3743 results about "Optical fiber sensing" patented technology

The invention discloses a tunnel multi-source fusion dynamic twin surrounding rock intelligent prediction and control method and system, and the method comprises the steps: collecting multi-source heterogeneous data in real time through intelligent drilling equipment, a distributed optical fiber sensing network and a mobile scanning device which are disposed on a tunnel construction surface; inputting the multi-source heterogeneous data into a space-time diagram convolutional network, constructing a space-time correlation model of geological features and construction disturbance parameters, and outputting a coupling feature matrix; based on the coupling characteristic matrix, simulating the dynamic response of the surrounding rock-support system through a streaming voxelization engine and a multi-physics coupling engine, and generating a risk evolution three-dimensional thermodynamic diagram; and inputting the risk evolution three-dimensional thermodynamic diagram into the deep reinforcement learning model, and dynamically optimizing to generate a construction parameter regulation and control instruction meeting a safety constraint condition. According to the technology, a full-link channel of'data perception-mechanical analysis-decision execution 'is opened in a closed-loop mode, and therefore the double risks of'data distortion misjudgment' and'response lag out-of-control 'of a traditional method are avoided.

The invention relates to the technical field of anti-cracking performance testing, in particular to an ultra-high performance concrete anti-cracking performance testing system and a dynamic monitoring method thereof.The system comprises a dynamic stress field simulation feedback module used for sensing three-dimensional distribution of a micro stress field in concrete in real time by constructing a flexible loading array to obtain dynamic stress field data; the multi-scale damage evolution tracking module is used for deploying a high-resolution acoustic emission network and a distributed optical fiber sensing layer based on dynamic stress field data of the flexible loading array to form a full-scale evolution graph from microdefects to macroscopic cracks; and the intelligent healing efficiency evaluation module obtains stress redistribution data and a full-scale evolution graph, and a repairing medium containing a tracer agent is injected into a preset crack path. According to the method, the whole process of crack resistance of the material from defect initiation to repair and regeneration can be quantitatively evaluated; and finally, outputting a dynamic evolution rule of the crack resistance and enhancing potential evaluation.

The invention relates to the technical field of laser control, in particular to a high-power fiber laser stable output control method and system. The method comprises the following steps: monitoring a multi-mode sensing signal of an optical fiber laser in real time based on an optical fiber sensor array; performing dynamic optical fiber sensing change analysis on the multi-mode sensing signal of the optical fiber laser to generate a dynamic optical fiber sensing change characteristic; laser output phase distribution analysis is carried out on the dynamic optical fiber sensing change characteristics, real-time power feedback adjustment is carried out, and a dynamic light beam power feedback adjustment strategy is constructed; overheat power unbalance analysis is carried out based on a fiber laser multi-mode sensing signal, and local temperature control power fine tuning is carried out, so that a local temperature control power fine tuning strategy is constructed; and performing sensor position calculation on the optical fiber sensor array one by one, and performing nonlinear optical effect analysis to generate nonlinear optical effect characteristics. According to the invention, efficient and stable laser output control is realized.

The invention relates to the technical field of reservoir earth and rockfill dam leakage abnormity safety monitoring and early warning, in particular to an earth and rockfill dam leakage abnormity real-time monitoring and early warning system based on deep learning and a medium. The system comprises a data sensing transmission module, a data fusion processing and analysis module, an early warning evaluation module, a system management and maintenance module, a database management module and an emergency response command module. Through a well-ground collaborative full-dimensional electrical method and shallow earth surface and full-section distributed optical fiber sensing, the system collects and transmits multi-source data. And multi-mode fusion and a deep learning algorithm are adopted to realize multi-physical field feature extraction and three-dimensional modeling. The system generates graded early warning information based on dynamic threshold and multi-factor coupling, and realizes automatic real-time monitoring, intelligent early warning and efficient management of leakage abnormity of the earth and rockfill dam in combination with a database, management maintenance and emergency response functions. According to the invention, the accuracy of earth and rockfill dam leakage abnormity identification and the intelligent level of early warning are improved.

