874 results about "Gas leak" patented technology

The invention discloses an SF6 gas leakage detection method and system based on a photoacoustic spectrum analyzer, and the method comprises the steps: arranging a sampling end to collect an SF6 gas sample, and obtaining stable gas input through constant-current sampling and steady-state pretreatment; steady-state gas is guided into the photoacoustic spectrum analyzer, and resonance frequency stabilization and signal amplification output are achieved through the self-tuning unit; executing double-microphone differential detection and digital filtering processing, and outputting a stable SF6 detection signal with a high signal-to-noise ratio; performing time calibration, abnormity elimination and consistency processing on the detection signal to generate standardized detection data; inputting the standardized data to a Transform model, and performing inversion to generate an SF6 leakage source position and a diffusion path; and displaying an inversion result on a monitoring interface, triggering a sound-light alarm when the inversion result exceeds a limit, and uploading the inversion result to a cloud monitoring platform. According to the invention, the intelligent photoacoustic spectrum system combining photoacoustic-fluid steady-state control and self-tuning detection is constructed, so that high-sensitivity detection and accurate positioning of SF6 gas leakage are realized.

The invention relates to the technical field of gas leakage detection, and discloses an infrared imaging radiation correction method and system for gas leakage detection, and the method comprises the steps: obtaining the distribution data of dark current noise, and the mapping relation parameters of an image gray value and a radiation brightness value; acquiring infrared radiation of the gas leakage scene by using an infrared detector to obtain an original infrared image; based on the distribution data of the dark current noise, performing pixel-by-pixel compensation on the original infrared image to generate an infrared image after dark current correction; extracting the radiation intensity distribution of the infrared image after dark current correction, calibrating the radiation value of each pixel in the infrared image based on the mapping relation parameter between the image gray value and the absolute radiation brightness value, converting the image gray value into the absolute radiation brightness value, and generating the infrared image after radiation calibration; and outputting an infrared image after radiometric calibration for subsequent gas leakage area identification and feature analysis. According to the invention, a high-quality and quantifiable radiation quantification image can be output.

The invention relates to an industrial gas tank storage place early warning method and system. The method comprises the following steps: acquiring image time sequence data at least representing temperature field distribution of a target monitoring area, generating a temperature image sequence, determining area temperature change characteristics and tank body surface reflection characteristics in the area, and generating reflection area probability distribution of the target monitoring area to determine initial gas leakage probability data of the target monitoring area; generating baseline feature data at least representing background thermal field distribution of the target monitoring area; and performing association processing on the initial gas leakage probability data and the baseline feature data to generate fusion time sequence features and determine a gas leakage diffusion weight so as to correct the initial gas leakage probability data to obtain corrected gas leakage probability data. By adopting the method, the gas leakage probability can be accurately judged by comprehensively utilizing temperature field time sequence information, tank body surface reflection characteristics and background thermal field distribution characteristics under the condition of a complex background thermal field, so that early warning is realized.

The invention relates to the technical field of gas sensing detection, and discloses a gas detection method and system based on a quartz tuning fork enhanced photoacoustic spectrum. The method comprises the following steps: constructing a standardized continuous tuning fork signal data stream; dynamically segmenting the data stream based on the gas concentration interval, and extracting time domain and frequency domain features in parallel in each segment to form an initial feature vector; dynamically adjusting an anomaly judgment threshold according to the jump amplitude of the adjacent segment feature vectors, and scanning and screening out an effective analysis interval of a stable concentration state according to the anomaly judgment threshold; performing cross-domain coupling compensation on the feature vectors in the effective interval to generate enhanced feature vectors; and finally, performing reverse traceability reasoning through a gas leakage propagation model based on the enhanced feature vector, and outputting a leakage source position identifier. The device can adapt to a dynamically changing concentration field, and the reliability and traceability positioning capability of gas detection in a complex environment are improved.

