Gas Leak Detection Research Articles

Unsupervised gas pipeline network leakage detection method based on improved graph deviation network

Historical data has shown that the natural gas pipeline network, as a critical urban lifeline system, is susceptible to disasters such as earthquakes resulting in leakage. Graph neural network modeling provides frontier rapid detection solutions for pipeline leakage; however, the challenges of collecting gas network anomaly data for training limit the precision and robustness of current model. This research proposes an unsupervised gas leakage detection and localization method based on a contained preprocessing process, with a graph deviation model that combines a structural learning approach with a graph neural network to model the spatial dependence of the sensors based on an attention mechanism, and variational inference models the posterior distributions of the hyper-parameters to optimize the model and improve the model precision. Meanwhile, in the preprocessing stage, the automatic optimization strategy of Northern Goshawk Optimization (NGO) for the best parameters K and ɑ in the Variable Mode Decomposition (VMD) efficiently extracts the valid signals and ensures that the model gives full play to the detection and localization effectiveness. The gas pipeline network dataset constructed by Pipeline Studio was used for comparing the performance of the model in this study with other frontier models. The results demonstrate that the model in this research has competitive detection Precision (93.31%), Recall (70.82%), and F1-score (0.81), and the posterior distribution of the model parameters strengthens the gas leakage localization precision, which provides a comprehensive solution for subsequent decision-making and reduces the hidden hazard of leakage effectively.

Rancang Bangun Purwarupa Simulasi Sistem Keamanan Rumah Berbasis Internet of Things

The use of information technology has spread to all fields, for example in the field of security using the Internet of Things technology. One of the places that need to be given security is the home, so that in this study prototypes of home security systems using the Internet of Things have been made with the aim of providing information to homeowners in the event of infiltration through windows or doors, gas leaks and fires. The tools used are Arduino Mega 2560 as a microcontroller, gas sensor, fire sensor, magnetic switch sensor, RFID, keypad, and selenoid. The home security system is made so that homeowners can control the condition of the home. The results of this study are that the home security systems that are made can run well and can be integrated with home security information systems. Sensors can detect gas leaks, fires, and doors or windows open when the security system is active. Homeowners can only turn off the home security system and unlock the door by using RFID tags that have registered IDs and correct passwords. Home security systems can also turn on alarms and send notifications to homeowners, fire stations and police stations in the event of a fire, gas leak or window or door that is opened when the security system is active.

Modelling of Gas Leakage Detector with Safety System

Abstract: Leaking of gas is the major problem with industrial sector, domestic areas and vehicles run by LPG gas. Many accidents occur in day-to-day life like explosion because of gas leakage. If gas leakage is not detected earlier then major harm is caused. Due to leakage of LPG gas, it produces hazardous and toxic impact for living things.[1] LPG and natural gas is highly combustible and can burn even at some distance from the source of outflow. The main aim of this project is to present the detection of leakage, alert the danger to people and on the exhaust fan to throw out the gas to prevent from explosion. The gas will be detected by using MQ5 gas sensor. It will immediately turn on the buzzer and exhaust fan and also off the all of the lights, fans of the house for safety, when the sensor detect any gas leakage. This system is controlled by Arduino platform

Sulfur hexafluoride gas response characteristics of hollow-core fiber based spectral absorption sensor

SF6 gas is a greenhouse gas that is harmful to the atmospheric environment and is widely used in gas-insulated power equipment. In this paper, a new SF6 gas detection system based on hollow waveguide fiber (HWG) is proposed, which can be used for low concentration SF6 gas leakage detection. The light emitted by the CO2 laser is attenuated and coupled into the hollow fiber through spatial collimation. Finally, it is detected by the detector after the absorption reaction between the hollow cavity and the gas. Finally, the signal is processed by digital filtering based on LabView and digital dual-phase lock-in amplification. SF6 gas with concentrations of 0.5 ppm, 2.45 ppm, 4.9 ppm, and 9.92 ppm were detected. The experimental results show that the detection limit of the detection system can reach 0.4 ppm, the detection error of the SF6 gas concentration is less than 1 %, and the repeatability test shows that the detection system has high stability.

Integrated Approach to the Optimization, Synthesis, Fabrication, and Application of ZnO-Based Sensors for Portable LPG Leakage Detection Systems

Liquefied petroleum gas (LPG) is used for cooking as well as in vehicles in the form of compressed natural gas (CNG) and in industries. As gas is volatile, there is the possibility of leakage which will be turned into take explosion or fire. It is a keen need to use the detection system for gas leakage for security purposes. ZnO thick film sensor was synthesized and fabricated by using the standard screen-printing method. The XRD pattern revealed that the ZnO thick film was polycrystalline, with an average crystallite size of around 27.1174 nm. The SEM scan revealed a ZnO particle size of around 1.88�m. Additionally, electrical and thermal properties were examined. This paper discussed the synthesized ZnO thick film LPG gas leakage detector prototype using Arduino ATMEGA8.

