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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions

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dc.contributor.author Liu, Wenpeng
dc.contributor.author Ray, Asok
dc.contributor.author Rostami, Jamal
dc.contributor.author Saab, Samer S.
dc.contributor.editor Mishra, Brijes
dc.contributor.editor Lawson, Heather
dc.contributor.editor Murphy, Michael
dc.contributor.editor Perry, Kyle
dc.date.accessioned 2019-08-30T13:18:38Z
dc.date.available 2019-08-30T13:18:38Z
dc.date.copyright 2017 en_US
dc.identifier.isbn 0873354567 en_US
dc.identifier.uri http://hdl.handle.net/10725/11255
dc.description.abstract Ground instability, such as roof or rib failures, is one of the most serious and frequent safety hazards that occur in underground mining, tunneling, and underground construction. The ground-related parameters and features of interest, in assessing roof or rib failures, are location, frequency, and orientation of the joints, voids, as well as rock-strength. These parameters are the main components of rock mass characterization that offers effective strategies for ground support, which, in turn, allow one to mitigate the risks related to ground instability. The main objective of this study is to determine the location of joints and classify rock-strengths by analyzing the drilling data recorded from an instrumented roof bolter while drilling for rock bolt installation during the operational cycle. For this purpose, computer programs based on updated pattern recognition algorithms were developed for joint-detection and classification of rock types to offer an estimated strength. This paper briefly introduces ongoing research on joint detection, especially for joints with an aperture less than 0.125in (3.175mm), by employing an instrumented roof bolter in controlled environments. To improve the capability and precision of joint detection programs in detecting the joints from the drilling data and reducing the number of false alarms, many laboratory tests with various simulated joints and rock-strengths were carried out at a J.H. Fletcher & Co. facility. This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole. en_US
dc.language.iso en en_US
dc.publisher Society for Mining, Metallurgy & Exploration en_US
dc.subject Ground control (Mining) -- Congresses en_US
dc.subject Coal mines and mining -- Congresses en_US
dc.subject Longwall mining -- Congresses en_US
dc.subject Mine roof bolting -- Congresses en_US
dc.title Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SOE en_US
dc.author.idnumber 199690250 en_US
dc.author.department Computer Science And Mathematics en_US
dc.description.embargo N/A en_US
dc.description.physdesc xv, 359 pages : illustrations (some color) en_US
dc.publication.place Englewood, Colorado en_US
dc.description.bibliographiccitations Includes bibliographical references. en_US
dc.identifier.ctation Liu, W., Ray, A., Rostami, J., & Saab, S. S. (2017, January). Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions. In 36th International Conference on Ground Control in Mining, ICGCM 2017 (pp. 297-303). Society for Mining, Metallurgy and Exploration (SME). en_US
dc.author.email ssaab@lau.edu.lb en_US
dc.conference.date 25-27 July, 2017 en_US
dc.conference.pages 297-303 en_US
dc.conference.place Morgantown, WV en_US
dc.conference.title Proceedings of the 36th International Conference on Ground Control in Mining en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://pennstate.pure.elsevier.com/en/publications/application-of-updated-joint-detection-algorithm-for-the-analysis en_US
dc.orcid.id https://orcid.org/0000-0003-0124-8457 en_US
dc.publication.date 2017 en_US
dc.author.affiliation Lebanese American University en_US


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