention, the LSTM neural network is introduced to realize bridge deformation trend prediction, the auto-encoder is used to eliminate temperature and vehicle response, and the early warning perspectiveness is improved.

The invention relates to the technical field of additive manufacturing, and particularly discloses a continuous fiber additive manufacturing process parameter optimization control system, which is characterized in that a curvature and a curvature change rate are extracted along a printing path, and a continuous micro-dispatchable function of a printing speed, a fiber tension and an extrusion multiplying power about an arc length is constructed; taking fiber strain energy abrupt change and resin stacking volume deviation minimization in the transition area as targets, and obtaining an optimal speed, tension and extrusion rate curve through offline nesting optimization; discretizing the curve into increment instructions according to a speed change section, and embedding the increment instructions into printing codes; actual tension and stacking width are collected in real time during execution, and a step length factor is dynamically adjusted based on the main deviation for compensation and correction; according to the method, continuous and smooth parameter scheduling and closed-loop compensation in the arc length direction are achieved, and the defects of fiber wrinkles and resin knots in the curve transition area are effectively overcome.

The utility model discloses a wind power gear box planetary gear fiber strain detection device comprising a detection device body, one end of the side surface of the detection device body is fixedly connected with an installation block which is convenient for installing the detection device body; a mounting mechanism for quickly mounting and dismounting the detection device body is arranged at one end of the side surface of the mounting block; according to the utility model, the detection device body can be quickly mounted and dismounted through the mounting block and the mounting mechanism, the tedious dismounting and mounting process can be avoided, and the operation difficulty and time cost of maintenance personnel can be reduced.

The invention relates to the technical field of pile foundation engineering quality detection, in particular to a pile foundation concrete quality detection method based on multi-source data. According to the invention, optical fiber data, stress wave reflection data, sound wave signals and environment data are synchronously acquired through a periodically calibrated multi-source sensor; secondly, preprocessing the data, including optical fiber strain-temperature decoupling, stress wave energy entropy extraction and sound wave compactness calculation; afterwards, inputting the preprocessed data into a periodically updated improved Bayesian network fusion model, calculating the comprehensive probability of each defect, and marking and adjusting positions which do not meet a preset probability threshold value; and finally, a detection characterization value is determined based on the number of times which meet the preset conditions and are adjusted within the preset time and the total number of times of adjustment, the quality detection state of the pile foundation concrete is judged according to the detection characterization value, and the calibration period of the optimization sensor and the preset probability of the model are dynamically fed back. The quality detection precision of the pile foundation concrete is improved.

The application discloses an ultra-high precision zero drift optimization method based on fiber loop tail fiber strain control, and belongs to the field of fiber optic gyroscope and optical measurement technology. Its characteristics are: under a certain temperature change rate, using polarization maintaining OFDR combined with multi-parameter decoupling technology to test the temperature and thermal strain in the loop; performing loop zero drift prediction to obtain the zero drift value of each temperature point; setting the length of strain control, adjusting the tail fiber value in the test data, calculating the strain control value and direction of each temperature point; under the same temperature condition, using the electric control tension platform to apply the corresponding temperature point strain in the corresponding direction to accurately correct the zero drift of each temperature point. The method realizes ultra-high precision full-temperature zero drift optimization through active tail fiber strain control, and can theoretically achieve quantitative ultra-high precision (10 ‑5 order of magnitude) zero drift optimization, and can be used for development of an ultra-high precision gyro system, online zero drift compensation, and plays an important role in performance improvement of the gyro system.

The invention discloses a preparation method of a self-healing hydroxyethyl cellulose-based hollow-structure hydrogel fiber strain sensing material. The hydrogel precursor solution is injected into a mold composed of transparent polytetrafluoroethylene tubes with different diameters through a disposable syringe, the mold is put into an ultraviolet curing box to be irradiated for a certain time, the interior of the hollow fiber is coated with a certain amount of liquid metal mixture, and the final hollow-structure conductive hydrogel fiber is obtained. In a cross-linked network in the prepared hydrogel fiber, a phenylboronic acid group in the ionic liquid and a cis-diol bond on the surface of hydroxyethyl cellulose form a dynamic borate bond, and a dynamic chemical cross-linking site is provided, so that the stability of the hydrogel network is further improved. The resistance-type strain sensor assembled by using the hydrogel fiber has linear sensitivity and wide strain detection range, and can realize real-time monitoring of motion states of different parts of a human body.

