313 results about "Fiber bragg grating sensor" patented technology

A shape-sensing system can include a stylet, an optical interrogator, a console, and a display screen. The stylet can include an optical fiber with fiber Bragg grating (“FBG”) sensors along a length of the optical fiber. The optical interrogator can be configured to send input optical signals into the optical fiber and receive FBG sensor-reflected optical signals from the optical fiber. The console can be configured to convert the reflected optical signals with the aid of filtering algorithms of some optical signal-converter algorithms into plottable data for displaying plots thereof on the display screen. The plots can include a plot of curvature vs. time for each FBG sensor of a selection of the FBG sensors for identifying a distinctive change in strain of the optical fiber as the stylet is advanced into a superior vena cava of a patient.

The invention discloses a coastal protection dam settlement monitoring method, and belongs to the technical field of hydraulic engineering safety monitoring. The method comprises the steps that a longitudinal monitoring section is arranged on the slope surface of the back sea side of a dam, a three-measuring-line fiber grating sensor array is arranged, and vertical displacement and horizontal dip angle data are periodically collected through a synchronous triggering unit; establishing a vertical displacement-horizontal dip angle joint analysis model by using a multi-source data fusion module, and eliminating tide level interference through a Kalman filtering algorithm to generate a settlement distribution curve; and triggering third-level to first-level early warning signals based on the grading early warning rule, and transmitting the signals to the terminal equipment. The problems that a traditional monitoring method cannot effectively separate tidal interference, the real-time performance is poor, and multi-dimensional data collaborative analysis is insufficient are solved, high-precision settlement monitoring, complex environment anti-interference and rapid emergency response are achieved through multi-measuring-line sensor deployment, dynamic filtering optimization and a graded early warning mechanism, and the method is suitable for large-scale popularization and application. And the reliability and timeliness of dam safety monitoring are obviously improved.

The invention provides an LNG ship containment system monitoring system and method based on a fiber bragg grating sensor, and belongs to the crossing field of fiber sensing technology and ship safety engineering, the system comprises a fiber bragg grating sensor and a demodulation device, the fiber bragg grating sensor is used for collecting optical signals, and the demodulation device converts the optical signals into electric signals and processes the electric signals. The fiber bragg grating sensor adopts a double-grating structure and is respectively used for stress monitoring and temperature compensation so as to realize omnibearing real-time monitoring. The fiber grating sensor comprises a tail fiber, a protective tube, a base, and a strain grating, a spring and a temperature grating which are located in the protective tube. According to the invention, the monitoring precision and safety of the LNG ship containment system can be improved; through a double-grating temperature compensation technology, the influence of temperature change on stress measurement is eliminated, and the accuracy and reliability of data are ensured; in addition, stress information in different directions can be obtained in real time through the three-dimensional stress monitoring scheme, the stress condition of the structure is comprehensively reflected, and the flexibility and adaptability of monitoring are improved.

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

The invention discloses an equipment environment detection method and system based on a fiber grating sensor, and relates to the technical field of equipment environment detection methods, and the comprehensive environment of equipment is determined based on the internal production environment of the equipment, the production image of the equipment and the external environment of the equipment. The internal production environment of the equipment, the production image of the equipment and the external environment of the equipment are integrally controlled, accurate detection of the comprehensive environment of the equipment is achieved, and the accuracy of the comprehensive environment of the equipment is improved. Therefore, the production grade of the equipment is determined according to the comprehensive environment of the equipment and the detection of the real-time image of the material produced by the equipment; and if the production grade of the equipment is lower than the preset production grade threshold value, determining the abnormal part in the equipment based on the abnormal detection of the equipment, and triggering the autonomous regulation and control of the abnormal part, thereby realizing the autonomous regulation and control of the abnormal part, and fully considering the production grade of the equipment.

