2289 results about "Gas leak" patented technology

The invention relates to the technical field of the Internet of Things, and discloses a gas leakage monitoring method, device and equipment based on the Internet of Things and a storage medium, and the method comprises the steps: carrying out the data collection of a gas storage device, and obtaining an initial multi-dimensional data set; performing filtering and edge detection processing to obtain potential abnormal point data; inputting the potential abnormal point data into a mixed deep learning model for gas leakage detection to obtain initial leakage source position data and a leakage intensity value; executing multi-sensor cooperative accurate leakage positioning to obtain target leakage source position data; performing gas diffusion simulation to obtain gas concentration distribution data and risk indexes; based on the gas concentration distribution data and the risk index, dynamic reconstruction of the sensor network is carried out, an emergency response strategy and sensor network configuration information are output, and the method realizes whole-process management from leakage detection and source positioning to risk assessment and emergency response.

The invention discloses a chemical safety risk management and control method and system, and relates to the technical field of risk management and control. Comprising the following steps: acquiring climate data of each region in a chemical plant in real time to obtain microclimate information of different regions; deploying a gas sensor to monitor the gas concentration change and calculate the gas leakage rate; combining the climate data and the gas leakage rate, and adopting a computational fluid mechanics method to establish a gas diffusion prediction model; and in combination with the output of the diffusion prediction model, judging the gas leakage risk level of each region, setting different early warning thresholds according to the risk levels, and automatically triggering an early warning mechanism when the set thresholds are reached. The method not only considers climatic factors, but also combines the change of the factory environment, and can update the prediction result of the diffusion path and the potential dangerous area in real time.

Systems and methods presented herein generally relate to greenhouse gas emission management and, more particularly, to a greenhouse gas emission management workflow to perform greenhouse gas detection sensor placement or greenhouse gas leak detection. For example, the system and method enable improved gas sensor arrangements within an oil and gas worksite. In another example, the system and method enable the prediction of a location and a leak rate of a gas leak within an oil and gas production facility based on measurements collected by gas leak sensors disposed within the facility and prevailing wind information.

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 discloses a multi-modal thermal imager intelligent monitoring method based on image processing. The method comprises the following steps: S1, performing dual-band synchronous imaging; s2, carrying out cross-modal image registration; s3, multispectral image fusion: performing smoothing processing on the infrared and visible light images through anisotropic diffusion to obtain a main structure layer image, calculating to obtain an infrared and visible light detail layer image, and linearly combining the detail layer image through PCA principal component weight, and finally, combining the detail layer image and the main structure layer image according to the self-defined weight to obtain a final fusion image. And S4, gas leakage detection is carried out, so that gas leakage detection and early warning can be realized. According to the invention, a gas enhancement algorithm is adopted to realize real-time detection of leaked gas, interference of most background noise can be eliminated, and the real-time performance and reliability of the system are improved.

The invention discloses a box-type energy storage substation operation control method and system, a product and a medium. The method comprises the following steps: collecting gas concentration data in the box-type energy storage substation, comparing the gas concentration data with a preset threshold value, and judging whether gas leakage exists or not; if yes, recording related data, and detecting an insulation resistance value of the electrical contact component; based on the gas concentration data and the leakage time of the leakage area, judging whether a chemical reaction triggering condition is met or not; if yes, inert gas is sprayed to the leakage area; if the insulation resistance value is lower than a safety threshold value, electromagnetic isolation is carried out on the leakage area, and distribution of the electric load to the related energy storage unit is stopped; then, current is applied to the electrical contact component at a preset frequency, and an insulating property value is detected; when the insulating property is restored to within the safe range, the electrical load is redistributed to the leakage region. By implementing the technical scheme, the safety of the fault area after the insulation performance is reduced due to gas leakage in the operation process of the box-type energy storage substation is improved.

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 a gas leakage early warning method and system for a chemical industry park. The early warning method comprises the following steps: acquiring real-time temperature and pressure data of a reaction kettle area and a storage tank area; obtaining a historical leakage record of a pipeline joint, and determining a diffusion path prediction boundary; extracting a wind direction and a wind speed in a diffusion path prediction boundary, and determining space-time distribution characteristics; analyzing space-time distribution characteristics, determining an overlapping region and setting concentration monitoring nodes; identifying the concentration contribution ratio of the reaction kettle area diffusion characteristic and the storage tank area diffusion characteristic; integrating the operation data of the pipeline joint diffusion characteristics and the loading and unloading area diffusion characteristics, and determining a diffusion path deviation correction coefficient; combining the deviation correction coefficient with the humidity data of the peripheral diffusion characteristics of the cooling tower; and updating diffusion parameters of the separation tower area diffusion characteristics and the public engineering area diffusion characteristics according to a source intensity estimation result. According to the invention, accurate prediction and early warning of gas diffusion in a complex chemical device area are realized, and the safety management level is improved.