The invention relates to the technical field of gas detection, and relates to an optimization method and system for SF6 gas detection in a multi-temperature environment, and the optimization method comprises the steps: obtaining dual-band infrared images of a scene to be detected at the same time, the dual-band infrared images comprising a detection band infrared image and a reference band infrared image; preprocessing the dual-band infrared image; performing registration processing on the preprocessed dual-band infrared image; performing differential operation on the registered dual-band infrared image to obtain a differential image; and determining a dynamic segmentation threshold according to the current environment temperature, and performing threshold segmentation on the differential image according to the dynamic segmentation threshold so as to identify the SF6 gas leakage area. According to the optimization method and the optimization system, the dynamic segmentation threshold value is determined according to the current environment temperature, the problem that the detection performance of a fixed threshold value is reduced due to background radiation changes at different environment temperatures can be solved, and stable and reliable detection sensitivity can be kept within a wide temperature range.

The invention discloses an acousto-optic combined detection and fusion positioning method and device for underground gas leakage, and belongs to the technical field of industrial safety monitoring. In order to solve the problems of high false alarm rate, insufficient positioning precision, poor dynamic environment adaptability and the like of a single sensor in the prior art, the invention provides a multi-modal signal space-time collaborative fusion technical scheme which specifically comprises an acousto-optic heterogeneous sensor, an integrated MEMS ultrasonic array and a tunable laser spectrum module. Microsecond-level synchronous acquisition of acousto-optic signals is realized through a GPS taming clock, and a cross-correlation time delay compensation model is designed to eliminate space-time mismatch errors. And designing a three-stage dynamic fusion framework: improving LMS adaptive filtering to suppress industrial noise, establishing a light intensity attenuation model in combination with dust environment concentration, carrying out multi-modal feature extraction of acousto-optic signals, carrying out signal preliminary fusion, and judging a gas leakage condition. And constructing an acousto-optic Bayesian joint probability model, and calculating the leakage posterior probability. And optimizing positioning parameters based on a double-Kalman filter group, predicting sound wave time delay by forward filtering, and correcting a light diffusion coefficient by backward filtering to realize three-dimensional coordinate solution. Temperature, humidity and dust concentration parameters are fused in real time, a sound velocity calculation model and a light intensity attenuation factor are corrected, and the robustness of complex working conditions is improved. According to the invention, the advantages of acousto-optic signals are combined, errors of various complex environmental factors are further fused and compensated, the overall error is greatly reduced, and the method has the characteristic of dynamic adaptation, and is very suitable for gas leakage detection and positioning in complex environments such as underground environments and the like.

The invention provides a chemical storage tank gas leakage monitoring system and a gas leakage positioning method. A leakage diffusion model in a chemical storage tank area is constructed; extracting chemical gas diffusion characteristics at each monitoring position according to the leakage diffusion model, and performing inversion calculation on the chemical gas leakage concentration of the chemical storage tank area to obtain different pre-estimated leakage source positions and pre-estimated leakage source intensities in the chemical storage tank area; extracting infrared absorption characteristics of chemical gas at each high-risk leakage point at different moments from an infrared image sequence at different high-risk leakage points in the chemical storage tank area, and performing spatial constraint on each estimated leakage source position to obtain a spatial constraint value of each estimated leakage source position; and performing positioning evaluation on each estimated leakage source position to obtain the positioning confidence of each estimated leakage source position. By adopting the scheme of the invention, the success rate of leakage source positioning search can be improved under the scene of early weak leakage of the chemical gas.

The invention relates to the technical field of detection sensors, in particular to dangerous chemical pipeline gas leakage detection protection equipment and a temporary protection method.The dangerous chemical pipeline gas leakage detection protection equipment comprises a supporting plate, the bottom side of the supporting plate is sequentially connected with an exhaust hopper, a gas storage cylinder and a gas inlet hopper, and an electrical sensor structure is installed in the gas storage cylinder; the electrical sensor is further provided with a jacking air inlet structure, a linkage pull-up structure and a protective spraying structure, the electrical sensor structure improves the detection accuracy and sensitivity through a unique electrode design and a gas flow guide mode, the jacking air inlet structure and the linkage pull-up structure cooperatively control air inlet and closing of the air storage cylinder, segmented detection is achieved, and the electrical sensor is protected; the protection spraying structure is used for plugging during leakage, the temporary protection method comprises the steps of detection, isolation, plugging, verification and marking, detection and temporary protection of dangerous chemical pipeline gas leakage are completed through equipment cooperation, the detection accuracy is improved, and the service life of a sensor is prolonged.