The invention discloses a multi-parameter monitoring and intelligent early warning system and method for a mine car dry disc braking device. The system comprises a data processing module, and a high-temperature fiber grating sensor, a laser displacement sensor, a piezoelectric vibration sensor, an industrial camera and an early warning execution module which are in signal connection with the data processing module. The data processing module corrects and processes the acquired temperature signal, thickness signal, vibration frequency signal and surface image signal, judges the wear state of the current brake device according to the signal processing result, and judges whether to send an early warning signal to the early warning execution module or not according to the wear state; and the early warning execution module implements corresponding early warning action according to the early warning signal. According to the method, the problem of misjudgment caused by single parameter monitoring is effectively solved, and the fault recognition accuracy is remarkably improved through multi-dimensional data cross validation. Seamless connection from state monitoring to safety protection is achieved through a closed-loop control system. And the multi-sensor cooperative working mode can effectively ensure the detection precision.

The invention relates to the technical field of sensor noise reduction, and particularly discloses a fiber bragg grating sensing system based on deep learning and a noise reduction method.The method comprises the steps that firstly, original reflection spectrum data of a fiber bragg grating sensor and temperature data of the environment where the fiber bragg grating sensor is located are synchronously collected, and a data processing algorithm based on deep learning is introduced; the method comprises the following steps: performing empirical mode decomposition and waveform feature extraction on original reflectance spectrum data to capture intrinsic intrinsic mode waveform features of the original reflectance spectrum data, then further combining environment temperature data, and performing implicit query interactive response coding on environment temperature features and the intrinsic mode waveform features of the original reflectance spectrum to obtain the intrinsic mode waveform features of the original reflectance spectrum; therefore, the dynamic influence mode of the environment temperature on the reflectance spectrum data can be understood, and the temperature compensation and noise reduction of the reflectance spectrum data can be realized. Through the mode, the influence of temperature fluctuation on the reflection spectrum can be adaptively identified and compensated, the noise caused by environment temperature fluctuation is effectively inhibited, and the measurement precision of the fiber grating sensor is improved.

The invention provides an underwater sonar target detection system and method. The underwater sonar target detection system comprises an optical fiber hydrophone array module which comprises a plurality of optical fiber hydrophone units, each unit comprises an optical fiber Bragg grating sensor and a sound pressure signal demodulation device, and the optical fiber hydrophone array module is used for collecting underwater sound wave signals in real time and converting the underwater sound wave signals into first electric signals; the sonar transmitting-receiving array module comprises a broadband sonar transmitter, a multi-beam receiver and a signal preprocessing circuit, and is used for actively transmitting a frequency modulation continuous wave signal, receiving a target reflection echo and generating a second electric signal; and the multi-mode signal fusion processing module comprises a high-speed data acquisition card, a self-adaptive noise suppression unit and a time-frequency analysis unit. The underwater sonar target detection system and method provided by the invention have the advantages of relatively high reliability, relatively high detection performance, relatively accurate cross-modal signal fusion and capability of performing intelligent target identification and tracking.

The invention relates to an automobile bunching belt detection method, system and device and a storage medium, and the method comprises the steps: carrying out the initial detection of a bunching belt through a multi-mode sensing device, obtaining an initial detection result, and enabling the multi-mode sensing device to comprise an industrial CT, a high-frequency ultrasonic phased array and a fiber Bragg grating sensor; designing a multi-physics field cooperative loading working condition of a simulated bunch strip service environment to obtain multi-physics field loading data; constructing a dynamic damage accumulation model based on the multi-physical field loading data and the initial detection result; based on the dynamic damage accumulation model and a machine learning algorithm, predicting the remaining service life of the cable tie, and generating a service life prediction result of the cable tie; and generating a comprehensive detection report in combination with the initial detection result, the multi-physics field loading data and the life prediction result. The method and the device have the effect of improving the detection accuracy of the bunching belt.