The invention relates to the technical field of fuel gas safety, and discloses an intelligent fuel gas safety valve and a method for intelligently opening and closing the safety valve, and the intelligent fuel gas safety valve comprises a sensor unit which is configured to be installed near a fuel gas pipeline or fuel gas equipment; the control unit is in communication connection with the sensor unit; the execution unit is in communication connection with the control unit; the communication unit is in communication connection with the control unit; and the standby power supply is used for providing emergency power for the intelligent gas safety valve when the main power supply fails or is powered off. The concentration, the pressure, the temperature and the flow of the fuel gas are monitored in real time through the sensor unit, the system can quickly send out an instruction for closing the valve when detecting abnormal conditions (such as gas leakage and too high or too low pressure), and accidents such as fire disasters or explosions caused by fuel gas leakage are effectively prevented. The system monitors a plurality of key parameters of the gas system through a plurality of sensors in a combined mode, and a multi-level safety guarantee mechanism is formed.

A method of operation of an unmanned autonomous vehicle includes autonomously maneuvering the unmanned autonomous vehicle about a facility, collecting gas concentration data using one or more sensors carried on or integrated with the unmanned autonomous vehicle, and monitoring the collected gas concentration data to detect a high concentration due to a gas leak. The method further includes, if a high concentration is detected, estimating a location of the gas leak and maneuvering the unmanned autonomous vehicle toward the estimated location of the gas leak.

The invention provides an air tightness self-adaptive control method and system for a wind measurement laser radar shell, and relates to the technical field of air tightness control, and the method comprises the steps: reconstructing the three-dimensional shape of a sealing surface of the wind measurement laser radar shell through a machine vision method, and building a mapping model of a multi-scale shape characteristic parameter and a gas leakage rate; obtaining the position coordinates of a sensitive area, and carrying out the dynamic pressure regulation of the sealing surface of the wind measurement laser radar housing according to the position coordinates of the sensitive area; the method comprises the following steps: acquiring air tightness control parameters under different working conditions, performing self-learning optimization on the air tightness control parameters to obtain an optimal control parameter matrix, storing the control parameter matrix to a controller, and predicting the air tightness performance of a wind measurement laser radar shell by adopting a pre-trained air tightness prediction model to obtain the air tightness performance of the wind measurement laser radar shell. And when the predicted gas leakage rate exceeds a preset early warning threshold value, outputting a gas tightness alarm signal, and starting a gas tightness self-adaptive control flow according to the stored optimal control parameter matrix.

The invention discloses a visual gas leakage detection system and method based on a laser spectrum, and relates to the technical field of gas detection visualization. According to the visual gas leakage detection system and method based on the laser spectrum, the method comprises the following steps that 1, gas monitoring data are collected and preprocessed; 2, extracting a characteristic spectrum from the gas monitoring data, obtaining a gas spectrum reduction value, and separating an overlapped absorption spectrum; 3, estimating the diffusion trajectory of the gas, and calculating a gas diffusion coefficient estimation value and a diffusion rate estimation value; outputting a gas concentration estimated value; 4, gas leakage source points are calculated, gas mass tracking is carried out, and different gas leakage sources are separated; and 5, generating a scatter diagram to display gas concentrations at different positions, and marking the position of a leakage source. The problem that a complex multi-gas environment cannot be recognized due to the fact that homogeneity and heterogeneity possibly exist in the same environment due to leakage of different types of gases in the prior art is solved.

The invention provides an inspection robot path optimization method and system based on dynamic obstacle avoidance, and the method comprises the steps: enabling an inspection robot to carry out the multi-layer convolution processing of gas and wind direction data through obtaining the turbulence data of a gas leakage source, the wind direction data of a meteorological station, and environment reflection feature data in real time, and generating a high-precision gas diffusion prediction map, meanwhile, a transparent obstacle optical contour and an unstructured obstacle geometric parameter are extracted from reflection data, and a three-dimensional space mapping relation with a gas diffusion diagram is established. On the basis of the mapping relation and the preset task priority, path control parameters are dynamically generated, global path node distribution is optimized, and the robot path is made to adapt to the composite risk environment of gas concentration sudden change and obstacle movement in real time. According to the invention, the dynamic obstacle avoidance precision and the safety response speed of the inspection robot path in a complex dangerous environment are improved.