The invention discloses a method for detecting, positioning and classifying underwater gas leakage through multiple beams based on deep learning, and relates to the field of underwater acoustic detection and deep learning. And carrying out azimuth correction on the multi-beam data with attitude offset to obtain multi-beam data without attitude offset. And through operations of seabed detection, median filtering, morphological expansion and the like, a high-quality multi-beam sonar image is generated. And constructing a data set for training an instance segmentation model and a flux classification model. And performing gas plume detection and segmentation on the preprocessed sonar image, and outputting mask information. And extracting a target contour based on a mask, determining plume coordinates through minimum circumscribed rotating rectangle fitting, and calculating the position of a seabed leakage point in combination with a conversion factor. And selecting complete plume data near the position right below the sonar equipment, and classifying leakage flux levels based on plume morphological characteristics by adopting a flux classification model. Multi-beam sonar and a deep learning algorithm are integrated, and detection, positioning and classification of underwater gas leakage are realized.

The invention discloses a multi-modal deep reinforcement learning gas leakage decision optimization method based on optical flow, and the method comprises the steps: carrying out the constraint and correction based on a pixel motion field in combination with wind speed estimation, and obtaining an optical flow reconstruction wind field; based on plume probability distribution, combining with an image intensity and radiation transmission model, obtaining concentration field estimation, fusing gas concentration data and an optical flow reconstruction wind field, and forming full-field state description; establishing a convective diffusion model, predicting the concentration field at the next moment through the convective diffusion model based on the full-field state, establishing a convective diffusion model, and predicting the concentration field at the next moment through the convective diffusion model based on the full-field state. According to the technical scheme of the invention, the dynamic evolution precision of gas leakage can be effectively improved by introducing the wind field reconstruction method of the optical flow and the scatter-free constraint, the prediction stability is improved, the physical consistency of the wind field and the concentration distribution is ensured, and stronger data support is provided for emergency control.

The invention discloses a gas leakage detection imaging device and method based on a single photon detection technology, and belongs to the technical field of gas detection and imaging. Aiming at the limitation problems of the existing gas leakage detection technology in the aspects of sensitivity, response speed, space imaging capability and anti-interference capability, nanosecond modulation control and synchronous photon counting are realized by utilizing an FPGA (Field Programmable Gate Array) through a visual gas detection imaging device combining an SPAD (Single Program Amplifier) array detector and a WMS modulation-demodulation mechanism; and the second harmonic of the absorption signal is further extracted by combining digital phase-locked amplification, so that gas leakage three-dimensional imaging with high spatial resolution, ppb-level sensitivity, strong background suppression capability and high time response is realized. The system has the advantages of high detection sensitivity, real-time imaging capability with high spatial resolution, high background light interference resistance and high signal-to-noise ratio, the demodulation method is novel, and the modular design has multi-gas compatibility and system expansibility.

The invention belongs to the technical field of gas pipeline fault prediction, and discloses a pipe gallery gas pipeline defect identification method and system and an inspection robot. The method comprises the following steps: synchronously sensing multi-dimensional time sequence data of a pipe gallery gas pipeline, wherein the multi-dimensional time sequence data comprises gas pipeline time sequence data, combustible gas concentration time sequence data and environment time sequence data; performing structured processing and feature extraction on the multi-dimensional time series data, and outputting a multi-modal feature data set for defect identification and risk assessment; performing joint modeling based on the multi-modal feature data set to obtain a fusion interaction embedding vector, and identifying a coupling abnormal state with causal correlation or collaborative performance between the structural defect and the trace gas leakage based on the fusion interaction embedding vector; based on the fusion interaction embedding vector and the coupling abnormal state, the early defect type of the pipe gallery gas pipeline is recognized; the early-stage defect identification accuracy and response speed of the pipe gallery gas pipeline are remarkably improved.

