Fault Diagnostics of Ball Bearings Using Wavelet Transform and Neural Networks
碩士 === 國立成功大學 === 製造資訊與系統研究所碩博士班 === 98 === Signals detected from accelerate and acoustic sensors should be processed to extract features by using such as time-domain, frequency-domain, and wavelet transform to diagnose machine faults. Effective features decide diagnostic performance. However, causi...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/66962117721223246633 |