{"title":"基于多节点甲烷检测网络的系统响应特性改进长壁煤矿甲烷实时监测","authors":"B. Cappellini","doi":"10.33915/ETD.8333","DOIUrl":null,"url":null,"abstract":"\n Methane released from coal during underground mining operations imposes a significant threat to the workers safety and consequently limits production. This paper introduces a method for the monitoring of methane emissions that are released during longwall coal mining operations. Furthermore, it describes the methodology used to test and develop the system’s response characteristics for improved measurement accuracy. The Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development to improve the safety and productivity during mining operations. The MWS consists of 10 compact sampling units designed to be integrated within the current roof support equipment of mines. Each unit contains an array of sensors to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. Reduced one-dimensional (1-D) modeling studies provided a useful tool to simulate the longwall mining environment. From the 1-D studies, multiple scenarios were constructed to generate temporal methane distributions that were the result of ventilation and production patterns. Model results were extracted from the proposed MWS sampling locations and used to demonstrate its usefulness and effectiveness within the laboratory setting. The resulting outputs from the system were then used to develop a signal reconstruction technique, which effectively sharpened response times and improved real time measurement accuracy.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving Real-Time Methane Monitoring in Longwall Coal Mines Through System Response Characterization of a Multi-Nodal Methane Detection Network\",\"authors\":\"B. Cappellini\",\"doi\":\"10.33915/ETD.8333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Methane released from coal during underground mining operations imposes a significant threat to the workers safety and consequently limits production. This paper introduces a method for the monitoring of methane emissions that are released during longwall coal mining operations. Furthermore, it describes the methodology used to test and develop the system’s response characteristics for improved measurement accuracy. The Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development to improve the safety and productivity during mining operations. The MWS consists of 10 compact sampling units designed to be integrated within the current roof support equipment of mines. Each unit contains an array of sensors to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. Reduced one-dimensional (1-D) modeling studies provided a useful tool to simulate the longwall mining environment. From the 1-D studies, multiple scenarios were constructed to generate temporal methane distributions that were the result of ventilation and production patterns. Model results were extracted from the proposed MWS sampling locations and used to demonstrate its usefulness and effectiveness within the laboratory setting. The resulting outputs from the system were then used to develop a signal reconstruction technique, which effectively sharpened response times and improved real time measurement accuracy.\",\"PeriodicalId\":146533,\"journal\":{\"name\":\"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33915/ETD.8333\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33915/ETD.8333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving Real-Time Methane Monitoring in Longwall Coal Mines Through System Response Characterization of a Multi-Nodal Methane Detection Network
Methane released from coal during underground mining operations imposes a significant threat to the workers safety and consequently limits production. This paper introduces a method for the monitoring of methane emissions that are released during longwall coal mining operations. Furthermore, it describes the methodology used to test and develop the system’s response characteristics for improved measurement accuracy. The Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development to improve the safety and productivity during mining operations. The MWS consists of 10 compact sampling units designed to be integrated within the current roof support equipment of mines. Each unit contains an array of sensors to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. Reduced one-dimensional (1-D) modeling studies provided a useful tool to simulate the longwall mining environment. From the 1-D studies, multiple scenarios were constructed to generate temporal methane distributions that were the result of ventilation and production patterns. Model results were extracted from the proposed MWS sampling locations and used to demonstrate its usefulness and effectiveness within the laboratory setting. The resulting outputs from the system were then used to develop a signal reconstruction technique, which effectively sharpened response times and improved real time measurement accuracy.