The invention discloses a poisonous gas leakage diffusion range simulation prediction method, relates to the technical field of electric digital data processing, and can solve the problems that prediction precision and real-time performance are difficult to consider when the poisonous gas leakage diffusion range is simulated and predicted at the present stage; the method comprises the following steps: acquiring gas diffusion related data of a gas leakage area; constructing a humidity intensity correction term according to the gas diffusion related data; wherein the humidity intensity correction item is used for correcting the influence of the air humidity on the diffusion concentration of the toxic gas; according to gas diffusion related data, constructing a water-gas intermiscibility correction term; wherein the water-gas intermiscibility correction item is used for correcting the influence of the water area on the diffusion concentration of the toxic gas; according to the humidity intensity correction item, the water-gas intermiscibility correction item and a preset gas diffusion model, simulation prediction is conducted on the leakage diffusion range of the toxic gas, and a diffusion prediction result of the toxic gas is obtained.

The invention relates to the technical field of ring main unit engineering, in particular to a state evaluation method and system for a gas insulation environment-friendly ring main unit, and the method comprises the steps: obtaining space probe distribution coordinates and gas concentration data in the environment-friendly ring main unit, and generating a leakage gas three-dimensional concentration matrix according to the leakage gas three-dimensional concentration matrix; constructing a gas concentration distribution prediction model matched with the environment-friendly ring main unit, inputting the leakage gas three-dimensional concentration matrix and the geometric parameters of the cabinet body into the gas concentration distribution prediction model, and outputting to obtain predicted gas concentration distribution; generating a gas leakage behavior parameter, and generating an insulation failure probability and an electric ignition risk index; and generating an insulation performance evaluation index, and generating state evaluation of the environment-friendly ring main unit according to the insulation performance evaluation index. According to the method, the gas leakage behavior is accurately simulated, so that the insulation failure probability and the electric ignition risk index are quantified, and the accuracy of state evaluation of the ring main unit is greatly improved.

The invention relates to the technical field of leakage ultrasonic detection, and discloses SF6 gas leakage ultrasonic detection equipment for a GIS pipeline, which comprises a handheld mechanism, a leakage detection mechanism, a switching mechanism and a controller, and is characterized in that the leakage detection mechanism is arranged on the handheld mechanism and comprises a first sensor mounting position and a posture adjusting mechanism; the posture adjusting mechanism is configured to drive the sensor mounted on the first sensor mounting position to perform posture adjustment; the switching mechanism is arranged on the handheld mechanism and comprises a second sensor mounting position; the controller is arranged in the handheld mechanism and is electrically connected with the leak detection mechanism and the switching mechanism; the equipment is at least provided with the ultrasonic micro-leakage fine detection sensor and the ultrasonic global quick scanning sensor, the ultrasonic micro-leakage fine detection sensor and the ultrasonic global quick scanning sensor can be exchanged between the first sensor mounting position of the leakage detection mechanism and the second sensor mounting position of the switching mechanism through the switching mechanism, and the detection efficiency and accuracy are remarkably improved.

The invention relates to the technical field of natural gas leakage detection, and discloses a method, device and equipment for detecting gas leakage of a natural gas inflation arm and a storage medium, and the method for detecting gas leakage of the natural gas inflation arm comprises the steps: collecting a visible light image and an infrared light image of a pipeline connection area of the inflation arm; identifying the morphological characteristics of the first image to obtain a first morphological detection result; extracting a first region of which the temperature is lower than a preset threshold value in the second image, performing thresholding processing on the second image, calculating an area proportion of the first region relative to the second image to obtain first proportion data, and comparing the first proportion data with a preset proportion data range; if it is judged that the first form detection result is smog and the first proportion data is within a preset proportion data range, it is judged that gas leakage occurs in the inflation arm pipeline connection area, and a leakage warning prompt is given out. According to the technical scheme, whether gas leaks or not can be detected in time, an alarm prompt is given out, and the detection accuracy is improved.

The invention discloses an environment gas leakage intelligent detection method based on big data analysis. The method comprises the following steps: collecting monitoring data and constructing a sensor network space-time diagram fused with meteorological conditions; predicting the background concentration of each node by using a sequence decomposition attention model; calculating a concentration residual error and constructing a space-time residual error map; extracting an abnormal feature vector through a physical information enhanced graph attention network; calculating an abnormal score in combination with the normal mode memory bank and generating a leakage source probability distribution diagram; when the conditions are met, calling a computational fluid dynamics model to simulate a theoretical concentration field; and determining a leakage event through spatial correlation analysis. According to the invention, the false alarm rate of gas leakage detection in an open environment is obviously reduced, and the leakage source positioning precision is improved.

