Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2326
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dc.contributor.authorTripathy, D P-
dc.contributor.authorNanda, S K-
dc.date.accessioned2015-05-27T06:45:44Z-
dc.date.available2015-05-27T06:45:44Z-
dc.date.issued2015-05-
dc.identifier.citation169th Meeting of the Acoustical Society of America,Pittsburgh, USA,18-22 May 2015.en_US
dc.identifier.urihttp://hdl.handle.net/2080/2326-
dc.descriptionCopyright belongs to proceeding publisheren_US
dc.description.abstractProlonged exposure of miners to the high levels of noise in opencast and underground mines can cause noise induced hearing loss and non-auditory health effects. To minimize noise risk, it is imperative to identify machinery noise and their impacts on miners at the work place and adopt cost effective and appropriate noise control measures at the source, path and at the receiver. In this paper, authors have summarized the noise levels generated from different machineries used in opencast and underground mines and elaborated on frequency dependent noise prediction models e.g. ISO 9613-2, ENM, CONCAWE and non-frequency based noise prediction model VDI-2714 used in mining and allied industries. The authors illustrated the applications of innovative soft computing models viz. Fuzzy Inference System [Mamdani and Takagi Sugeno Kang (T-S-K)], MLP (multi-layer perceptron, RBF (radial basis function) and adaptive network-based fuzzy inference systems (ANFIS) for predicting machinery noise in two opencast mines. The paper highlights the developments and research conducted on effective noise control measures being adopted for mining machineries and implemented in mines to minimize the noise menace so that noise levels generated in mines are within the prescribed noise standards and rules.en_US
dc.language.isoenen_US
dc.publisherAcoustical Society of Americaen_US
dc.subjectNoise identificationen_US
dc.subjectMining industryen_US
dc.titleNoise Identification, Modeling and Control in Mining Industryen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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