The invention discloses a battery thermal runaway early warning method based on multi-sensing information fusion, which is suitable for safety management of a lithium ion battery. A fiber bragg grating sensor is embedded into a battery, temperature and strain multi-dimensional physical parameters of the battery are monitored in real time, external electrochemical parameters are combined, and a multi-source sensing information fusion system is constructed. And by analyzing a square curve of an internal strain derivative, temperature gradient change and voltage drop characteristics, a thermal runaway early-stage signal is extracted, and graded early warning is realized. According to the method, the hysteresis of traditional surface parameter monitoring is broken through, an early warning signal is provided before thermal runaway, and the safety and reliability of a battery system are remarkably improved.

The invention provides a highway bridge joint vibration and deformation condition monitoring method, and particularly relates to the technical field of bridge structure health monitoring, and the method comprises the steps: laying a fiber bragg grating sensor array at a bridge joint, and the array comprises a plurality of fiber bragg grating sensors which are distributed at intervals along the length direction of the joint; and each sensor is connected with the joint filling body contact surface through a pre-embedded fixing structure. The sensor array collects strain signals and vibration signals in the joint in real time, analog-to-digital conversion and caching are completed through the data collection unit, digital sensing signals are generated and stored, and a historical monitoring data set is constructed. A noise suppression algorithm is adopted to filter the signal, and ambient temperature and humidity and electromagnetic noise interference are eliminated. Features are extracted based on a data fusion algorithm, and crack feature parameters reflecting the seam fine crack expansion trend are generated. A historical monitoring data set and the parameters are combined, a supervised learning model is used for calculating a dynamic adjustment threshold value, a real-time monitoring early warning signal is generated through comparison, and early-stage high-sensitivity monitoring of the seam is achieved.

The invention discloses a remote real-time monitoring and fault early warning method for a power supply operation state, and relates to the technical field of power electronics and energy management, and the method comprises the steps: collecting the temperature data of a key part of a power supply through an optical fiber Bragg grating sensor array, and analyzing the wavelength offset; electrical parameters are collected through a differential MEMS current / voltage sensor, and a permalloy / ferrite composite shielding layer is arranged in the sensor; collecting a mechanical vibration signal through a piezoelectric ceramic vibration sensor; for device data from different manufacturers, Modbus and CAN heterogeneous protocols are matched and analyzed through a regular expression, and the Modbus and CAN heterogeneous protocols are converted into a unified RDF triple format; inputting temperature, current and vibration data into a space-time alignment module, and constructing a semantic mapping relation by adopting an ontology; calculating a sensor confidence coefficient weight, and performing weighted fusion to generate an equipment health index; operating a lightweight LSTM model at an edge node, and detecting current harmonic and vibration resonance frequency band abnormity in real time; cOMSOL multi-physical field simulation is combined at the cloud end, and the evaporation rate of the capacitor electrolyte is predicted.

The invention discloses a high-voltage cable state live detection method, which relates to the technical field of power detection, and is characterized in that a mathematical model of an electric field around a cable is established by using an electrostatic field equation in a Maxwell equation set, and electric field distribution between a cable insulation layer and a conductor is solved; high-frequency electromagnetic pulse signals are measured, and partial discharge detection in the insulating layer of the high-voltage cable is carried out according to a Paschen curve model; the temperature distribution change in the cable is simulated through a heat transfer equation, and the temperature distribution of the cable is monitored in real time by using a fiber bragg grating sensor; and correcting the electric field distribution and the partial discharge detection result based on the obtained temperature distribution of the cable. The partial discharge phenomenon in the cable insulation layer can be accurately identified and positioned, the insulation state of the cable can be monitored in real time, whether the discharge phenomenon exists or not can be rapidly judged, and therefore cable faults can be effectively prevented.