The invention discloses a preparation method of a low-modulus self-healing cellulose nanofiber based hydrogel fiber strain sensing material. A hydrogel precursor solution is injected into a transparent silica gel pipeline through a wet spinning strategy, a micro sample injection pump continuously extrudes the precursor solution according to a certain propelling speed, and solution polymerization is initiated by ultraviolet light to obtain the low-modulus ionic conductive hydrogel fiber. A main network of the hydrogel fiber is composed of a three-dimensional network framework formed by polyacrylamide through covalent crosslinking, TEMPO oxidized cellulose nanofibers and polyacrylamide form an interpenetrating network, the mechanical performance of the hydrogel fiber is improved, and the self-healing effect of an internal network of hydrogel is improved through the coupling effect of dynamic hydrogen bonds and a covalent network. The resistance-type strain sensor assembled by the ionic conductive self-healing hydrogel fiber has ultralow modulus and wide strain detection range, and can realize real-time monitoring of motion states of different parts of a human body.

The invention relates to a hydraulic fracturing temporary plugging effect evaluation method and device. Comprising the following steps: acquiring optical fiber strain rates of a plurality of depth measuring points of a target fracturing section at a plurality of time measuring points in a fracturing and temporary plugging process; for each time measuring point, calculating the accumulated positive strain rate of the optical fiber after noise reduction of the time measuring point according to the optical fiber strain rates of a plurality of time measuring points before the time measuring point; for each depth measuring point, extracting the noise-reduced optical fiber accumulated positive strain rate of the corresponding time measuring point according to the temporary plugging effective waiting duration corresponding to the temporary plugging measure, and forming a noise-reduced optical fiber accumulated positive strain rate curve corresponding to the temporary plugging measure of the depth measuring point; performing similarity measurement on the noise-reduced optical fiber accumulated positive strain rate curve of each depth measuring point to obtain a similarity distance matrix; and evaluating the temporary plugging effect of each depth measuring point according to the similarity distance matrix. According to the method, fracturing field personnel can be assisted in dynamically adjusting construction parameters, the temporary plugging agent putting opportunity and dosage are optimized, and the uniformity and overall efficiency of fracturing transformation are improved.

A thin-walled cylinder pressure sensor based on distributed optical fiber strain measurement is characterized in that one end of a sensing sleeve is a closed end, the middle of the sensing sleeve is a thin-walled sensing section, the other end of the sensing sleeve is a connecting end, the connecting end of the sensing sleeve is connected with a connector, and an axial through hole is machined in the center of the connector and communicated with a cavity of the sensing sleeve; and a single-mode optical fiber is wound on the thin-wall sensing section of the sensing sleeve. The optical fiber and the thin-walled cylinder structure are combined, global continuous strain monitoring is carried out on the outer wall of the sensing sleeve, strain distribution complete information of the whole cylinder wall is obtained, the limitation of traditional sensor point type measurement is broken through, the situation that key pressure change areas are omitted due to limited measurement points is avoided, pressure field distribution data can be synchronously obtained, and the measurement accuracy is improved. And a brand new technical path is provided for accurate analysis and fault pre-judgment in a complex pressure environment.

The invention discloses a side slope surface horizontal displacement monitoring method based on optical fiber strain, which can be widely applied to the technical field of geotechnical engineering safety monitoring. According to the invention, after the plurality of anchoring points are arranged in the horizontal direction of the slope to be monitored to form the reference measuring line, the second fixing parts are connected with the anchoring points, so that the plurality of optical fiber fixing rod assemblies are fixed on the reference measuring line, and the adjacent optical fiber fixing rod assemblies on the reference measuring line are connected through the universal connecting parts. A plurality of fixing rods and a plurality of optical fiber groups are arranged in each optical fiber fixing rod assembly, optical fibers of the optical fiber groups are arranged on the fixing rods, and the optical fibers between the adjacent optical fiber groups are connected through an elliptical rotating shaft, so that the sensitivity and the precision of the optical fibers in the micro deformation monitoring process can be effectively improved; then the real-time displacement amount and the real-time displacement direction in the slope to be monitored are analyzed through the optical fiber deformation reference data and the real-time optical fiber deformation amount, the slope displacement direction data can be effectively obtained, and the accuracy of the displacement data is improved.

