Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/13423
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dc.contributor.authorLiu, Qiyuan.en_US
dc.date.accessioned2008-10-20T08:17:08Z-
dc.date.available2008-10-20T08:17:08Z-
dc.date.copyright1999en_US
dc.date.issued1999en_US
dc.identifier.urihttp://hdl.handle.net/10356/13423-
dc.description.abstractIn repair workshops or production factories, technical personnel are often required to identify the faulty components or devices in a malfunctioning machine system. To facilitate such fault diagnosis, this research aims at developing a method for identifying those components or devices which, due to their changed sound arising from faults, cause variations in the overall sound field in an enclosed space. To do this, three microphones, hung at the centre and the ends of a rod with a given length, were made to rotate in a plane above the sound sources in order to acquire information on the sound distribution in the enclosure. The statistical properties (auto spectra and cross spectra) of the acquired signals, as functions of sound frequency and rotating angle, were taken as the object for pattern recognition.en_US
dc.format.extent124 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processingen_US
dc.titleSound pattern recognition from multiple sources in an enclosed spaceen_US
dc.typeThesisen_US
dc.contributor.supervisorLing, Shih Fuen_US
dc.contributor.schoolSchool of Mechanical and Production Engineeringen_US
dc.description.degreeMaster of Engineering (MPE)en_US
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