A helicopter blade waving and shimmy decoupling position measuring method based on fiber bragg grating sensors comprises the following steps that a plurality of fiber bragg grating sensors are evenly pasted on the upper surface and the lower surface of a to-be-measured section of a helicopter blade in parallel from the front edge to the rear edge of the blade; flapping and shimmy bending moments are loaded on the blades respectively, and strain values corresponding to the flapping and shimmy bending moments are obtained through measurement; according to the position of the sensor and strain measurement data thereof, adopting a Kriging interpolation method to carry out interpolation on point positions with the same spacing, and obtaining an estimated value of a corresponding spatial position; establishing shimmy / flapping and flapping / shimmy decoupling coefficient evaluation functions; global traversal is carried out on the interpolation result, evaluation function values are calculated and sorted, and finally a decoupling position is determined.

The invention provides a fiber grating sensor testing device and method, and the device comprises a temperature box which is configured to adjust the temperature and maintain the temperature at a preset temperature; the stretching mechanism partially stretches into the temperature box, the tested piece is located in the temperature box and installed on the stretching mechanism, the stretching mechanism is constructed to move to a preset position so as to stretch the tested piece, and the tested piece is a fiber grating sensor; the fiber bragg grating demodulation device is configured to demodulate the reflection wavelength of the measured piece to obtain wavelength data; and the acquisition and processing device is configured to acquire displacement data of the measured piece and obtain a strain sensitivity coefficient based on the wavelength data, or acquire temperature data of the measured piece and obtain a temperature sensitivity coefficient based on the wavelength data.

The invention discloses a method for detecting the strain of a key part of a wind turbine generator based on a temperature compensation OFDR demodulation weak fiber bragg grating array, and relates to the technical field of wind turbine generator detection, and the method comprises the steps: installing a weak fiber bragg grating sensor array at the key strain part according to the structural characteristics of the wind turbine generator, a temperature reference grating is arranged in the non-strain area or the constant-temperature area so as to monitor the temperature change in real time; a tunable laser, an optical fiber coupler and a photoelectric detector are utilized to construct an optical frequency domain reflection demodulation system, and system calibration is completed; based on an optical frequency domain reflection demodulation system, reflection spectrum signals are collected, the relation between wind turbine generator strain and temperature change is analyzed through a temperature compensation mechanism, and strain information of key parts of the wind turbine generator is obtained. According to the method, the accuracy and reliability of strain detection are effectively improved, and the problem of measurement errors caused by neglecting the influence of temperature change in a traditional method is solved.

The invention relates to an unmanned aerial vehicle wing deformation monitoring sensor layout method based on modal analysis, and the method comprises the steps: determining the modal parameter detection of a wing under different working conditions through modal analysis, and employing a modal component sum index to recognize a key degree of freedom so as to optimize the position of a sensor; the method is mainly used for verifying the deformation of the wing part in the overall design process of the unmanned aerial vehicle in a laboratory. According to the method, the modal shape and the inherent frequency are obtained through finite element analysis, the modal amplitude and the participation factor of each degree of freedom are calculated, the optimal arrangement position of the sensor is further optimized through an iterative algorithm, and the arranged fiber bragg grating sensor can accurately monitor the deformation information of the wing. The data processing unit collects data and evaluates wing performance by applying a data analysis algorithm. The method improves the accuracy and comprehensiveness of deformation measurement, and provides guarantee for the flight safety and efficiency of the unmanned aerial vehicle.

The invention discloses an environment detection system and method based on a fiber bragg grating sensor in the technical field of fiber bragg grating application, and the method comprises the steps: detecting an environment through the fiber bragg grating sensor, and obtaining a grating reflection signal; stratified analysis is carried out on the grating reflection signal pair according to the physical variable type, and different physical variable information is extracted; calculating the coupling strength between different pieces of physical variable information; performing characteristic adjustment and decoupling control on the fiber grating sensor based on the coupling strength; and performing nonlinear error compensation on the physical variable information after decoupling control by using an error compensation model. Through combination of the fiber grating sensor and the error compensation model, deep fusion of a physical layer and an algorithm layer is realized, so that the system can better deal with various interference factors in a complex environment, and the fiber grating sensor can perform accurate measurement in the complex environment.