The invention discloses an intelligent cable fault accurate positioning and early warning method and system, and the method comprises the steps: collecting the temperature gradient, strain distribution and partial discharge signals of the whole length of a cable in real time through a distributed optical fiber sensing network, and generating a multi-dimensional feature matrix of the operation state of the cable; based on the multi-dimensional feature matrix, outputting a preliminary fault positioning coordinate; generating corrected fault coordinates according to the topological structure data of the cable laying environment and the electromagnetic interference distribution diagram; historical fault data, real-time operation parameters and the corrected fault coordinates are fused, and a fault risk thermodynamic diagram in a future preset duration is output; and based on the fault risk thermodynamic diagram and real-time monitoring data, generating fault first-aid repair information by using a dynamic priority algorithm, synchronously triggering an early warning signal, and visually displaying a fault positioning result and a risk area in a three-dimensional geographic information system. According to the embodiment of the invention, rapid positioning, accurate early warning and intelligent disposal of the cable fault can be realized.

The invention provides a distributed optical fiber-based soil roadbed deformation monitoring method and monitoring system, and the method comprises the steps: obtaining a distributed optical fiber sensing data set of a target soil roadbed, dividing the target soil roadbed into a plurality of monitoring regions with different deformation characteristics according to the deformation intensity distribution of an optical fiber strain data sequence, and carrying out the monitoring of the deformation of the target soil roadbed. And performing coupling analysis processing on the optical fiber strain data sequence and the temperature compensation data sequence of each monitoring area to generate a multi-dimensional deformation feature set of the monitoring area, and generating deformation early warning information of the target soil roadbed according to a space-time matching result of the multi-dimensional deformation feature set and a preset deformation threshold condition. And generating a soil roadbed deformation optimization strategy based on the deformation early warning information, and feeding back the soil roadbed deformation optimization strategy to the roadbed maintenance system to trigger reinforcement response operation. The method can effectively improve the active control capability of the health state maintenance of the soil roadbed.

The invention relates to the technical field of grouting simulation tests, in particular to a sandy gravel stratum catastrophe grouting prevention and control virtual-real blending collaborative test method and system, and the method comprises the steps: carrying out a grouting test on a sandy gravel stratum simulation model, and obtaining grouting parameters and monitoring parameters in the grouting process; based on the resistivity and the radar data, further obtaining a slurry diffusion path and a diffusion range of the area with the higher surrounding rock grade; based on the resistivity and the optical fiber sensing data, the slurry diffusion path and the diffusion range of the area with the low surrounding rock grade are further obtained; inputting the initial grouting parameters into the trained neural network model to obtain simulation data; carrying out preprocessing and alignment operation on the previous data, and carrying out fusion analysis; and according to the fusion analysis result, grouting equipment parameters and a grouting scheme are pre-controlled and adjusted. And real-time regulation and control of a grouting scheme and equipment are realized.

The invention discloses a lightning arrester operation state online monitoring and evaluation method and system, and relates to the technical field of lightning arrester operation state monitoring, and the method comprises three steps of cooperative correction, health degree evaluation and local defect discrimination. According to the cooperative correction, data is acquired through a multi-sensor network, an environment compensation model is established to optimize the leakage current measurement precision, and a filter is dynamically adjusted to suppress interference signals. Health degree evaluation is fused with multi-dimensional features, a dynamic entropy weight method and a self-adaptive membership function are adopted to realize accurate state grading, and the parameter coupling analysis capability is improved through covariance correction. Local defect identification utilizes a distributed optical fiber sensing network and a digital twinning technology to realize real-time positioning and growth prediction of microdefects. The monitoring precision and reliability of the operation state of the lightning arrester can be effectively improved, potential faults can be found in time, the maintenance cost is reduced, and safe and stable operation of a power system is guaranteed.