Pengembangan Alat Pendeteksi Kebocoran Gas LPG Menggunakan Sensor Mq-2 Sebagai Upaya Pencegahan Dini Terhadap Risiko Kebakaran

This research aims to find out how to design a security system that has a role as an LPG gas leak detection tool which is able to detect the presence of polluted gas in the surrounding air which can cause fires using a device, namely the mq-2 sensor and to find out how the gas leak detection tool works. the LPG. In preparing this research, the methodology used was ADDIE which is a development model that focuses on the suitability of the product being designed with the approach used. This research was carried out by carrying out several stages, including the analysis stage, namely analyzing the background and benefits of product development, design is the activity of making a product design, development is the stage of making a product according to the design that has been made, implementation is the application of a product that has been made, evaluation is the stage carried out to evaluate products that have been developed. The way this tool works is by detecting indications of polluted gas in the surrounding air, then the sensor sends a signal to the buzzer to provide a warning in the form of a sound produced by the buzzer.

Measurement of the concentration distribution of hydrogen jets using adaptive stream stripe- background oriented schlieren (ASS-BOS)

Hydrogen leakage diagnosis has attracted more and more attention, especially in the high-pressure hydrogen system of fuel cell vehicles, where the chance of deflagration is quite high. Traditional methods for detecting gas leaks rely on stationary sensor measurements and manual inspections. Manual inspections are time and resource-consuming, and it is challenging to achieve real-time, comprehensive inspections in large spaces. In this study, a new Adaptive Stream Stripe-Background Oriented Schlieren (ASS-BOS) method for hydrogen jet visualization is proposed. Three different background patterns, namely random scatter background, checkerboard background, and stripe background, are designed for multiple experiments. The results show that when observing hydrogen jets in the far-field region (low-density gradient), ASS-BOS has higher accuracy and resolution, detects larger background displacements, and shows more turbulence details. In addition, the concentration distribution of the hydrogen jet is reconstructed using ASS-BOS. We compare the concentration of the hydrogen jet obtained from the inversion of the ASS-BOS method with the experimental results measured by the sensor. We find that the average error is 3.45%, indicating that ASS-BOS can accurately reconstruct the concentration distribution of the hydrogen jet.

Early Detection of Pipeline Natural Gas Leakage from Hyperspectral Imaging by Vegetation Indicators and Deep Neural Networks.

The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt detection. This study explores the utility of Vegetation Indicators (VIs) to reflect vegetation health deterioration, thereby representing leak-induced stress. Despite the acknowledged potential of VIs, their sensitivity and separability remain understudied. In this study, we employed ground vegetation as biosensors for detecting methane emissions from underground pipelines. Hyperspectral imaging from vegetation was collected weekly at both plant and leaf scales over two months to facilitate stress detection using VIs and Deep Neural Networks (DNNs). Our findings revealed that plant pigment-related VIs, modified chlorophyll absorption reflectance index (MCARI), exhibit commendable sensitivity but limited separability in discerning stressed grasses. A NG-specialized VI, the optimized soil-adjusted vegetation index (OSAVI), demonstrates higher sensitivity and separability in early detection of methane leaks. Notably, the OSAVI proved capable of discriminating vegetation stress 21 days after methane exposure initiation. DNNs identified the methane leaks following a 3-week methane treatment with an accuracy of 98.2%. DNN results indicated an increase in visible (VIS) and a decrease in near-infrared (NIR) in spectra due to methane exposure.

Novel differential pumping system with extended sampling range: Design and application in the EAST tokamak

A novel differential pumping system (DPS) with an adjustable sampling rate has been developed and implemented in the Experimental Advanced Superconducting Tokamak (EAST). This system is equipped with a high-resolution quadrupole mass spectrometer (QMS), covering a mass range of 1–16 atomic mass units (AMU), alongside a conventional QMS with a broader range of 1–200 AMU. The DPS features a dynamic pressure sampling capability from 10−2 to 105 Pa, utilizing a gas dosing valve and an angle valve, enabling a wide gas sampling ratio range of 10−9 to 3 × 10−2. The high-resolution QMS (QMG700) is adept at directly quantifying the partial pressures of deuterium and helium within mixtures, while the conventional QMS (RGA200) offers indirect measurement of D2 partial pressures above 2 × 10−5 Pa, complemented by direct wide-range mass analysis. During the EAST tokamak campaigns of 2023 and 2024, the DPS was effectively utilized for glow discharge cleaning (GDC) at a pressure of 3 Pa and ion cyclotron wall conditioning (ICWC) at approximately 3 × 10−3 Pa, accurately distinguishing deuterium pressure from the helium environment in the wide pressure range of vacuum vessel. Moreover, the DPS was successfully employed to trace the vacuum leak location in EAST campaign with a pressure of up to hundreds Pa. This DPS is a key tool for gas ingredient analysis and leak detection in the EAST campaigns, providing a valuable reference for the vacuum operation of future fusion reactors.