The invention provides an optical fiber type underwater robot attitude sensing device and method. The device comprises a plurality of fiber bragg grating sensors, a base, flexible silica gel, an omnidirectional rotatable transmission shaft, a spring and a stress sensing ball, wherein the plurality of fiber bragg grating sensors are embedded in the flexible silica gel; the flexible silica gel is placed in the circular base and is used as a medium to transmit the force in the vertical direction of the stress sensing ball to the plurality of fiber bragg grating sensors; the base is separated from the lower rotary transmission shaft; the omni-directional rotatable transmission shaft, the spring and the stress sensing ball form an elastic linkage system. The device is installed on the upper surface of a robot, when the posture of the robot deviates, an elastic device formed by connecting a spring and a stress sensing ball slides on the whole flexible silica gel, the stress sensing ball extrudes the flexible silica gel, accordingly, the fiber Bragg wavelength changes, the position of the stress sensing ball can be obtained by adopting a posture analysis model based on deep learning, and the posture of the robot is analyzed. Therefore, different postures of the robot are sensed.

The utility model relates to a high-capacity wavelength division multiplexing fiber bragg grating sensing system in the field of fiber sensing. The high-capacity wavelength division multiplexing fiber bragg grating sensing system comprises a mode-locked fiber laser, a spectrum expansion module, a three-port optical circulator, a fiber bragg grating array, a dispersion module, a photoelectric detector, a data acquisition module and a data processing module. The spectrum expansion module is composed of an optical fiber amplifier, a nonlinear element and a polarization controller; the optical fiber amplifier is composed of an optical isolator, an erbium-doped optical fiber, a wavelength division multiplexer and a pump light source. According to the sensing system, the dispersion Fourier transform technology is applied, the offset of the center wavelength of the fiber bragg grating is mapped into the offset of time delay between time domain reflected light pulses, and the demodulation rate and precision of the fiber bragg grating sensing system are improved; and by adding a spectrum expansion module, the spectrum of pulse data output by the light source laser is expanded into a super-continuum spectrum by using a nonlinear effect, and the simultaneous measurement of hundreds of fiber bragg grating sensors can be theoretically supported.

Apparatuses and methods therefor generally relate to sensing. In one example of such an apparatus, there is a platform. An optical fiber with Fiber Bragg Grating sensors is located in a trench formed in the platform. The trench has curved sections. The Fiber Bragg Grating sensors are respectively in the curved sections of the trench.

The invention relates to a concrete bridge deflection monitoring method based on a distributed fiber bragg grating in the field of optical fiber sensing. The problems that in an existing bridge deflection monitoring method, instruments are inconvenient to install and prone to being affected by the environment, and networking is difficult are solved. The invention provides a distributed fiber Bragg grating-based concrete bridge deflection monitoring method, which comprises the following steps of: determining a monitoring total length, and dividing units and end points; distributed fiber bragg grating sensors are arranged at the bottom and the upper portion of a bridge in a parallel topology mode, and monitoring intervals are divided; wavelength data are collected, and strain values of the bottom and the upper portion of the bridge in each monitoring interval under the load condition are obtained; calculating the curvature of each end point by using a parallel topology principle; and calculating the deflection value of each end point by using a finite integral method and a Lagrange interpolation method. The method is simple in thought, the deflection values of multiple points of the bridge are obtained through the wavelength-strain-curvature-deflection data processing flow, and the method has certain engineering use value.