The invention discloses a long-distance communication optical cable fault automatic detection and positioning system and method, and the method comprises the steps: collecting optical signal data in an optical fiber link in real time through the deployment of a multi-optical fiber sensor or a distributed optical fiber sensing technology; denoising processing is carried out on the collected data, abnormal fluctuation is analyzed by applying a self-adaptive algorithm, and the type of a fault which is about to occur is identified; classifying the faults by using a machine learning classification algorithm; time domain reflection and wavelength multiplexing technologies are combined, a composite algorithm is adopted to accurately position a fault point, and path optimization and error correction are carried out through sensing node data comprehensive analysis; an environment compensation algorithm is introduced, influences of environment factors on the optical signals are analyzed in real time, and errors are eliminated; and based on a fault positioning and analysis result, an AI algorithm is adopted to evaluate a fault influence range, a repair scheme is automatically generated, and priorities are scheduled for repair.

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.

The invention discloses an air-ground cooperative monitoring and early warning method and system for a buried gas pipeline in a landslide hidden danger area, and the method comprises the steps: carrying out the ground monitoring through employing distributed optical fiber sensing, and enabling an optical fiber sensor to be embedded in the outer wall of the buried gas pipeline or to be laid with an accompanying optical fiber pipeline; collecting multiple physical quantity data of strain, temperature and vibration of the pipeline; in-air monitoring, a multi-sensor platform carried by an unmanned aerial vehicle is used for carrying out in-air inspection; the air monitoring data and the ground monitoring data are fused, and a landslide hidden danger area pipeline safety state evaluation model is constructed; performing real-time intelligent analysis on the fusion data by using an advanced mixed attention convolutional neural network, and identifying a potential catastrophe hidden danger area of the pipeline; and according to a risk assessment result, early warning grading is carried out, and a corresponding emergency plan is formulated. According to the method, real-time and accurate monitoring of the pipeline state can be realized, the landslide hidden danger can be found in time, accurate early warning can be realized, and safe operation of the buried gas pipeline in the landslide hidden danger area can be effectively guaranteed.

The invention discloses a photovoltaic power station intelligent remote operation and maintenance method and system based on relay protection, and the method comprises the steps: collecting the multi-mode characteristic quantity of a photovoltaic array region relay protection device in real time through a distributed optical fiber sensing network, so as to construct a dynamic protection characteristic matrix; performing feature decoupling on the dynamic protection feature matrix by adopting a space-time convolution adversarial encoder to generate a fault feature vector set; inputting the fault feature vector set into a physically constrained LSTM-GAN hybrid prediction model, and predicting a multi-dimensional failure probability tensor of the key relay protection node in a future preset duration; generating an optimal operation and maintenance strategy decision tree based on the multi-dimensional failure probability tensor; and analyzing the operation and maintenance strategy decision tree through a remote execution gateway driven by the digital twinborn, and synchronously updating the topological connection relationship of the digital twinborn bodies of the power station. According to the embodiment of the invention, the operation and maintenance efficiency and reliability of photovoltaic power station protection can be improved.

The invention provides a comprehensive pipe gallery structure health monitoring system based on distributed optical fiber sensing, and relates to the technical field of engineering detection, and the system comprises a laying module which is used for laying an optical fiber sensing optical cable with waterproof and anti-corrosion performances in a pipe gallery structure, setting a positioning reference point and a coordinate calibration reference point in the central area of the tops of the two ends of a pipe gallery, and setting a positioning reference point and a coordinate calibration reference point; a linear reference system covering the length of the whole pipe gallery is constructed; and the acquisition module is used for connecting the optical fiber sensing optical cable with the distributed optical fiber temperature measuring device and the distributed optical fiber strain device, and acquiring temperature distribution data and strain distribution data in the pipe gallery based on Raman scattering and Brillouin scattering principles to form a monitoring data set. According to the invention, the temperature and strain multi-dimensional data of the pipe gallery are collected in real time through the distributed optical fiber sensing technology, and the structure health monitoring is realized in combination with redundancy monitoring, dynamic compensation and an intelligent early warning mechanism.

