Jiani Zhou;Chen Chen;Yong Zhang;Jun Lin;Heng Piao;Feng Sun
{"title":"A Passive Detection Method of Gas Cloud Concentration Distributions for Leaking Alkane Gas","authors":"Jiani Zhou;Chen Chen;Yong Zhang;Jun Lin;Heng Piao;Feng Sun","doi":"10.1109/TIM.2026.3660409","DOIUrl":null,"url":null,"abstract":"Methane is the primary component of natural gas. The accurate detection of methane leakage points and concentration is crucial to ensuring safety and environmental protection. However, traditional active gas concentration detection methods are susceptible to interference from dynamic backgrounds, which makes concentration detection challenging. This article presents a passive method for detecting gas cloud concentration distributions based on a self-developed passive infrared imaging system operating in the 3.2–<inline-formula> <tex-math>$3.4~\\mu $ </tex-math></inline-formula>m wavelength band. A methane detection model considering multiple influencing factors was established. During the model development, an adaptive factor was incorporated into the prediction and tracking framework of the Kalman filter to mitigate the effect of time-varying light sources on gas concentration detection performance. Experimental results demonstrate that the detection limit is 0.79%, and the relative error is less than 1.00%. The system enables real-time methane concentration detection and validates its potential for natural gas leakage detection through its industrial application in complex environments. The field test videos and the core code of the proposed method have been made publicly available at: <uri>https://github.com/1996Eric/AT-EKF</uri>","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-12"},"PeriodicalIF":7.0000,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Instrumentation and Measurement","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11371322/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Methane is the primary component of natural gas. The accurate detection of methane leakage points and concentration is crucial to ensuring safety and environmental protection. However, traditional active gas concentration detection methods are susceptible to interference from dynamic backgrounds, which makes concentration detection challenging. This article presents a passive method for detecting gas cloud concentration distributions based on a self-developed passive infrared imaging system operating in the 3.2–$3.4~\mu $ m wavelength band. A methane detection model considering multiple influencing factors was established. During the model development, an adaptive factor was incorporated into the prediction and tracking framework of the Kalman filter to mitigate the effect of time-varying light sources on gas concentration detection performance. Experimental results demonstrate that the detection limit is 0.79%, and the relative error is less than 1.00%. The system enables real-time methane concentration detection and validates its potential for natural gas leakage detection through its industrial application in complex environments. The field test videos and the core code of the proposed method have been made publicly available at: https://github.com/1996Eric/AT-EKF
期刊介绍:
Papers are sought that address innovative solutions to the development and use of electrical and electronic instruments and equipment to measure, monitor and/or record physical phenomena for the purpose of advancing measurement science, methods, functionality and applications. The scope of these papers may encompass: (1) theory, methodology, and practice of measurement; (2) design, development and evaluation of instrumentation and measurement systems and components used in generating, acquiring, conditioning and processing signals; (3) analysis, representation, display, and preservation of the information obtained from a set of measurements; and (4) scientific and technical support to establishment and maintenance of technical standards in the field of Instrumentation and Measurement.