{"title":"Gas Leakage Source Localization and Boundary Estimation using Mobile Wireless Sensor Network","authors":"Subhash Kumar, Sameer Chouksey","doi":"10.1109/ICCAKM50778.2021.9357732","DOIUrl":null,"url":null,"abstract":"The undesirable release of toxic and flammable gases such as carbon monoxide (CO) and methane (CH4) possess a serious threat for underground coal mine operations. The gas leakage source localization and boundary detection can not only play an important role to avert its consequences but also allow the mine management to take preventive measures at the earliest. However, the current practices for gas monitoring in underground coal mines have very limited scope for gas leakage source localization and boundary estimation. In this paper, a gas analyzer mounted unmanned ground vehicle (UGV) based intelligent system has been proposed for achieving the desired goal. The location-specific gas concentration values will be statistically analyzed under the deduced Gaussian Plume gas model for underground coal mines to find out the gas leakage source, spread boundary, and gas concentration grid map.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAKM50778.2021.9357732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The undesirable release of toxic and flammable gases such as carbon monoxide (CO) and methane (CH4) possess a serious threat for underground coal mine operations. The gas leakage source localization and boundary detection can not only play an important role to avert its consequences but also allow the mine management to take preventive measures at the earliest. However, the current practices for gas monitoring in underground coal mines have very limited scope for gas leakage source localization and boundary estimation. In this paper, a gas analyzer mounted unmanned ground vehicle (UGV) based intelligent system has been proposed for achieving the desired goal. The location-specific gas concentration values will be statistically analyzed under the deduced Gaussian Plume gas model for underground coal mines to find out the gas leakage source, spread boundary, and gas concentration grid map.