The invention relates to the technical field of structure health monitoring, and discloses an underground pipe gallery structure corrosion monitoring and evaluation method based on optical fiber sensing, which comprises the following steps: constructing a composite optical fiber sensing structure which comprises a Fe-C alloy coated optical fiber and a long-period grating, synchronously monitoring the chemical component change and the structural mechanical state of the corrosion product through the photoluminescence spectrum characteristic peak displacement and the strain distribution cloud picture; measuring deviation caused by coating layer loss is dynamically corrected in combination with the change rate of the environment refractive index; a reference grating is embedded to eliminate temperature drift interference, and iron ion in-situ deposition is triggered to realize sensing interface self-repairing. According to the invention, through a multi-physical-quantity cooperative sensing and self-adaptive compensation mechanism, the problems of signal interruption and the like caused by difficult decoupling of chemical-mechanical parameters and film coating failure in traditional monitoring are avoided, the long-term stable monitoring capability of a corrosion process in a complex environment is remarkably improved, and high-precision data support is provided for safety assessment of an underground pipe gallery structure.

The invention, which relates to the technical field of landslide monitoring, discloses an optical fiber sensing landslide dynamic response monitoring system comprising an event monitoring module, a sampling optimization module, a landslide risk analysis module and an early warning level adjustment module. By comparing the offset of adjacent data points in real time, tiny displacement abnormity can be quickly identified, instant marks are provided for early geological activities, and the sampling frequency is automatically adjusted according to real-time monitoring data, so that data acquisition is finer, meanwhile, storage and processing of irrelevant data are reduced, the operation efficiency of the system is effectively improved, and the working efficiency of the system is improved. Real-time data and a historical landslide mode are finely compared, comprehensive analysis is carried out in combination with key indexes such as earth surface displacement and soil humidity, the system can accurately calculate the probability of occurrence of the landslide, the accuracy and timeliness of early warning are greatly improved, and casualties and property losses caused by landslide disasters are effectively reduced.

The invention discloses a building foundation settlement and stability long-term monitoring method and system. According to the method, building settlement related data are collected through a distributed optical fiber sensing network, an inclination sensor array and a soil pressure sensor; establishing a soil stress memory effect calculation model, and calculating effective stress considering the memory effect; constructing a building foundation settlement total model containing main consolidation settlement, creep settlement and additional settlement caused by environmental factors; according to the method, risk grade division is carried out based on multi-level threshold values, early warning advance is calculated, an emergency response strategy is generated, intelligent monitoring and early warning of building foundation settlement are achieved, and the method has important engineering application value.

The invention discloses a karst cave pile foundation grouting real-time control system based on optical fiber sensing and AI dynamic optimization, which relates to the field of pile foundation grouting real-time control and comprises a data acquisition module, an intelligent analysis module, a dynamic optimization module and a feedback control module. Normalized optical fiber input vectors and geological input vectors are obtained by analyzing karst cave optical fiber sensing data and geological parameter data, fusion is performed through a double-branch convolutional network, a grouting diffusion prediction model is constructed through a convolutional neural network, the slurry diffusion radius and the filling saturation are output, the model is constructed based on an isolated forest algorithm, and the grouting diffusion prediction model is constructed. The method comprises the following steps: calculating abnormal score early warning, establishing a mapping model, and dynamically adjusting the weight to obtain a Pareto optimal solution set adjusted in each construction stage, and a closed-loop control module can perform timely early warning adjustment on an accident according to the Pareto optimal solution set adjusted by real-time progress and rescreening parameters, can sense data in real time to form closed-loop feedback, and meets the requirements of engineering economy.