The invention discloses an intelligent ground mobile high-precision gas leakage inspection and source tracking system, and relates to the technical field of gas pipe network leakage detection and leakage point positioning analysis. The system is mainly composed of a mobile inspection platform, a mid-infrared laser detection device, a three-dimensional anemograph, an inertial navigation module, a GIS system, a GNSS navigation positioning system, a wireless communication module and an intelligent detection comprehensive platform, and multi-source information fusion calculation, a dynamic adaptive analysis model and a maximum likelihood estimation method are combined. According to the intelligent gas leakage detection system, autonomous inspection can be achieved in a complex environment, abnormal gas component data can be processed in real time, detected gas space-time distribution information is transmitted to an intelligent comprehensive platform through a wireless communication module, data sharing and monitoring are completed, and efficient detection and accurate positioning of gas leakage are achieved. The method is suitable for gas leakage monitoring and component tracking in the fields of urban gas pipe networks, industrial parks and environmental protection, and the efficiency and precision of gas detection are remarkably improved.

The invention discloses a gas leakage point leakage detection system and method based on an e-dog, and belongs to the technical field of gas leakage detection. Through the autonomous navigation capability of the mobile platform module, the system can automatically avoid obstacles in a complex environment and inspect along a predetermined path, optimizes the inspection path in real time after finding a gas leakage point, improves the inspection efficiency, guarantees the high-density inspection of a key area, and the rapid movement and precise positioning capability of an e-dog, and improves the inspection efficiency. The gas leakage detection is quicker and more efficient, the risk that personnel enter a dangerous environment is reduced, the system has the functions of autonomous navigation, obstacle avoidance, remote control and the like, the intelligent level of detection is improved, the system is suitable for detection requirements of various complex environments and different types of gases, and through cooperative work of the gas detection module and the data acquisition and processing module, the detection efficiency is improved. The gas concentration data can be accurately acquired, the position of the leakage point can be judged, and the leakage point can be quickly and accurately positioned based on the combination of the GPS and the gas concentration data.

The invention discloses a chemical gas leakage detection management method and system, and relates to the technical field of chemical gas leakage detection, and the method comprises the following steps: determining a detection region and the gas type and characteristics of the detection region, collecting the environment data of the chemical detection region, constructing an environment parameter database, carrying out the preprocessing according to the collected environment data, and obtaining a detection result. The method comprises the following steps: analyzing environmental data influencing gas leakage detection to obtain an environmental data analysis sequence table, configuring detection equipment according to the environmental data analysis sequence table, establishing a data acquisition system and an anomaly detection mechanism, and collecting detection data and identifying anomaly detection data in the detection data by utilizing the detection equipment. The gas concentration in the environment is monitored in real time, abnormal conditions are rapidly detected, an alarm mechanism is triggered, a leakage source is found and controlled in time, the emission amount of harmful gas is reduced, the time difference from leakage occurrence to detection is shortened, and safety accidents such as fire disasters and explosions are effectively prevented.

The invention discloses a gas cylinder storage leakage point positioning detection method and system, and the method comprises the steps: building a gas cylinder leakage model under the conditions of no wind and wind, simulating a leakage process through a gas turbulence diffusion model, and introducing a sensor array to detect a gas leakage point; an adaptive filtering algorithm AF is introduced to carry out noise removal on data detected by the sensor array; extracting time difference information hidden in a gas sensor signal by using continuous wavelet transform (CWT) and a modulus maximum value method, judging the position of an optimal leakage point, and obtaining positioning information of a certain time point; a window function is introduced into a Kalman filtering algorithm, multiple sets of positioning information at different time points are obtained through processing of the improved Kalman filtering algorithm, interference of measurement invalid signals not in the range of the window function is filtered out, and the optimal positioning point is estimated. Compared with the prior art, the sensor array is introduced to realize leakage detection and positioning, a window function of a related time point is introduced into Kalman filtering, and the detection accuracy is effectively improved.