The invention discloses a fuel gas leakage detection system based on mid-infrared laser, relates to the technical field of fuel gas detection, and aims to solve the problems that a large-area region is difficult to cover quickly and only close-range detection can be carried out in an existing laser fuel gas leakage detection method. The gas leakage detection system comprises a laser emission module, an infrared imaging detector module and a data processing module, the laser emission module is used for emitting an intermediate infrared laser beam to a to-be-detected area; the infrared imaging detector module is used for collecting an infrared spectrum signal of the to-be-detected area in real time; the infrared spectrum transmitting module is used for transmitting the infrared spectrum signal to the data processing module; and the data processing module is used for processing the received infrared spectrum signal to obtain a gas leakage detection result of the to-be-detected area. The method is suitable for detecting gas leakage in a natural gas pipeline and a liquefied petroleum gas storage tank area.

The invention relates to a gas leakage monitoring system and method, computer equipment and a computer program, and the system comprises a pressure sensor which is disposed on the inner wall of a gas storage shaft, is in communication connection with a controller, and is used for detecting the gas pressure in the gas storage shaft; the gas sensors are arranged on the inner wall and the outer wall of the gas storage shaft, are in communication connection with the controller and are used for detecting the gas concentration inside the gas storage shaft and the gas concentration outside the gas storage shaft; the ultrasonic sensor is arranged on the inner wall of the gas storage shaft, is in communication connection with the controller and is used for detecting a sound wave signal generated by gas leakage; and the controller is used for judging whether gas leakage occurs in the gas storage shaft or not through a preset risk grade judgment model according to the gas pressure, the gas concentration and the sound wave signal. According to the utility model, the monitoring accuracy and sensitivity are improved, real-time monitoring and early warning can be realized, the leakage position can be accurately positioned, and the safety and reliability of the monitoring system are improved.

The invention belongs to the technical field of packer detection, and relates to a method for detecting the airtight sealing performance of a packer, and a device for detecting the airtight sealing performance of the packer comprises a pipeline unit, a bubble measuring unit, a leakage rate measuring unit, an air pressure detecting unit, a to-be-detected unit and a controller. Performing double-signal cross validation according to the obtained visual data and infrared data to obtain a bubble recognition result, and if the bubble recognition result meets a grade judgment condition, judging that the to-be-detected piece is at a V0 grade; and if the bubble identification result does not meet the grade judgment condition, executing a leakage rate measurement step. In the first aspect, during bubble detection, through double-signal cooperative cross validation of visual form verification and infrared signal positioning and targeted recognition of tiny bubbles through an enhanced linkage mode, the accuracy of effective bubble recognition is improved. On the second aspect, the volume of the measuring cylinder is coarsely adjusted and finely adjusted through cooperation of the macroscopic adjusting and controlling assembly and the microcosmic adjusting and controlling assembly, and the accuracy of calculating the gas leakage rate is improved.

The invention relates to the technical field of gas leakage monitoring and early warning, in particular to an intelligent gas leakage early warning and cut-off system based on multi-sensor fusion, which comprises an intelligent gas leakage management end, a multi-sensor sensing module, a leakage identification module, a leakage area initial determination module, an area progressive correction module, a cut-off simulation decision module and an early warning response end. The method adopts a data-level and feature-level two-level fusion algorithm, effectively reduces false alarms caused by sensor drift and environmental interference, is accurate in leakage identification, guarantees the positioning precision through multi-layer designs such as a physical model and geometric analysis, pays more attention to the physical effectiveness and operation and maintenance practicability of a positioning result, and improves the positioning accuracy. And a visual'leaked gas pipeline diagram 'is generated, operation and maintenance personnel can quickly lock a leakage area through a visual interface to carry out leakage cut-off management, layered cut-off, simulation rehearsal operation and preferential closing of a lowest-level valve are carried out for leakage cut-off, the influence range is reduced, and accident loss is reduced.