The invention discloses a method for measuring fan blade root stress based on a fiber bragg grating sensor. According to the method, 6-10 key measurement points are selected in a blade root area of a fan blade, a pair of FBG sensors is installed at each measurement point, one FBG sensor is used for stress measurement (affected by strain and temperature at the same time), the other FBG sensor is used for temperature compensation, and decoupling of temperature and strain signals is achieved. The system adopts a single-mode optical fiber, a broadband light source (the wave band is 1525-1565 nm, and the power is 10-20 mW) and a high-resolution spectrum analyzer (the resolution is smaller than or equal to 1 pm, and the sampling rate is larger than or equal to 100 Hz or 1 kHz) to collect optical signals reflected by an FBG sensor in real time, measured wavelength shift is converted into accurate strain data through temperature compensation and a strain calculation formula, and the optical signals are transmitted to the FBG sensor. And calculating a stress value by combining the Young modulus and Poisson's ratio of the material. The method has the advantages of being high in precision, high in real-time performance, resistant to electromagnetic interference and suitable for seaborne, high-altitude and other severe environments, and reliable data support can be provided for dynamic stress monitoring, fatigue life prediction and fault early warning of the fan blade.

The invention provides an antenna oscillator production method, an antenna oscillator and communication equipment, and the method comprises the following steps: S1, material pretreatment: selecting a high-conductivity titanium-aluminum alloy plate, eliminating initial stress through vacuum annealing, and after annealing, removing an oxide layer and organic matters through plasma cleaning equipment; and S2, composite forming: carrying out stamping and stretching forming on the titanium-aluminum alloy plate by using a die to form an antenna oscillator, and integrating a fiber bragg grating sensor in the stamping process to monitor the stress distribution of the material in real time. According to the production method of the antenna oscillator, the antenna oscillator and the communication equipment, the annealing and cooling processes are accurately controlled, and the stress distribution is monitored in real time by using the FBG sensor, so that the production period of the antenna oscillator is remarkably shortened, the waiting time in the production process is reduced, and the production efficiency is improved. The problems of deformation, cracking and the like caused by stress concentration in the machining process of the antenna oscillator are greatly reduced, the rejection rate is reduced, and waste of raw materials and energy is reduced.

The invention discloses a chlorine salt corrosion resistant prestressed concrete solid square pile and a construction method thereof, a cementing material of a pile body concrete body of the square pile comprises a mineral admixture accounting for 50%-70% of the total mass of the cementing material, and the cementing material adopts Portland cement; sacrificial anode blocks electrically connected with the main reinforcements are embedded in the pile body concrete body. The pile body concrete body is doped with a composite corrosion-resistant and rust-resistant agent; the outer surface of the pile body concrete body is coated with polyurea waterproof paint or epoxy seal primer. An electromigration type corrosion inhibitor and a microcapsule containing bacillus are doped into the pile body concrete body; the prestressed main reinforcements are steel reinforcements with anti-corrosion coatings; and fiber bragg grating sensors are pre-embedded around the prestressed main reinforcements. The mixing proportion of the concrete body of the pile body is specially designed for fixing and blocking chloride ions, an inapplicable sulfate-resistant cement scheme is abandoned, and the chlorine salt resistance is improved from the source of materials.

The invention discloses a tunnel longitudinal deformation self-sensing system and method based on an intelligent bolt, the system comprises the intelligent bolt and a computer terminal, the intelligent bolt comprises a bolt main body connected to a tunnel segment; the fiber bragg grating sensor is installed in the bolt body and used for generating corresponding wavelength change based on deformation of the tunnel segment and outputting a wavelength change optical signal; the integrated circuit board is used for receiving the wavelength change optical signal, calculating the bolt axial force of the bolt body based on the wavelength change, and further calculating the longitudinal curvature of the tunnel; and the threshold indicator lamp is used for controlling the light emitting color of the threshold indicator lamp according to the range value of the longitudinal curvature of the tunnel. Compared with the prior art, the method has the following beneficial effects that the stress deformation of the bolt is monitored in real time, the relationship between the stress deformation of the bolt and the longitudinal deformation of the tunnel is established, and finally the tunnel deformation condition is visually reflected through the intelligent bolt with the threshold indicator lamp, so that the problem of poor deformation perceptibility in current tunnel monitoring can be solved.