The invention relates to the technical field of material performance, and provides an SMAF-ECC fiber stress calculation method based on a multi-seam cracking effect, and the method comprises the steps: obtaining material parameters of a to-be-tested material, the material parameters being parameters describing mechanical behaviors of the to-be-tested material; according to the material parameters and a preset multi-crack width, performing strain calculation on the shape memory alloy fiber in the to-be-tested material to obtain the strain of the shape memory alloy fiber; wherein the preset multi-crack width represents the sum of the opening widths of all cracks in the to-be-tested material intersected with the shape memory alloy fiber; and calculating the shape memory alloy fiber stress according to the material parameters and the shape memory alloy fiber strain based on the constitutive relationship of the shape memory alloy fiber. According to the method, the fiber strain calculation model considering the accumulated width of the multiple cracks is established, so that high-precision prediction from crack information to fiber stress is realized.

This invention discloses a method and apparatus for crack morphology inversion combining full-time step and physical model, comprising: inputting crack height and crack offset in the crack height direction into a physical model; first, processing the crack height through a crack propagation sub-model to output crack geometric parameters for the full-time step; then, processing the crack geometric parameters and crack offset in the crack height direction through a fiber strain response sub-model to output axial strain rate at simulated measurement points for the full-time step; adjusting the axial strain rate at simulated measurement points based on positive and negative strain rate scaling factors; calculating the loss value between the adjusted simulated axial strain rate and the measured axial strain rate; if the loss value is greater than a preset loss threshold, adjusting the corresponding optimization control parameters until the loss value is less than or equal to the preset loss threshold, or a preset iteration stop condition is reached; and outputting the target crack geometric parameters for the full-time step based on the finally adjusted optimization control parameters. This invention can improve the accuracy and efficiency of crack morphology inversion.

The present application relates to the technical field of wind power equipment health monitoring and fault prediction, and discloses a wind power blade recession trend monitoring and prediction method based on digital twinning and optical fiber strain driving, which comprises the following steps: determining a damage monitoring key area based on global point cloud data, and constructing a mechanical twinning model of the wind power blade in combination with sensor measured data; correcting the boundary conditions of the mechanical twinning model through strain data, and establishing a dynamic correlation mechanism between the strain data and the wind power blade; constructing a spatial continuous deformation mode based on the strain data to implement initial parameterization setting of the mechanical twinning model, and establishing a model inversion iteration mechanism to locate and evaluate the damage degree of the wind power blade; constructing a recession trend comprehensive index to determine a trend prediction quantitative basis of the wind power blade; and constructing a prediction model based on the trend prediction quantitative basis and strain time series data to calculate the recession trend of the wind power blade at a future time. The present application can accurately locate the damage position and evaluate the damage degree.

This invention discloses a method for identifying fatigue cracks in wind turbine blades based on distributed optical fiber strain response, belonging to the field of wind power equipment condition monitoring technology. The method includes the following steps: collecting continuous optical strain response records formed during the wind turbine blade's operation; organizing these records according to a unified time scale to form a strain change trajectory; calculating the difference in amplitude between adjacent strains within the strain change trajectory and extracting continuous, slowly fluctuating segments to form a list of low-frequency oscillation segments. This invention identifies low-frequency oscillation segments in the strain change trajectory and constructs an oscillation unfolding trajectory, enabling the time unfolding of local strain changes in the low-frequency oscillation background, thereby revealing the minute strain change characteristics of the crack initiation stage; further, by extracting suspected crack fragments and reconstructing crack release trajectories, a crack strengthening trajectory is formed, allowing crack release changes to be continuously presented in a continuous time series, improving the early identification capability and the ability to identify the change process of fatigue cracks in wind turbine blades.

The application discloses a fracture inversion optimization method based on fiber strain monitoring after fracturing pump stopping, relates to the oil and gas field exploitation technical field, and comprises the following steps: determining the filtration coefficient and the fracture complete closure time based on the fiber strain data after fracturing pump stopping; determining the formation filtration characteristics according to the filtration coefficient; adjusting the fracturing fluid system and the construction discharge capacity according to the determined formation filtration characteristics; and adjusting the pump injection time according to the determined fracture complete closure time.