The invention relates to a surface collapse monitoring system based on multi-parameter distributed optical fiber sensing, and the system comprises a monitoring module which comprises a plurality of fully distributed optical fiber sensors laid in a monitoring area, and an optical signal transmission and demodulation module which comprises a continuous spectrum laser, an optical switch, an optical amplifier, an optical filter, and a demodulation module. The data processing and analysis center comprises a data acquisition module and a collapse model modeling module, and the data acquisition module is used for performing acquisition and digital conversion on the optical signal demodulated by the demodulation module; the collapse model modeling module constructs a model according to the monitoring data and can predict the development trend of surface collapse; and the early warning and communication module communicates with a remote monitoring center. The monitoring system provided by the invention has the advantages of multi-parameter monitoring, high monitoring precision, suitability for large-scale laying, real-time response and the like, and can comprehensively and accurately reflect the real condition of surface collapse.

The invention provides a high-negative-pressure gas extraction drill hole full-life-cycle efficiency evaluation method, and belongs to the technical field of mineral exploitation. A ground stress distribution model is established through microseism monitoring to determine drill hole arrangement parameters; a distributed optical fiber sensing system and a multi-parameter gas flow meter are used for monitoring the stress change around a drill hole and gas extraction data in real time, the coal fracture development degree is obtained in combination with sound wave testing, and all the data are input into a physical numerical value coupling model to calculate a permeability dynamic evolution curve. Establishing a permeability influence coefficient matrix and determining a key parameter weight, constructing an evaluation index system including the extraction amount, the permeability change rate, the drilling life and the coverage range, and performing multi-objective optimization configuration by applying a Pareto optimal solution theory. The technical problem that full-life-cycle dynamic monitoring and comprehensive efficiency evaluation of the high-negative-pressure gas extraction drill hole are lacked at present is solved.

The invention discloses a submarine cable fault online diagnosis and positioning method and system based on an optical fiber sensing technology, and relates to the technical field of optical fiber sensing, and the method comprises the steps: obtaining a real-time strain data flow of a submarine cable through a distributed optical fiber strain measurement device; carrying out space-time alignment and abnormal value correction processing on the original data set, and constructing a target data set; coordinate mapping is carried out on the target data set and a geographic information system of a submarine cable laying line, and a fault diagnosis layer with multi-dimensional visualization features is generated; an interactive fault analysis panel is generated on a geographic information system interface, and the deviation ratio between the strain theoretical threshold value and the actual measurement value of each monitoring point in the target data set is calculated; according to the submarine cable fault online diagnosis and positioning method and system based on the optical fiber sensing technology, rapid positioning of fault features is achieved, the fault response efficiency is improved, and long-term stable operation of a submarine communication network is ensured.

The invention belongs to the technical field of distributed optical fiber sensing, and particularly relates to an OFDR system phase noise compensation device and method based on an or equivalent optical fiber loop auxiliary interferometer. The optical fiber 2 * 2 coupler and the delay optical fiber form a loop and serve as a delay optical path of the auxiliary interferometer, the optical delay can be doubled every time laser passes through the loop, and therefore a plurality of beat frequency signals with different optical delays are obtained. And according to the to-be-measured optical fibers at different distances on the main interferometer, the beat frequency signal of the auxiliary interferometer with the closest optical delay is selected for compensation. And splicing the compensated reflected signals at different distances to obtain a distance domain reflected signal of the whole sensing optical fiber, thereby realizing phase noise compensation in the full range of the OFDR system. The OFDR full-range high-precision measurement is realized, and the OFDR full-range high-precision measurement device has the characteristics of simple structure, stable performance, low manufacturing cost and the like.

The invention relates to the technical field of electric forklifts and energy storage, and discloses an intelligent battery management system and prediction method based on optical fiber sensing, the system comprises a distributed optical fiber sensing network, a data acquisition and processing module, an intelligent analysis decision module, a battery management control module and a cloud platform interaction module; the method comprises the following steps: collecting a battery signal through a snakelike-spiral optical fiber network, reconstructing a temperature / strain field through noise reduction and filtering, extracting multi-modal features, inputting the multi-modal features into an LSTM model to predict thermal runaway, generating a risk level in combination with an improved equation, dynamically adjusting charging, discharging and heat dissipation strategies, and realizing three-dimensional visual monitoring through a cloud platform. According to the invention, high-precision distributed monitoring of the temperature / strain field of the battery pack is realized through the BOTDR optical fiber sensing network, the LSTM prediction model is constructed by fusing multi-physical field characteristics, and thermal runaway is warned in advance. The improved algorithm reduces the false alarm rate, charging and discharging parameters are dynamically adjusted to prolong the service life of the battery, and a three-dimensional visual platform improves the operation and maintenance efficiency.

