Fault diagnostic model for rotating machinery based on principal component analysis and neural network
In the current economic challenge, methods to accurately predict system failure has become a holy grail in maintenance with the goal to reduce the cost of unavailability due to unscheduled shutdown. This has led to the current research with the aim to achieve a more accurate fault diagnosis for rota...
| Main Authors: | Muhammad, M.B, Sarwar, U., Tahan, M.R., Abdul Karim, Z.A. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.25858 / |
| Published: |
Asian Research Publishing Network
2016
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009230977&partnerID=40&md5=fca03f86730f7990ca001fa0e14380df http://eprints.utp.edu.my/25858/ |
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