The invention discloses a wide-area gas traceability method and device based on multistage sensing asynchronous cooperative triggering, a medium and a product, and relates to the field of wide-area gas leakage traceability, and the method comprises the steps: carrying out the adaptive three-dimensional grid division of a to-be-detected region; environment background information is detected; smoke plume discovery is carried out by adopting a random walk strategy and introducing a weight avoidance mechanism; determining a threshold value of binary detection according to the mean value of the environment background noise, and carrying out binary calculation on the sampled data; determining a near-field region according to a binary calculation result; performing concentration tracking according to the near-field region, and performing near-field state evaluation in real time; adjusting the size of the near-field region according to an evaluation result; continuously judging whether to exit the concentration detection of the near-field region; when the concentration detection of the near-field area is quitted and switched to the far-field area, a binary detection cycle is entered; determining a concentration peak value according to the concentration detection data of all the near-field regions; according to the invention, efficient, accurate and low-cost pollution source positioning in a complex wide-area environment can be realized.

The invention relates to a gas leakage grading traceability system and method based on cooperation of a fixed monitoring network and a mobile robot. The system comprises a fixed sensing assembly, a mobile execution assembly and a cooperative control assembly. The fixed sensing assembly is composed of a sensor array arranged in a limited space and is used for monitoring a concentration field in real time; the mobile execution assembly is composed of an autonomous mobile robot carrying multiple types of sensors, and has navigation, obstacle avoidance and active sniffing capabilities. The cooperative control assembly comprises a data processing unit, a source item inversion unit and a task scheduling unit, and is used for processing monitoring data, carrying out leakage source coarse positioning based on a differential evolution Markov chain algorithm, and scheduling the robot to rapidly maneuver to a target area. Compared with the prior art, through a grading cooperation mechanism of fixed network coarse positioning and robot fine traceability, response speed and positioning precision are considered, and the problems of low gas leakage traceability efficiency and poor precision in a large-scale limited space are effectively solved.

The invention discloses a real-time data acquisition and analysis method in industrial intelligent manufacturing, and relates to the technical field of industrial automation and intelligent manufacturing, and the method comprises the following steps: air quality monitoring equipment carries out conventional detection on the concentration of harmful gas in the environment according to a pre-configured time sequence resolution, and obtains air quality parameter information in real time; according to the invention, the response sensitivity and intelligent identification capability of the air quality monitoring equipment to instantaneous high-concentration harmful gas leakage are improved, and the monitoring limitation of traditional fixed time sequence resolution is broken through. And through fusion of feature engineering and a machine learning model, accurate judgment of dynamic change of gas is realized. After the severe fluctuation state is identified, the system dynamically adjusts the sampling frequency and starts the cache, the concentration peak value is effectively captured, meanwhile, the storage pressure is relieved, the stability and the real-time performance of the system are enhanced, and the safety protection capability of the industrial environment is improved.

A vacuum leak detection system may comprise a test chamber unit having a test chamber gas inlet and a test chamber gas outlet, a gas detection unit having a gas detection gas inlet and a gas detection gas outlet, and a gas control unit connecting the test chamber gas inlet and the test chamber gas outlet to the gas detection gas inlet and the gas detection gas outlet, which is connected to the test chamber unit and to the gas detection unit, and which has separate gas line paths for optionally connecting the gas inlets and the gas outlets of the test chamber unit and the gas detection unit, wherein the gas control unit has a third gas inlet which is open towards the atmosphere and which can be connected to the test chamber gas inlet via a gas line path running through the gas control unit.

The invention discloses an ammonia gas leakage multi-sensor fusion automatic monitoring method and system, and the method comprises the steps: deploying a plurality of gas detection sensors in a monitoring region, synchronously collecting the ammonia gas concentration and environmental parameters, and forming a multi-source data set; carrying out noise filtering and drift correction by utilizing the edge computing node, and extracting spatial-temporal characteristics to identify concentration anomaly; determining a leakage source coordinate through a data fusion algorithm, simulating a diffusion path and a trend, and constructing a risk diffusion model; and finally, an emergency trigger signal is extracted, ventilation equipment and valve control are activated, and real-time linkage response is achieved. According to the method, data layer fusion and a risk diffusion model are combined, so that the high efficiency of accurate positioning and emergency response of a leakage source is ensured, the safety and reliability of harmful gas monitoring and control are remarkably improved, and a technical guarantee is provided for gas leakage risk management in a complex environment.