The invention relates to the field of pipeline engineering and intelligent detection, and discloses a buried PE pipeline corrosion monitoring and evaluating system which comprises a distributed optical fiber sensor module which is used for being installed on the outer wall of a buried PE pipeline, collecting pipeline temperature and stress change data and sensing the pipeline corrosion condition through optical fiber sensing signals; the invention further discloses a buried PE pipeline corrosion monitoring and evaluating method which comprises the following steps: S1, installing the distributed optical fiber sensors on the outer wall of the buried PE pipeline, and collecting temperature and stress change data of the pipeline in real time; through a distributed optical fiber sensor and an intelligent algorithm, real-time monitoring and accurate corrosion evaluation of the buried PE pipeline are realized, the monitoring efficiency is remarkably improved, a signal acquisition system based on the Internet of Things reduces the construction and maintenance cost, and meanwhile, the flexibility and data security of the system are enhanced; the multi-modal data fusion and deep learning technology optimizes corrosion risk prediction, and reduces misinformation and missing report.

The invention relates to the field of highway safety monitoring, and discloses a highway subgrade safety monitoring system and a risk identification method, and the system comprises a distributed optical fiber sensing subsystem and a video image capturing equipment subsystem which are respectively connected with a rear-end server; the distributed optical fiber sensing subsystem comprises distributed Rayleigh scattering optical fibers and / or distributed Brillouin scattering optical fibers which are arranged on a highway subgrade according to risk levels and is used for collecting dynamic information related to the highway subgrade, and the dynamic information represents environment and state changes of the highway subgrade; the video image capture device subsystem comprises a plurality of AI video image capture devices; and after receiving the dynamic information, the back-end server inputs the dynamic information into a preset calculation model to obtain a deformation index parameter output by the preset calculation model, determines a response level of the AI video image capture device according to the deformation index parameter, and configures an operation parameter of the AI video image capture device based on the response level. According to the system, real-time, accurate and comprehensive monitoring of a road is realized through cooperation of the distributed optical fiber, the AI video image capturing equipment and the back-end server.

The invention provides a vortex aircraft detection signal processing method and system based on optical fiber sensing. The method comprises the following steps: firstly, acquiring an original micro-vibration signal; secondly, performing environment self-adaptive cooperative processing on the original micro-vibration signal to generate a self-adaptive micro-vibration signal; converting the generated self-adaptive micro-vibration signal into a spatio-temporal evolution sequence based on eddy current physical characteristics; then analyzing the spatio-temporal evolution sequence to output a type discrimination result of the vortex aircraft; and finally, generating a customized detection report based on the type discrimination result. According to the technical scheme provided by the invention, the detection and identification capability of a low-altitude low-speed small target in a complex environment is improved, and reliable detection and identification of the vortex aircraft in the complex environment are also realized.

The invention belongs to the technical field of distributed optical fiber sensing, and discloses a distributed optical fiber sensing pipeline leakage identification method. Comprising the following steps that 1, a distributed optical fiber sensor is adopted to collect vibration information of water supply pipeline leakage to serve as an original data set, and original data is a one-dimensional time sequence signal; 2, preprocessing the original data, and converting the preprocessed signal into a spectrogram; step 3, an improved MobileNetV3-large network model is constructed, and the step 3 is that the improved MobileNetV3-large network model is And step 4, performing leakage aperture identification by using the trained network model. According to the method, the accuracy of distributed optical fiber sensing water supply pipeline leakage identification can be improved while the calculated amount is small, and the identification efficiency is improved.

