A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things
DC Field | Value | Language |
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dc.contributor.author | Jo, Byung Wan | - |
dc.contributor.author | Khan, Rana Muhammad Asad | - |
dc.contributor.author | Lee, Yun Sung | - |
dc.contributor.author | Jo, Jun Ho | - |
dc.contributor.author | Saleem, Nadia | - |
dc.date.accessioned | 2021-07-30T05:10:11Z | - |
dc.date.available | 2021-07-30T05:10:11Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2018-04 | - |
dc.identifier.issn | 1687-725X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3368 | - |
dc.description.abstract | Accurate sensing is the key to structural health monitoring of underground coal mines while using fiber Bragg grating (FBG) sensors. However, the previously developed systems for structural monitoring of underground mines have been limited to monitoring without any capability of damage detection. Therefore, this study integrates a highly accurate FBG monitoring system and output-only data-driven approaches on an Internet of things (IoT)-based platform to develop a comprehensive mine structural safety system. This system relies on a Web 2.0 main server that runs data acquisition, data processing, and damage detection algorithms along with real-time information sharing at remote locations. This system was successfully implemented at the Hassan Kishore coal mine, situated in the Salt Range of Pakistan. Wavelength division multiplexing of the FBG strain sensors reliably captured the effects of dynamic and continuous coal excavation on the stability of mine roadway and access galleries. Principal component analysis, along with hierarchical clustering, was used to determine the damage indicator of the mine. The damage index was validated, showing the minimum value for 2% stiffness reduction. Thus, integration of FBG technology with the Internet can be effectively applied for early safety assessment of underground coal mines and information sharing in real time. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | HINDAWI LTD | - |
dc.title | A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jo, Byung Wan | - |
dc.identifier.doi | 10.1155/2018/9301873 | - |
dc.identifier.scopusid | 2-s2.0-85047605188 | - |
dc.identifier.wosid | 000430686400001 | - |
dc.identifier.bibliographicCitation | JOURNAL OF SENSORS, v.2018, pp.1 - 17 | - |
dc.relation.isPartOf | JOURNAL OF SENSORS | - |
dc.citation.title | JOURNAL OF SENSORS | - |
dc.citation.volume | 2018 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 17 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Engineering | - |
dc.relation.journalWebOfScienceCategory | Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.subject.keywordPlus | MULTIVARIATE STATISTICAL-ANALYSIS | - |
dc.subject.keywordPlus | SENSING SYSTEM | - |
dc.subject.keywordPlus | TEMPERATURE | - |
dc.subject.keywordPlus | SENSORS | - |
dc.subject.keywordPlus | IOT | - |
dc.identifier.url | https://www.hindawi.com/journals/js/2018/9301873/ | - |
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