GDI (IoT-Based Gas Detector) As an Appropriate Technology for Gas Leak Detection in Tarakan City, North Kalimantan

Tarakan City, as the center of oil and gas resource exploitation in North Kalimantan Province, faces significant challenges related to safety and security concerning potential natural gas leaks. With its large population and the presence of 1,400 oil and gas wells, as well as being the largest consumer of natural gas networks in Indonesia with 32,000 consumers, the risk of gas leaks is a major concern. Previous gas leak incidents have demonstrated serious impacts, including fires and explosions resulting in significant losses for the community and the environment. To address these challenges, the 5.0 technology offers a potential solution, particularly implementing the Internet of Things (IoT). Based on this technology, developing an IoT-Based Gas Detector involves surveying potential tools, analyzing economic, social, and environmental factors, assembling the tools, and applying the product. IoT Gas Detectors have an advantage by utilizing connected sensor technology. The IoT-Based Gas Detector can be utilized to detect gas leaks in real-time, providing swift responses and reducing the potential impacts of gas leaks. Consequently, it can increase safety, security, and the efficient use of natural resources. The IoT-based Gas Detector (GDI) program supports several Sustainable Development Goals (SDGs), including: [1] No Poverty, [3] Good Health and Well-being, [7] Affordable and Clean Energy, [9] Industry, Innovation, and Infrastructure, [11] Sustainable Cities and Communities, [17] Partnerships for the Goals.

Smart Solutions for Safe and Convenient Home Gas Management: A Comprehensive Approach to LPG Cylinder Monitoring and Booking

In today's fast-paced world, people often struggle to manage daily tasks, including household chores such as scheduling LPG cylinder deliveries and addressing emergencies like gas leaks or fires. Recognizing this challenge, there's a growing need to develop technological solutions. The Proposed work focuses on designing a system to detect gas leaks from cylinders. It utilizes a gas sensor that triggers a servo motor to shut off the gas regulator upon detecting any presence of gas leakage, while also sending a notification to the user via a GSM modem. Additionally, the system addresses the issue of irregular LPG cylinder supply by automatically placing an order when the cylinder's net weight drops to 16.5kg, ensuring a reserve of 2kg of gas until the new cylinder arrives. Other features include flame intensity control through precise timing of the burner using Arduino, as well as an automatic gas supply shutoff if inactive for an extended period. Implementing this system in households guarantees enhanced safety and convenience in various ways. Key Words: Arduino Mega, Gas sensor MQ5, GSM Module, Load cell, Gas regulator, Servomotor.

GSM-Enabled Home Automation and Security System: A Comprehensive Investigation and Implementation

This research project focused on integrating home control and security through advanced Home Automation Systems. A thorough analysis and practical implementation of home automation technology were conducted, utilizing Global System for Mobile Communication (GSM) modems to manage various home appliances, including fans, air conditioning systems, and security systems. The system relied on Short Message Service (SMS) text messages for control and monitoring. Key features included an entrance security mechanism to promptly notify homeowners of unauthorized access, bolstering overall security. Additionally, an anti-theft reporting system employed alarms and SMS notifications to inform owners of security breaches. The system also integrated safety protocols for fire or gas leakage, dispatching SMS notifications and activating alarms to alert homeowners. The use of GSM technology provided wireless access to control connected devices, enhancing system efficiency and convenience. This research contributed to the smart home technologies field by presenting an advanced system that harmonized automation, security, and safety, with potential applications across diverse residential settings. While numerous home automation systems were available in the market, the significance of the proposed home automation system lay in its advanced features and comprehensive approach to integrating control and security functions. Unlike many existing systems, which may have offered basic automation capabilities, the proposed system went beyond simple automation by seamlessly integrating security measures using GSM technology. This allowed homeowners to effectively manage a wide range of home appliances, including fans, air conditioning systems, and security systems, all through the convenience of SMS text messages. Key features of the proposed system, such as the entrance security mechanism and anti-theft reporting system, addressed critical security concerns and provided homeowners with real-time notifications of unauthorized access or security breaches. Additionally, the integration of safety protocols for fire or gas leakage further enhanced the system's utility and value by prioritizing homeowner safety. Moreover, the utilization of GSM technology offered wireless access to control connected devices, significantly enhancing system efficiency and convenience compared to traditional wired systems. This wireless connectivity ensured that homeowners could remotely monitor and control their home environment from anywhere, at any time, providing them with peace of mind and control over their living space. Overall, the proposed home automation system represented a significant advancement in the field of smart home technologies by offering a comprehensive solution that harmonized automation, security, and safety. Its potential applications across diverse residential settings underscored its importance and relevance in meeting the evolving needs of modern homeowners. Index Terms: Short Message Service (SMS), GSM modems, Safety protocols, Gas leakage detection.