This invention provides an ablation-resistant, low-strain composite drag cable, relating to the field of cable technology. It includes an optoelectronic composite cable core and a polyimide wrapping layer. The optoelectronic composite cable core comprises fiber buffer reinforcement optical fibers and high-temperature conductors, with multiple sets of high-temperature conductors. This invention uses the optoelectronic composite cable core and the polyimide wrapping layer to form the cable core. A polyimide fiber reinforcement layer covers the outside of the cable core. The polyimide fiber reinforcement layer is wrapped using parallel twisting and unidirectional spiral twisting. The parallel twisting process forms fiber bundles with two twisting directions, further improving the consistency of fiber output. The use of spiral twisting with different twisting directions after parallel twisting, and unidirectional braiding, ensures fiber output efficiency while achieving fiber self-tightening and reducing the size of the optoelectronic composite conductor. This reduces material usage while ensuring that fiber strain can be effectively controlled within 1%.

This invention provides a fault diagnosis method for ammonia-hydrogen fuel cells. The method includes: first, acquiring multi-dimensional non-stationary signals such as voltage, current, three-dimensional temperature field, broadband acoustic vibration, distributed fiber strain, and temperature across the entire fuel cell stack using a multi-source sensor system deployed on the stack; second, introducing an adaptive fractional-order manifold sieving mechanism to orthogonally decouple the signals and extract fault features; third, constructing a dual-flow collaborative decision-making architecture consisting of a deep physical evolution flow and a fast response pre-diagnosis flow, respectively performing deep fault probability calculation and real-time early warning, and fusing the two at the decision level to obtain the diagnostic result; finally, optimizing the model parameters using a parametric manifold multi-objective particle swarm optimization equilibrium search strategy. This invention achieves full-chain innovation from signal processing and model architecture to parameter optimization, significantly improving the sensitivity, robustness, and physical consistency of early fault diagnosis.

The present invention relates to a negative capacitive fiber-type strain sensing system comprising: an induction coil for transmitting and receiving electrical stimulation signals; a fiber strain sensor in which a first electrode, a dielectric fiber and a second electrode are sequentially arranged, and which is formed by winding the first electrode, the dielectric fiber and the second electrode a plurality of times into a spring structure; and a transmission line electrically connecting the induction coil to the fiber strain sensor, and thus wireless signal amplification with the body is possible such that recovery efficiency can be increased through effective rehabilitation and therapeutic assistance.

The invention discloses a displacement sensor and a displacement measurement system, and the displacement of an object to be measured can be obtained according to the interference light spectrum by obtaining the interference light spectrum of the reflected light generated by the incident light on the end face of a light guide part and the reflected light generated by the incident light on the end face of a top column. According to the displacement sensor and the displacement measurement system, conversion operation among displacement, optical fiber strain and grating resonant wavelength is not needed, so that the influence of temperature change on measurement can be reduced, and the measurement error is reduced.

The invention discloses a shape follow-up steel structure fatigue crack state monitoring device and method, and belongs to the technical field of steel structure fatigue crack monitoring. The monitoring device structurally comprises N optical fiber shape follow-up sensing films, a signal transmission optical fiber, a scattering enhancement optical fiber strain demodulator and an upper computer; the optical fiber conformal sensing film comprises a conformal flexible film, a scattering enhanced optical fiber strain sensing array and a temperature compensation optical fiber measuring point; the scattering-enhanced optical fiber strain sensing array is fixed on the shape-followed flexible film and comprises a plurality of scattering-enhanced optical fibers and arc-shaped connecting optical fibers connected with the scattering-enhanced optical fibers. According to the method, the spectral frequency offset is obtained by using the scattering enhancement optical fiber strain demodulator, the influence of the environment temperature is eliminated through the temperature compensation optical fiber measuring points, and the strain distribution and the crack width change of each measuring point are further inverted based on the spectral frequency offset, so that the crack state in the monitoring area is identified. According to the invention, high-precision and real-time automatic monitoring of the fatigue crack state of the complex area of the steel structure is realized.