The invention relates to the technical field of gas leakage traceability positioning, in particular to a dangerous gas leakage traceability positioning method and system based on artificial intelligence, and the method comprises the steps: data collection: collecting environment parameters and gas concentration data from fixed and mobile sensors, and deploying the fixed sensors at key nodes to monitor gas diffusion; the mobile sensor is carried on the inspection robot or the unmanned aerial vehicle to dynamically fill the dead zone of the fixed sensor; preprocessing the data, and performing denoising, normalization and feature enhancement on the data; feature extraction and selection: extracting key features by using a machine learning algorithm; model training: training a deep neural network model to predict a leakage source position; monitoring and triggering: monitoring data and triggering traceability positioning when the data is abnormal; accurate positioning is carried out, and a leakage source is positioned by using the model and real-time data; intelligent decision making is achieved, and emergency response suggestions and optimization schemes are provided.

The invention discloses a gas leakage source positioning system based on multispectral imaging, which comprises a gas leakage positioning supervision platform, and the gas leakage positioning supervision platform is in communication connection with a holder data acquisition unit, a gas leakage centering analysis unit, a gas data comprehensive processing unit and an early warning information linkage unit. According to the invention, the accurate position of the leakage source is positioned and calculated by realizing omnibearing scanning of the target area and comparing and converting the parallax among the spectral imaging display and the value of the overlapping area, and the positioning result is fed back on the user interface for display, so that the accuracy and environmental adaptability of gas leakage detection are improved, and the detection efficiency is improved. Rapid detection and accurate positioning of dangerous chemical gas leakage can be realized, the reliability of positioning a leakage source is improved, and the emergency response capability of a petrochemical park is effectively improved.

The invention relates to the technical field of dangerous goods storage, and discloses a data twinborn early warning system and method for a dangerous goods storage area. The model establishing module is configured to establish a data twinborn model of the storage area according to the image information; the acquisition module is configured to acquire the environment information and the dangerous goods information of the storage area and display the information on the data twinborn model; the environment evaluation module is configured to obtain an environment evaluation value according to the temperature information and the humidity information and adjust the environment evaluation value according to the change value amplitude; the dangerous goods evaluation module is configured to obtain a dangerous goods evaluation value according to the complete state of the dangerous goods and adjust the dangerous goods evaluation value according to the gas leakage information; and the early warning module is configured to judge the early warning level of the storage area according to the comprehensive evaluation value and perform early warning. Storage of dangerous goods is monitored in multiple aspects, and the safety of storage materials is effectively evaluated.

A gas leak detection system that combines sensor units having an array of sensors that detect natural gas and the volatile organic compounds and variable atmospheric conditions that confound existing gas leak detection methods, a specially designed sensor housing that limits the variability of those atmospheric conditions, and a machine learning-enabled process that uses the wide array of sensor data to differentiate between natural gas leaks and other confounding factors. Multiple low-cost sensor units can be used to monitor gas concentrations at multiple locations across a site (e.g., a well pad or other oil or natural gas facility), enabling the gas leak detection system to model gas leak emission rates in two- or three-dimensional space to reveal the most likely origin of the gas leak.

A gas leakage detection apparatus may include a movement control unit that controls a movement of a moving object on which a gas sensor is mounted. The gas leakage detection apparatus may include an acquisition unit that acquires a measurement result of target gas that is obtained by a measurement by the gas sensor while the moving object is moving over a target area, and a response time from a start of a measurement of the gas sensor until an output of the measurement result. The gas leakage detection apparatus may include a detection unit that detects a leakage of the target gas in the target area based on the measurement result and the response time. The detection unit may detect the leakage of the target gas in the target area based on the measurement result and location information of the moving object, to identify a gas leakage spot.

The invention relates to a pressure-sensitive material and an insulating gas leakage identification method based on the pressure-sensitive material, and the visual identification method comprises the following steps: a pressure-sensitive material is applied to the surface of inflation equipment using insulating gas (sulfur hexafluoride or a sulfur hexafluoride mixture), and the pressure-sensitive material has set toughness and ductility and changes color after deformation; when the pressure sensitive material bulges from the surface of the inflation equipment and changes color, leakage of the insulating gas is visually found, and treatment is carried out immediately. The pressure-sensitive material comprises the following components: an adhesive material, a foaming material, a piezochromic material and a forming agent, the mass ratio of the adhesive material is 70%-80%; the mass ratio of the pressure color-changing material is 8-12%; the foaming material is not less than 5% of the total mass. The leakage point can be found timely and visually, sulfur hexafluoride can be prevented from leaking into the atmosphere, and the situation that greenhouse effect gas sulfur hexafluoride is discharged into the atmosphere to cause harm to the environment is avoided.

