Blade fault diagnosis using artificial intelligence technique
Blade fault diagnosis is conventionally based on interpretation of vibration spectrum and wavelet map. These methods are however found to be difficult and subjective as it requires visual interpretation of chart and wavelet color map. To overcome this problem, important features for blade fault diag...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/86089/1/NguiWaiKengPFKM2016.pdf http://eprints.utm.my/id/eprint/86089/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:131284 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |