4608 results about "Gas pipeline" patented technology

The invention provides a gas leakage time-space correlation early warning method and system based on multi-modal data fusion, and relates to the technical field of data processing, and the method comprises the steps: collecting real-time concentration data and a historical leakage accident database through an NB-IoT combustible gas sensor network disposed at a key node of a gas pipe network; according to the real-time concentration data and a historical leakage accident database, a UTM projection coordinate system is adopted to carry out registration on geographic space data, a three-dimensional space mapping model of a pipe network topological structure is established, timestamp alignment is carried out on all dynamic monitoring data streams through an NTP clock synchronization protocol, and a time-space correlation standardized data set is formed. According to the invention, full-chain intelligent management of the gas leakage risk from sensing, prediction to disposal is realized.

The invention discloses a gas pipe network fault positioning method based on a space-time diagram neural network, and the method employs an edge-cloud collaborative architecture, and achieves the precise detection of leakage points through simulation data generation, multi-modal perception, dynamic space-time modeling and hierarchical positioning. Firstly, simulation modeling is conducted on a pipe network, a multi-working-condition leakage data set is generated, and monitoring point layout is optimized through fuzzy clustering; a multi-modal sensing unit and a lightweight anomaly detection module are deployed at an edge end to realize coarse-grained anomaly detection and data hierarchical transmission; the cloud constructs a dynamic space-time diagram neural network, integrates a pipe network topological structure, multi-source time sequence data and physical constraints, and realizes high-precision positioning of leakage points through a hierarchical positioning strategy; and finally, realizing online evolution of the model through elastic weight solidification and hierarchical parameter updating. According to the method, the space-time diagram neural network and the physical characteristics of the pipe network are deeply fused, and the problems that space-time coupling features are difficult to extract and physical constraints are missing in complex pipe network fault positioning are solved.

The invention provides an urban gas pipeline micro-leakage early warning method and system, and relates to the technical field of data processing, and the method comprises the steps: employing a fuzzy analytic hierarchy process to calculate a dynamic risk index based on an evaluation matrix, and triggering the three-stage linkage alarm of an audible and visual alarm, a mobile terminal and an emergency platform when the index exceeds a threshold value; for three-level linkage alarm, a mobile robot is dispatched, a target area is navigated based on thermodynamic diagram positioning and reference coordinates, gas concentration is remeasured through a methane laser detector, a pipeline surface temperature field is scanned in combination with infrared thermal imaging, and a verification result and correction data are bound through a block chain evidence storage technology. And a tamper-resistant full-link evidence chain is formed. According to the invention, through cooperation of early warning and calculation, full-process automation of gas pipeline monitoring, early warning and emergency verification is realized, and the intelligent level of safety monitoring is improved.

The invention relates to the technical field of gas pipeline safety assessment, in particular to a gas pipeline safety assessment early warning system and method based on data analysis. The method comprises the following steps: collecting gas pressure data of a gas pipeline at multiple points at the same time, carrying out time-space synchronization processing to obtain aligned gas pressure data so as to construct a continuous gas pressure field of the pipeline, based on the gas pressure field, identifying the pressure distribution difference of the pipeline, estimating the transient flow velocity of the gas, continuously recording the transient flow velocity of the gas, and deducing the change of the flow velocity. Judging the deformation condition of the inner wall of the pipeline in combination with air pressure field data, positioning a deformation area, reconstructing a pipeline frame, analyzing deformation response, identifying a deformation type, identifying a corrosion evolution trend, performing safety evaluation, judging the gas circulation degree and performing physical safety evaluation. According to the invention, dynamic monitoring of the gas pipeline is realized, a data-driven safety management mode is promoted, the early warning capability of potential risks is improved, and a more intelligent safety assessment and early warning mechanism is formed.

The invention relates to the technical field of intelligent inspection, in particular to a pipeline inspection abnormal hidden danger intelligent identification system based on an unmanned aerial vehicle. According to the invention, the three-dimensional grid construction is carried out on the data collected by the unmanned aerial vehicle in the inspection process, so that the space division of the inspection area is realized, and the detection of the gas pipeline has higher precision. In combination with hyperspectral data analysis, measurement of methane concentration can be accurately mapped to space grid points, interference of environmental factors is reduced, and preliminary recognition accuracy of a leakage area is improved. On the basis of local concentration gradient calculation, through a data smoothing and diffusion optimization method, the boundary of a leakage area is clearer, interference of environmental noise is eliminated, meanwhile, the concentration value is dynamically adjusted, and the adaptive capacity to the change trend of leakage points is enhanced. By means of the construction of the virtual diffusion field and in combination with the space occupation condition of terrain obstacles, the analysis of the gas flow path is more accurate, and the problem of misjudgment caused by terrain complexity is solved.

The invention discloses a three-dimensional GIS (geographic information system) system for safety assessment of an urban gas pipeline internet of things. A gas pipe network monitoring and assessment system combining the internet of things, a mobile internet and BIM / GIS information is established. Firstly, an overall framework based on sensing, transmission, knowing and use of the internet of things is established; secondly, a front-end sensing system deployment scheme is established, a database system is built, and index data are collected and stored; thirdly, a gas leakage hazard model is constructed, and possible hazard consequences are evaluated; 4, a pipe network monitoring system application layer module is constructed, and underground space information management, safety analysis, prediction and early warning and an auxiliary decision making module are achieved; and establishing a gas pipe network risk identification module, a basic information checking module, a monitoring and explosion early warning module, a three-dimensional visualization module and an auxiliary decision-making module. The system monitors the operation condition of the gas pipe network in real time, analyzes the operation rule of the gas pipe network, evaluates the risk of the gas pipe network, predicts, early warns and decides in time, changes passive first-aid repair into active protection, and is high in monitoring stability, precision and efficiency.

The invention relates to the field of urban gas pipeline integrity management, and discloses a ground gas leakage diffusion simulation calculation method, which comprises the following steps of: initializing environmental parameters and leakage physical conditions, constructing a rotation alignment wind field calculation grid, and dividing dense and sparse time sequences by adopting a dynamic time step strategy; a leakage flow dynamic sequence is generated in combination with linear interpolation, diffusion coefficients are calculated based on atmospheric stability level sections, and an intermediate coefficient matrix is pre-calculated to optimize the calculation efficiency of a Gaussian puff model; an RK4 numerical solution is introduced to process an unsteady state diffusion process, and fusion of an analytical model and a numerical method is realized; and performing standard condition conversion, anomaly correction and structured storage on the concentration data to generate a multi-dimensional visualization result. According to the method, minute-level high-resolution grid leakage diffusion simulation is realized, leaked gas volume concentration distribution and diffusion trend are accurately output, and reliable technical support is provided for smart city operation, city gas safety management, real-time early warning and emergency decision making.

The invention relates to the technical field of urban public safety, in particular to an underground gas pipe network safety pre-warning system, which comprises an acquisition module, a monitoring module, a monitoring module and a control module, and is characterized in that the acquisition module is used for arranging sensing nodes at key positions of a gas pipeline body and a surrounding environment to form a distributed monitoring network; the method comprises the following steps: synchronously acquiring mechanical deformation, methane concentration and mechanical vibration data of a pipeline through a distributed monitoring network to obtain a multi-modal sensing data set; the fusion module is used for performing humidity and temperature interference correction on the methane concentration data in the multi-modal sensing data set to obtain corrected methane concentration data; and performing fusion processing on the mechanical deformation data, the mechanical vibration data and the corrected methane concentration data to obtain an initial pipeline safety state evaluation index. Through multi-source data fusion, environmental interference correction and spatial domain calibration, transmission and dynamic analysis are combined, and precise early warning and efficient linkage disposal of the safety state of the gas pipe network are achieved.

In order to overcome the defects in the prior art, the invention provides an urban gas pipeline risk assessment method based on a knowledge graph, and the method comprises the following steps: 1, collecting historical information of gas pipeline accidents, including detailed information of accident causes, types and consequences, and collecting images, videos and text reports of accident sites, needed information is identified and extracted, then multi-modal fusion is carried out to obtain a comprehensive feature vector, and an urban gas pipeline-risk source knowledge graph is established. And step 2, constructing an urban gas pipeline digital model. And step 3, acquiring related information of the running state of the urban gas pipeline in real time, and inputting the information into the urban gas pipeline-risk source knowledge graph for risk assessment. And for risk points which may form risks, marking and prompting the risk points on the urban gas pipeline digital model, and / or forming alarm information. Through the advanced knowledge graph technology, early warning and real-time response to gas pipeline accidents are achieved, and the overall emergency management efficiency and scientificity 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 fuel gas intelligent valve with point type laser methane sensors, and relates to the field of fuel gas intelligent valves, and the fuel gas intelligent valve comprises an equipment installation module which is used for installing three point type laser methane sensors and collecting interface methane concentration values; the data acquisition module is used for acquiring pipeline parameters and environment parameter data inside and outside the interface; the risk assessment module is used for calculating the methane concentration change rate according to the methane concentration value and assessing whether gas leakage exists at each interface; the fuel gas leakage positioning module is used for constructing a fuel gas leakage positioning model based on a neural network and acquiring the probability of the fuel gas leakage risk at each interface; the valve self-adjusting module is used for determining whether the gas leakage point is a leakage point or not according to the gas leakage risk probability; and the historical data analysis module is used for calculating the precision ratio, the recall rate and the F1-Score value by using the historical data and the field actual measurement result. The leakage risk of the gas pipeline is effectively diagnosed and positioned, and the opening degree of the valve is intelligently controlled.

The invention belongs to the technical field of material life prediction, and particularly relates to an X70 steel gas pipeline multi-working-condition life prediction method based on transfer learning. Aiming at the problem of low prediction precision caused by dependence on single working condition data and large distribution difference between laboratory and actual service environment data in a traditional life prediction method, the invention provides a cross-domain transfer learning framework. The method comprises the following steps: acquiring mechanical property data through slow strain tensile tests of different hydrogen doping ratios in a laboratory environment, and constructing a domain self-adaptive life prediction model in combination with multi-modal feature decoupling, dynamic distribution alignment and physical constraint fusion strategies. The method significantly reduces actual scene data requirements, realizes high-precision prediction of the residual life of the pipeline under multiple working conditions, is suitable for oil and gas pipeline health monitoring and hydrogen embrittlement risk assessment, and has the advantages of high efficiency, low cost and high reliability.

The utility model discloses an automatic closing valve for gas pipeline leakage and a self-closing valve thereof, and relates to the technical field of structural design of gas self-closing valves. According to the gas pipeline leakage automatic shut-off valve, a vent hole is formed in the middle of a shell, a leather film is connected to the edge of one side of the shell in a sealed mode, a connecting structure is arranged on the edge of the shell, a gas inlet is formed between the connecting structure and the leather film, and the connecting structure is connected with the inner wall of a gas pipeline in a sealed mode. According to the self-closing valve, a timer is arranged on a valve body, a closing device is arranged at the gas inlet end of the valve body, and a gas pipeline leakage automatic closing valve is arranged at the gas outlet end of the valve body. The problem that in the prior art, automatic closing of the gas pipeline can not be achieved when leakage happens to the gas pipeline, and use safety of gas is affected is solved. According to the gas pipeline leakage automatic closing valve and the self-closing valve thereof, when gas leakage occurs, the gas pipeline leakage automatic closing valve can be automatically closed. And through the closing device of the self-closing valve, the action of the closing valve is further ensured, and the effectiveness of leakage closing is ensured.

The invention provides an intelligent gas pipe network transformation method and system based on the supervision Internet of Things and a medium, and relates to the field of pipe network transformation, the method is executed by a gas company management platform of the intelligent gas pipe network transformation system based on the supervision Internet of Things, and the method comprises the following steps: through a gas company sensing network platform, from an intelligent gas equipment object platform, a gas supply network is established; acquiring gas monitoring data; acquiring historical fault data through the gas database, and determining transformation strategy parameters based on the historical fault data and the gas monitoring data; and on the basis of the transformation strategy parameters, generating a regulation and control instruction, and sending the regulation and control instruction to an intelligent gas equipment object platform through a gas company sensing network platform so as to regulate and control monitoring parameters of gas monitoring equipment of the intelligent gas equipment object platform. The use state of the gas pipeline can be accurately monitored in real time, so that the pipeline needing to be transformed can be found and effectively treated in time, and the overall safety performance of the gas pipeline is remarkably improved.

The invention discloses a standard volume-based mass spectrum signal calibration system and method, and belongs to the field of measurement, the standard volume-based mass spectrum signal calibration system comprises a standard flow generation system and a mass spectrum detection system.The standard flow generation system comprises a standard tank, a first valve, a fifth valve and a micro-leakage valve which are sequentially connected through a gas pipeline; a gas inlet pipeline, a film gauge and a first molecular pump set are connected to a gas pipeline connecting the first valve and the fifth valve in parallel, a second valve is installed on the gas inlet pipeline, and a fourth valve is installed at an inlet of the first molecular pump set. The mass spectrometry detection system comprises a vacuum chamber communicated with the micro-leakage valve through a gas pipeline, a mass spectrometer, a second molecular pump set and a full-scale gauge are connected to the vacuum chamber, and a gate valve is installed at an inlet of the second molecular pump set. The gas release rate can be calculated and continuously adjusted on the premise that a leak hole is not needed, and the problems that in the prior art, a standard leak hole is limited in application range, low-flux measurement is inaccurate, the nominal leak rate is prone to drifting, and cost is high are solved.

The invention provides a multi-scene fusion perception system and method of a humanoid robot olfaction sensor, and relates to the technical field of intelligent sensors, and the system comprises an olfaction perception optimization module which is used for obtaining an olfaction perception optimization network; the first matrix module is used for monitoring a gas pipeline to obtain a first matrix; the second matrix module is used for performing interference compensation according to a real-time environment; the third matrix module is used for correcting according to the state of the sensor; the leakage detection module is used for detecting pipeline leakage; and the suppression verification module is used for carrying out false alarm suppression verification on the pipeline leakage detection result to obtain a pipeline early warning signal. The gas leakage detection method and device can solve the technical problem that the gas leakage detection precision is limited due to the fact that the gas leakage detection device is prone to environmental interference and high in false alarm rate in the prior art, and can adjust the multi-node olfaction sensing network in real time through historical data, conduct multi-level correction on monitoring data and introduce false alarm suppression verification, thereby improving the detection accuracy of gas leakage. The accuracy of gas leakage detection in a multi-scene environment is improved.

The invention discloses a gas pipeline leakage detection method based on an unmanned aerial vehicle, and the method comprises the following steps: S1, controlling the unmanned aerial vehicle to fly along a preset pipeline inspection path, and synchronously collecting the following data: S2, carrying out the real-time fusion processing of the data collected in S1, and generating a leakage probability score; s3, when the leakage probability score exceeds a preset threshold value, controlling the unmanned aerial vehicle to hover and marking a leakage point coordinate; and S4, generating an evaluation report containing the leakage aperture, the risk level and the environmental parameters, and encrypting and transmitting the evaluation report to the emergency terminal through the hybrid network. The unmanned aerial vehicle is adopted to carry the laser methane sensor, the multispectral thermal imager and the directional microphone array to detect whether the gas pipeline leaks or not, so that the labor intensity of workers is reduced, and meanwhile, the large-scale pipe network detection time can be shortened by adopting multi-machine cooperative task allocation, so that the detection efficiency is improved.

The present disclosure provides a method and an Internet of Things (IOT) system for distributed energy pipeline natural gas transmission safety management, the method comprising: obtaining a safety management region, the safety management region is provided with one or more spot-check sites; determining, based on a preset cycle, whether a monitoring sequence of the one or more spot-check sites satisfies a first preset condition during a preset historical time period; in response to determining that a monitoring sequence of the one or more spot-check sites does not satisfy the first preset condition, maintaining a first monitoring instruction of the one or more spot-check sites; in response to determining that the monitoring sequence of the one or more spot-check sites satisfies the first preset condition, adjusting the first monitoring instruction based on the monitoring sequence and an inspection sequence in the preset historical time period, and sending a second monitoring instruction obtained after adjustment to a monitoring sensing and control platform; determining an abnormal probability of the one or more spot-check sites in a predetermined future time period based on the monitoring sequence, the inspection sequence, and an adjacency matrix of gas pipelines; and generating maintenance instructions based on the abnormal probability, sending the maintenance instructions to a maintenance sensing and control platform to deploy maintenance personnel.

The invention discloses an electric steam generator with a waste heat recovery device, and relates to the technical field of steam generators, the electric steam generator comprises a main body, a heating cavity is fixedly connected to the inner side of the main body, a plurality of electric heating pipes are fixedly connected to the inner side of the main body and located on the periphery of the heating cavity, and a recovery unit is arranged on the outer side of the main body. The upper side of the main body is fixedly connected with a first water inlet pipe, the right side of the main body is fixedly connected with a steam discharge pipe and a gas pipeline, the recovery unit comprises a fixing frame, and the fixing frame is fixedly connected to the outer side of the main body. According to the electric steam generator with the waste heat recovery device, the main body, the heating cavity, the electric heating pipe, the smoke conveying pipe, the heat exchange pipe and the recovery barrel are arranged, generated high-temperature smoke waste heat is conveniently recovered, stirring plates on the upper side and the lower side are conveniently controlled to rotate through a control rod, a second gear, a first gear, a motor and a fixing ring, water is stirred, and the heat exchange effect is improved.

The invention relates to the technical field of pipeline detection, and particularly discloses a corrosion analysis method and device for gas pipeline integrity management and a medium. The method comprises the following steps: determining a key corrosion risk position; acquiring pipeline state data of the key corrosion risk position; analyzing the pipeline state data based on a preset corrosion prediction model to generate a corrosion degree; determining the residual strength of the key corrosion risk position based on the corrosion degree and the pipeline attribute data; and evaluating the structural integrity of the key corrosion risk position based on the residual strength, and generating a corrosion analysis result. Through corrosion degree analysis and structural integrity analysis of a key corrosion risk position, fundamental conversion from static general detection to dynamic fine detection is realized, a real high-risk position in a current state can be actively identified, the number of unnecessary excavation verification times is greatly reduced, and the construction efficiency is improved. And the maintenance cost is obviously saved, and secondary damage to the pipeline due to excessive detection is avoided.

The invention discloses a gas pipeline operation risk dynamic evaluation system based on big data analysis, and relates to the technical field of gas pipeline safety monitoring, and the system comprises a multi-source data processing module, a feature extraction module, a local risk modeling module, a risk evolution prediction module and a dynamic early warning module. The multi-source data processing module is used for acquiring original multi-source time sequence data from a pressure sensor, a flow sensor, a temperature sensor, a geological monitoring device and a third-party construction disturbance data interface of a gas pipeline network, and performing time alignment, abnormity elimination, normalization and characteristic standardization processing on the data; a uniform input feature vector is formed; and the feature extraction module is used for decomposing the normalized time series data into a low-frequency trend component and a high-frequency residual signal by using discrete wavelet decomposition. The gas pipeline risk assessment system solves the problems of low gas pipeline risk assessment precision, insufficient risk propagation modeling and lack of dynamic early warning and emergency strategies in the prior art.

The invention provides an intelligent gas pipeline differential pressure safety monitoring Internet of Things system and method and a storage medium. The Internet of Things system comprises a gas company management platform and a plurality of other platforms. The method is executed by a gas company management platform and comprises the following steps: acquiring a pressure difference data matrix of a current gas pipe network; based on the pressure difference data matrix, determining an abnormity judgment result of the current gas pipe network; determining anomaly probability distribution based on the differential pressure data matrix in response to the existence of the anomaly; generating an operation instruction set based on the abnormal probability distribution; and based on the differential pressure data matrix, generating a voltage regulation instruction, the voltage regulation instruction being configured to control a voltage regulation device to perform voltage regulation. The method can also be operated after a computer instruction stored in a computer readable storage medium is read. According to the Internet of Things system and method, real-time and accurate monitoring and analysis of the pressure difference of the gas pipeline can be realized, and safe and stable operation of a gas pipeline network is ensured.

The invention discloses a high-entropy alloy silicon carbide nanofiber composite material and a preparation method and application thereof, a high-entropy alloy is loaded on silicon carbide nanofibers, compared with a carbon fiber material carrier, SiC fibers can form a compact SiO2 protective layer in a high-temperature aerobic environment, further oxidation failure of the internal structure can be prevented, and the high-entropy alloy silicon carbide nanofiber composite material is prepared. And meanwhile, SiC also has relatively high high-temperature stability and weather resistance, so that the high-entropy alloy silicon carbide nanofiber composite material can stably work in an extreme high-temperature oxidation environment (such as a spacecraft thermal protection system and an engine tail gas pipeline) of over 1000 DEG C, and perfectly adapts to a high-temperature wave-absorbing scene.

Provide are an IoT system, a method, and a storage medium for smart gas pipeline pressure difference safety monitoring. A gas company management platform of the IoT system is configured to: obtain a pressure difference data matrix of a current gas pipeline network from a gas equipment object platform; determine an abnormality judgment result for the current gas pipeline network based on the pressure difference data matrix; in response to determining that the abnormality judgment result indicates an abnormality, determine an abnormality probability distribution of the current gas pipeline network based on the pressure difference data matrix; generate an operation instruction set based on the abnormality probability distribution; generate a pressure adjustment instruction based on the pressure difference data matrix, and send the pressure adjustment instruction to the gas equipment object platform to control a pressure adjustment device to regulate an abnormal gas pipeline in the current gas pipeline network.

The invention discloses a gas pipeline leakage rapid detection method and system, and belongs to the technical field of computers. According to the technical scheme, the problem that the reliability of the sensor is reduced due to environmental interference is solved to a certain extent, and optimal utilization of the multi-modal data is ensured through dynamic weight distribution. The cross-modal feature fusion mechanism significantly improves the feature recognition precision in a complex leakage scene, and the modal collaboration degree parameter effectively eliminates abnormal data interference. The introduction of spatio-temporal evolution characteristics provides diffusion path prediction for emergency disposal, and forms a full-flow solution of coverage detection, positioning and prediction.

The invention provides an intelligent gas pipe network valve remote control supervision Internet of Things system and method, and relates to the field of intelligent gas control. The method is realized based on the Internet of Things system, and comprises the following steps: obtaining pipe network information and performance parameters of a control assembly, and uploading the performance parameters to a government safety supervision management platform; obtaining a parameter confirmation instruction, determining layout parameters, and uploading the layout parameters to a government safety supervision management platform; a layout confirmation instruction is obtained, and layout parameters are sent to a gas maintenance object platform; after the layout is completed, the regulation and control compensation amount of the control assembly is determined based on the correction period and uploaded to a government safety supervision management platform; and a correction confirmation instruction is obtained, the control assembly is corrected based on the regulation and control compensation amount, the control assembly is controlled to regulate and control the coverage valve based on the regulation and control parameter set in the correction period, a regulation and control gas data pair is obtained, and the regulation and control compensation amount is determined. The arrangement position of the control assembly can be reasonably determined, and the regulation and control deviation is accurately evaluated to ensure the remote control effectiveness of the valve.

The utility model discloses an overflowing cut-off gas cylinder valve which comprises a valve body, an upper cavity channel and a lower cavity channel which are divided by a valve seat are arranged in the valve body, a transverse gas outlet communicated with the upper cavity channel is formed in the side portion of the valve body, an overflowing cut-off mechanism is installed in the gas outlet, and the overflowing cut-off mechanism comprises a core seat connected with the gas outlet in a sealed mode. The core seat is provided with a through air outlet channel, a valve seat opening is formed in the air outlet channel, and a ball used for blocking the valve seat opening and a first spring keeping the ball moving towards the valve seat opening are installed in the air outlet channel in a clearance fit mode. The overflowing cut-off mechanism is installed at the gas outlet of the gas cylinder valve, when a gas using pipeline is abnormally damaged, the gas flow and the flow speed in the pipeline are suddenly increased, the gas flow with the flow speed and the flow suddenly increased pushes the ball to overcome the first spring to move towards the valve seat opening, the valve seat opening is blocked, and gas leakage is cut off.

The invention discloses a gas pipeline leakage source positioning method, and relates to the field of gas leakage detection. According to the method, acceleration signals and sound wave signals are collected through sensors arranged at detection points, peak value extraction is carried out in respective corresponding frequency domain complex spectrums through data preprocessing, and main frequency signals and frequency multiplication signals are obtained; distinguishing real leakage and interference signals according to the stable frequency integral multiple relation characteristic and time sequence consistency of the two signals; the phase difference is calculated by extracting the phase of the dominant frequency signal and the phase of the corresponding frequency multiplication signal, and the position of the leakage source relative to the detection point is calculated by combining the path sound velocity. The method can capture small distance differences, effectively improves the precision and robustness of leakage positioning, and is suitable for online leakage monitoring and diagnosis of gas or liquid medium pipelines.

The utility model discloses a jacket heat preservation flame arrester for high-oxygen VOCs (volatile organic compounds) to enter dry quenching, which belongs to the technical field of flame arresters and comprises two valve bodies respectively communicated with a gas pipeline for the VOCs to enter the dry quenching and a flame arresting screen arranged between the two valve bodies, a jacket capable of introducing steam to preserve heat is arranged between the two valve bodies, and the two valve bodies are communicated with a gas pipeline for the VOCs to enter the dry quenching. The jacket is arranged on the outer side of the fire-retardant screen; a jacket inlet communicated with a steam pipeline is formed in one side of the jacket, and a jacket outlet communicated with a drain pipeline is formed in the other side of the jacket. According to the utility model, the temperature around the fire-retardant screen can be ensured not to be lower than the crystallization temperature of naphthalene gas, so that the naphthalene gas in VOCs gas can smoothly pass through the fire arrester and then enters dry quenching for incineration, and the VOCs are really discharged without external emission.

The invention provides a pipeline impurity monitoring Internet of Things system and method based on an intelligent gas Internet of Things, and the system comprises a government safety supervision management platform, a government safety supervision sensing network platform, a government safety supervision object platform, a gas company sensing network platform, and a gas equipment object platform. The government safety supervision object platform comprises a gas company management platform, and the gas company management platform is configured to determine the impurity gathering degree of at least one gas pipeline based on pressure monitoring data and temperature monitoring data of the valve device; determining a temperature control adjustment parameter based on the impurity removal instruction and the impurity aggregation degree; and generating a temperature control instruction based on the confirmation parameter, and sending the temperature control instruction to the temperature control device. According to the invention, the adhesion condition of impurities in the gas pipeline can be accurately monitored in real time, so that the corrosion problem of the pipeline can be timely found and effectively treated, and the overall safety performance of the gas pipeline is further guaranteed.