The invention discloses a pollution source dynamic tracing method and equipment for industrial park hidden gas leakage. Comprising the following steps: acquiring meteorological monitoring data at each observation point through fixed monitoring equipment and / or mobile monitoring equipment; correcting the coordinates of the observation points; predicting a first gas pollutant predicted concentration corresponding to each observation point after coordinate correction according to a Gaussian plume diffusion model; inputting the first gas pollutant predicted concentration and meteorological monitoring data into a CatBoost model to obtain a second gas pollutant predicted concentration; taking the difference between the actual gas pollutant concentration at each observation point and the second gas pollutant predicted concentration as a target function, and solving the target function to obtain the pollutant source intensity and the source position; completing one iteration; and setting the observation point near the current predicted pollutant source position, and so on, and obtaining the final pollutant source intensity and source position after n iterations.

The invention relates to the technical field of gas leakage detection, in particular to a high-pressure storage tank hydrogen leakage diffusion analysis method which comprises the steps that physical characteristics of hydrogen and interaction between the hydrogen and the environment can be accurately captured by building a physical model, and diffusion processes in different leakage scenes are simulated; the sensors are deployed to monitor key index parameters in real time, so that the real-time performance and reliability of data are ensured, potential leakage events can be quickly responded, and the possibility and consequences of accidents are reduced; by establishing a mapping relation between real-time monitoring data and physical model parameters, the model parameters can be dynamically adjusted according to the real-time data, and an output result is optimized; through quantitative evaluation and risk level classification, corresponding risk early warning signals are generated, potential safety hazards can be found in time, and necessary emergency response measures can be taken. The device is used for solving the technical problems of high-pressure storage tank hydrogen leakage diffusion simulation and real-time monitoring and early warning.

The invention belongs to the technical field of aircraft oil leakage monitoring, and relates to an aircraft oil leakage detection method based on a high-sensitivity mass spectrometry technology, and the method comprises the steps: obtaining a time-resolved mass spectrogram of aviation kerosene molecules in a sample testing stage, and storing the time-resolved mass spectrogram in a database; then oil gas molecules are captured at leakage-prone points of an aircraft pipeline system through a gas collection probe, the captured oil gas molecules are transmitted to an ion source end of a proton transfer reaction mass spectrometer through a negative pressure transmission system to be ionized to generate ions, and the ions are analyzed by a mass analysis system to obtain a mass spectrum; comparing the mass spectrogram obtained by analysis with a time-resolved mass spectrogram in a database, and judging whether leakage occurs or not; based on the method, the problems of insufficient anti-interference capability, difficulty in sample collection and the like of a high-sensitivity mass spectrum oil gas leak detection method can be solved in a targeted manner, and the functions of environmental interference suppression, efficient collection of oil gas molecules, improvement of spatial scanning resolution and the like can be realized at the same time.

A method for locating and mitigating a gas leak includes receiving gas leak sensory data from one or more gas leak detection sensors disposed on a gas-handling system and further receiving environmental conditions data. The method further includes dispatching an unmanned aerial vehicle (UAV) to a location upon detecting a gas leak using the one or more gas leak detection sensors and collecting one or more visual images of the gas-handling system using the UAV once it has reached the location. The method further includes determining, using the one or more visual images, the gas leak sensory data, and the environmental conditions data, a gas leak location and identifying components of the gas-handling system impacted by the gas leak given the gas leak location. The method further includes determining a mitigation action and resolving the gas leak by applying the mitigation action.

The invention provides an alkane gas leakage real-time identification and positioning method and system based on deep learning and a medium. The method comprises the following steps: acquiring an infrared image and a visible light image; performing rapid registration based on the imaging area and view field offset correction to obtain a registered visible light image; performing gas target detection according to the infrared image; performing pseudo-color conversion according to the detected gas target and gas concentration; and fusing the pseudo color to the registered visible light image. Gas detected in an infrared view field is subjected to pseudo-color fusion in a visible light view field, and finally plug flow output is performed. According to the invention, the deep learning detection algorithm and the dual-light rapid registration algorithm are combined to solve the alkane gas leakage detection task, and compared with the existing artificial observation alkane gas leakage detection method, the detection error caused by limited artificial observation is reduced, the gas leakage detection speed is greatly accelerated, and the safety and reliability are better.

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 present invention pertains to an enclosure for a refrigerant gas leak detection sensor, comprising a top part, a bottom part and a PCBA with a sensing element. Preferably, the enclosure is made of plastic. A gasket is provided between the sensing element and the bottom part. The invention also pertains to a refrigerant gas leak detection sensor with an enclosure.