Active gas camera mass flow quantification (qOGI): Application in a biogas plant and comparison to state-of-the-art gas cams.

Gas cameras are primarily used to detect gas leaks, but their use has been increasingly extended to mass flow quantification (qOGI). We employ the previously published active illuminated gas camera [Bergau etal. "Real-time active-gas imaging of small gas leaks," J. Sens. Sens. Syst. 12, 61-68 (2023) and Bergau etal. "Flow rate quantification of small methane leaks using laser spectroscopy and deep learning," Process Saf. Environ. Prot. 182, 752-759 (2024)] in a real-world application for quantification, enhancing the camera with two new features: sensitivity adaptation and camera-gas distance detection. This technology was applied to a gas leak found in the pressure swing adsorption room of a biogas plant in Germany. We compare its performance with state-of-the-art quantification gas cameras (qOGI), such as Sensia Mileva 33. Such a comparison between active and passive gas cameras is possible for the first time due to the introduced sensitivity tuning. Additionally, we enclosed the gas leak and measure the methane concentration with a flame ionization detector, providing a gold standard for comparison. Our findings revealed relative offsets to our gold standard of -57% and +319% for the DAS-camera and the Sensia, respectively, suggesting that the accuracy of mass flow quantification could be improved through the use of active gas cameras.

Gas Leakage Detection and Prevention Using Sensors and IoT

In today's world, safety is critical, and good safety systems must be put in place. The principal objective of this study is to design a gas sensing and warning system based on Internet Of Things. LPG is used for cooking and in industries. Since LPG is stored and handled by civilian’s, it is easily damaged. In any case, when the gas cylinder, controller, and tube are not in great state, breaks occur, resulting in an issue. Accidents can cause problems such as suffocation and can start fires. Installing gas leakage detectors in vulnerable areas is the most important measure to avoid accidents caused by gas spill. The primary purpose of this study is to propose a framework for detecting and eliminating gas leakage in vulnerable areas. The gas sensor is one such way of detecting and alerting people to gas spills in their initial stages. The gas leak detection system includes a GSM module that sends SMS messages when a gas leak is noticed. It also turns on the exhaust fan and alerts the firefighter department and helps us prevent unexpected disasters. This device can be used in households and industrial facilities, they can be controlled and observe conditions remotely. Key Words: Node MCU, MQ6 Sensor, ESP2866 WIFI, Servo Motor, GSM module.

Lora Based Industrial Environment Monitoring System

With the advent of automation, the concept of protecting the business environment has become popular and recognized in the business world. As the factory scale grows and the complexity of the process increases, advanced technology must be used in the device to measure and control many business processes simultaneously. Today, the trend is towards miniaturization of instruments and greater precision and accuracy. Reliable equipment and controls are crucial to the safety and efficiency of any process. The goal of this project is to gain knowledge about the most important aspects of the job to improve safety. The system includes the use of LORA to monitor the business environment. In this project, we use Lora communication to send data, and the receiving end of the monitoring station receives the data from the sending end. In an emergency, when you press the emergency button on the monitoring station, a message is sent to the work unit by LORA. Since LORA is a transceiver, two- way communication is possible in the project. Temperature sensors, gas sensors and fire sensors are used to monitor the environment of business units. Temperature sensors are used in industry to calculate temperature and provide information to microcontrollers. Gas sensors are used in industry to detect gas leaks. Fire sensors are used to detect fire and send the information to the monitoring station. This product is delivered by LORA.

LPG Gas Leakage Detection System with Auto Cutoff Regulator using Arduino

The problem of gas leakage and fire is often encountered in our day-to-day life. LPG, Liquified Petroleum Gas, is highly flammable gas used as fuel in heating appliances. Leakage of this gas raises the risk of building fire, suffocation or an explosion. Most of the fire-breakouts in industries are due to gas leaks. These cause dreadful damage to the equipment, human life leading to injuries, deaths, and environment. The mentioned problem can be solved with the development of reliable techniques to detect gas leakage. We proposed a system to detect gas leakage automatically with the help of gas sensor and Arduino microcontroller and alerts the person if there is gas leakage by buzzer alarm and auto cutoff regulator.