The invention relates to the technical field of gas leakage detection, and discloses a gas sensor-based gas leakage detection system and method. The system comprises a dynamic gas concentration acquisition module, a leakage feature extraction module, a risk area modeling module, a multi-mode verification module and a grading response control module. The acquisition module acquires multi-dimensional concentration data through a distributed sensor array and a self-adaptive sampling mechanism; the feature extraction module separates steady-state background and transient leakage features through spatial-temporal feature decomposition and generates feature vectors; the risk modeling module constructs a three-dimensional diffusion model, and outputs potential leakage point coordinates with confidence in combination with a hydrodynamic equation; the multi-modal verification module generates a fusion result through infrared spectrum and sound wave detection cross validation; and the grading response module is matched with the strategy library to dynamically generate a gradient control instruction. According to the system, accurate detection, positioning and graded response of gas leakage are realized, and the comprehensiveness of leakage monitoring and the pertinence of emergency treatment are improved.

The invention provides a gas leakage three-dimensional reconstruction method and system based on thermo-optical fusion, and relates to the technical field of three-dimensional reconstruction, and the method comprises the steps: extracting multi-scale features from a thermal radiation and visible light image sequence, constructing a space-time cause and effect graph based on mutual information fusion, and carrying out the directed message transmission to obtain enhanced node features; and after mapping to a continuous time-space domain, carrying out Fourier neural operator transformation to obtain a characteristic field as a condition to guide iterative denoising, and finally generating a three-dimensional space distribution model of gas leakage. According to the invention, the three-dimensional space distribution of gas leakage can be accurately reconstructed, and the precision and reliability of leakage monitoring are improved.

The invention relates to the technical field of image processing, and discloses a sulfur hexafluoride ring main unit gas leakage detection method and system based on thermal imaging, and the method comprises the steps: obtaining an infrared thermal imaging multispectral sequence image of a ring main unit; identifying a plurality of candidate regions of the multispectral sequence image, selecting a gas reference region, and calculating an average multispectral vector of the gas reference region as a gas reference spectrum; calculating the intra-group variance of each spectrum channel, and determining a weight vector and an angle threshold value; calculating a weighted spectral angle between the multispectral vector of the pixel point to be detected and the gas reference spectrum; judging the to-be-detected pixel point which simultaneously meets the following conditions as a gas leakage point: the weighted spectral angle is smaller than an angle threshold value, and the temperature of the to-be-detected pixel point is lower than a preset temperature threshold value; and generating a visual image of the gas leakage area according to all the judged gas leakage points. According to the invention, the anti-interference capability of detection is improved, and reliable identification of sulfur hexafluoride gas leakage can be realized under a complex background.

The invention is suitable for the field of engineering monitoring, and particularly provides a compressed air energy storage underground gas storage engineering work cave surrounding rock state monitoring system, which comprises a distributed sensing module, which is used for synchronously acquiring multi-source heterogeneous data of surrounding rock and is integrated with a fatigue damage feature extraction unit and a gas leakage source positioning unit; the system further comprises a multi-field coupling data processing module which is used for adjusting a dynamic early warning threshold value based on the operation stage of a target work cave, fusing multi-source heterogeneous data through an improved Kalman filtering algorithm, and correcting error measurement data through a verification model. The system further comprises a multi-model fusion prediction and early warning module, a model dynamic switching unit and an early warning regulation and control linkage unit are built in the multi-model fusion prediction and early warning module, and the model dynamic switching unit is used for self-adaptive switching between the LSTM model and the ELM model; and the early warning regulation and control linkage unit controls the gas storage control system to execute self-adaptive regulation and control of inflation and deflation based on the graded early warning signal. According to the method, the full-life-cycle safety and the risk disposal efficiency of the compressed air energy storage underground gas storage engineering work hole are remarkably improved.