The invention discloses a true triaxial dynamic and static combined loading and multi-field coupling test device and method. The test device comprises a test cavity; the loading system comprises an axial loading device, a Hopkinson pressure bar, a longitudinal loading device and a vertical loading device; the axial loading device is configured to apply an axial load to the test coal sample; the Hopkinson pressure bar is configured to apply an impact load to the test coal sample; the longitudinal loading device is configured to apply a longitudinal load to the test coal sample; the vertical loading device is configured to apply a vertical load to the test coal sample; the gas supply system comprises a gas bottle and is configured to inject gas into the test cavity; the fiber bragg grating monitoring system comprises a fiber bragg grating sensor and a fiber bragg grating demodulator, and the fiber bragg grating demodulator is configured to be used for sensing a change signal of a strain field of the test coal sample under the loading action of the loading system; and the ultrasonic phased array monitoring system comprises an ultrasonic transducer and is used for sensing an ultrasonic signal of the test coal sample under the loading action of the loading system.

The utility model discloses a fiber grating sensor with a heat insulation function, and relates to the technical field of fiber grating sensors, in particular to a fiber grating sensor with a heat insulation function, which comprises an armor optical cable, an outer shell and an elastic element, and a grating is engraved on the exposed part of the end part of the armor optical cable; the grating and one part of the elastic element are fixed together through the inner shell, multi-layer heat insulation protection is carried out on the inner shell through an aerogel felt layer, a ceramic silicone rubber layer and a polytetrafluoroethylene layer in the heat insulation assembly, external high temperature is prevented from being transmitted to the grating, and then the influence of the high temperature on the grating is avoided; the other end of the elastic element penetrates through the inner shell and the heat insulation assembly, and the other end of the elastic element is used for bearing force; the stress of the elastic element acts on the grating, the grating receives the stress change, and the wavelength of the grating shifts. According to the fiber grating sensor with the heat insulation function, the purpose of heat insulation is achieved, and meanwhile, the detection accuracy and sensitivity are not affected.

The present invention provides a non-contact optical fiber sensing system and method. The system includes a passive fiber Bragg grating sensor and an active demodulation analyzer. The passive fiber Bragg grating sensor includes an optical fiber and a fiber Bragg grating sensor connected in series on the optical fiber. The active demodulation analyzer includes a laser light source, an optical circulator, and a demodulation analyzer. One end of the passive fiber Bragg grating sensor is connected with a first fiber collimator. The active demodulation analyzer further includes a second fiber collimator and an alignment mechanism. The laser light source is connected to the first end of the optical circulator for outputting an optical signal. The optical fiber led out from the second end of the optical circulator is connected with the second fiber collimator. The second fiber collimator is used for non-contact alignment with the first fiber collimator under the adjustment of the alignment mechanism so as to transmit the optical signal bidirectionally. The demodulation analyzer is connected to the third end of the optical circulator. The present invention can expand the application scenarios of the optical fiber sensing system and save costs.

The invention relates to the technical field of post insulator detection, and discloses a post insulator crack detection method and system based on stress wave recursion characteristics, and the method comprises the steps: S1, generating an initial stress wave through a high-energy pulse exciter, and introducing the stress wave into a post insulator; s2, collecting a dynamic response signal of insulator stress wave propagation by using a distributed fiber bragg grating sensor network; s3, carrying out preprocessing on the dynamic response signal; s4, acquiring real-time environment parameters through an environment monitoring sensor; s5, combining material attributes and geometric structures of the post insulators; and S6, outputting recursive quantization features based on the recursive neural network model. According to the method, a stress wave propagation path is dynamically tracked by constructing a recurrent neural network model, multiple reflection characteristics of waves are quantified, abnormal phase deviation is accurately captured based on material attribute physical constraints, and the energy characteristic analysis capability of tiny defects is remarkably enhanced.