The invention discloses an optical fiber line fault detection method and system, and the method comprises the steps: employing broadband light sources at the two ends of an optical fiber in an optical fiber network at the same time, and carrying out the frequency coding of a signal in the broadband light sources, and obtaining an optical signal; collecting optical fiber sensing data; performing multi-mode acquisition on the optical signal to obtain multi-mode optical signal data; preprocessing the multi-mode optical signal data and the optical fiber sensing data to obtain clear signal data; analyzing and fusing the clear signal data to obtain fused data; and inputting the fusion data into a pre-purchased fault identification model, and outputting a fault type. According to the method, through technologies of multi-modal data fusion, high-frequency signal extraction, physical model constraint, feature compression and the like, the problems that the complex fault recognition capability is insufficient and the stability of the model is weakened by environmental interference are effectively solved, and the precision, robustness and generalization capability of optical fiber line fault detection are remarkably improved.

The invention belongs to the technical field of optical fiber sensing analysis, and particularly relates to an intelligent self-adaptive environment multi-parameter passive optical fiber sensing analysis system which comprises an optical fiber sensor array module, an intelligent signal processing module, a self-adaptive adjustment control module, a comprehensive monitoring alarm module and a remote control center. By fusing an optical fiber sensing technology and an intelligent algorithm, real-time monitoring and accurate analysis of environmental changes are realized, and the system has the advantages of high transmission rate and electromagnetic interference resistance, has wide application prospects in the fields of environmental monitoring, industrial production control and the like, and is suitable for popularization and application. The environment management and control difficulty in the detection period is analyzed through the environment management and control analysis module, and the inspection performance of the optical fiber sensor array module in the detection period is analyzed through the inspection influence analysis module when the environment control high-difficulty signal is generated, so that whether the influence caused by the inspection performance factor is eliminated or not is judged; management personnel can reasonably carry out follow-up management scheme planning, and the intelligent degree is high.

The invention provides a temperature self-compensating intrusive optical fiber pressure guide wire and an FFR wireless monitor, and belongs to the technical field of optical fiber sensing. Comprising a first hollow guide wire section, a second hollow guide wire section, a third hollow guide wire section and an FBG-FP cascade optical fiber sensor which are sequentially arranged, the first guide wire section is used for guiding the second guide wire section and the third guide wire section in a blood vessel; the second guide wire section and the third guide wire section are hollow and are communicated with each other; the FBG-FP cascade optical fiber sensor is arranged in the second guide wire section and extends towards the inner direction of the third guide wire section; the FBG-FP cascade optical fiber sensor comprises a multimode optical fiber, a hollow optical fiber and a single-mode optical fiber which are arranged in sequence, and the single-mode optical fiber is provided with a fiber bragg grating (FBG); the FBG-FP cascade optical fiber sensor is used for measuring temperature and strain signals in a blood vessel at the same time. The method is particularly suitable for parameter measurement of the area before and after the stenosis lesion in the blood vessel.

The invention discloses a swimming pool waste heat recovery system based on a phase change energy storage material, and belongs to the technical field of phase change energy storage technologies. The system comprises a phase change energy storage module which realizes efficient energy storage in a wide temperature range through phase change materials with different melting points; the heat exchange module adopts a bionic fractal spiral structure and an advanced surface treatment technology, so that the heat exchange area is obviously increased, and the fluid resistance is reduced; the intelligent hierarchical control module is used for realizing comprehensive intelligent management from millisecond-level real-time control to long-term optimization; the sensing network module is combined with optical fiber sensing and wireless sensing technologies and is used for providing high-precision and high-spatial-resolution omnibearing monitoring; the energy conveying module achieves efficient, reliable and low-noise fluid conveying through the integrated design of a magnetic suspension bearing and a permanent magnet synchronous motor. The auxiliary heating module integrates a solar heat collector and a CO2 heat pump, uses a phase change material as a heat buffer, and provides a flexible and efficient supplementary heat source when stored energy is insufficient.