ANALYSIS OF THE PROSPECTS OF APPLICATION OF NATURAL GAS LEAK DETECTION METHODS TO INCREASE THE EFFICIENCY OF ATMOSPHERIC AIR MONITORING AT HTS FACILITIES

The activities of the oil and gas industry enterprises, in particular the objects of gas transportation systems (GTS), are accompanied by a significant anthropogenic impact on the environment. The atmospheric air itself is significantly affected, since many technological processes are accompanied by emissions of natural gas (organized, unorganized and emergency) and, as a result, a significant amount of volatile substances, many of which are dangerous and harmful, enter the atmosphere. There is a wide range of methods for detecting gas leaks from elements of gas transportation systems. Ways of classifying methods directly depend on the features that form the basis of their distribution. However, the insufficient definition of the classification features, their "one-sidedness" do not allow a full assessment of the shortcomings and advantages of certain methods and means, and, therefore, the possibility of their application to increase the effectiveness of atmospheric air monitoring at HTS facilities in order to ensure environmental safety. The main tasks solved in this article are the formulation of the optimal classification of existing methods of controlling the presence of gas leaks in terms of applicability in environmental monitoring systems of atmospheric air; analysis of their advantages and disadvantages; substantiation of the expediency and perspective of using these means and methods to ensure constant monitoring of the state of atmospheric air at GTS facilities. A classification of methods and means of control is proposed based on the level of application of technical means, according to which all methods are divided into organoleptic, hardware and computational (software-mathematical). According to the results of the analysis of the data of the groups, it was determined that, from the point of view of the prospects of application in the atmospheric air quality monitoring systems at the GTS facilities, hardware means, namely gas analyzers, have the most advantages.

Assessing Gas Leakage Detection Performance Using Machine Learning with Different Modalities

Assessing Gas Leakage Detection Performance Using Machine Learning with Different Modalities

High sensitivity and stability cavity-enhanced photoacoustic spectroscopy with dual-locking scheme

We present a high sensitivity and long-term stability cavity-enhanced photoacoustic spectroscopy (CE-PAS) system with optical cavity and acoustic frequency dual-locking scheme for trace acetylene (C2H2) detection. The first mechanism involves locking the optical wavelength to the cavity resonance by comparing the phase-sensitive component of the reflected light with a reference signal in a feedback loop. The second locking mechanism controls the gas proportion inside the photoacoustic cell to lock the acoustic frequency, suppressing the drift caused by environmental temperature variation. By minimizing amplitude fluctuations through dual-locking, the sensor achieves improved stability with reduced fluctuations from ±10.12 % to ±1.16 %. The linear responsivity and excellent linearity of the sensor are demonstrated over a concentration variation spanning four orders of magnitude. Experimental results showcase a minimum detection limit of 1.2 parts-per-billion (ppb) at an integration time of 400 s, corresponding to a normalized noise equivalent absorption (NNEA) coefficient of 1.37×10−11 cm−1·W· Hz−1/2 for C2H2 detection. Long-term stability is within ±2 % over a 15-day period. The combination of high sensitivity and long-term stability make this CE-PAS sensor suitable for a wide range of applications in environmental monitoring, industrial process control, and gas leak detection.

Multi unmanned aerial vehicle odor source location based on improved artificial fish swarm algorithm

Odor source location technology has important application value in environmental monitoring, safety emergency and search and rescue operations. For example, it can be used in post-disaster search and rescue, detection of hazardous gas leakage, and fire source detection. Existing odor source location methods have problems such as low search efficiency, inability to adapt to complex environments, and inaccurate odor source location. In this study, based on unmanned aerial vehicle technology and using swarm intelligence optimization algorithm, an improved artificial fish swarm algorithm (IAFSA) is proposed by combining curiosity in psychology on the basis of retaining the good optimization performance of the artificial fish swarm algorithm. The algorithm quantifies the curiosity of artificial fish searching high-concentration areas through a model, dynamically adjusts the artificial fish's field of vision and step length with the calculated curiosity factor, and avoids the oscillation phenomenon in the later stage of the algorithm. Simulation results show that the IAFSA has a higher success rate and smaller location error. Finally, odor source location experiments were carried out in an indoor physical environment, the feasibility of the odor source location method proposed in this study is verified in actual scenarios.