Intelligent fault diagnostic model for rotating machinery
The aim of this paper is to present an intelligent fault diagnostic to assess the changes and detect malfunctions in rotating machinery using real-time data. The developed model interprets performance condition monitoring data and determines machine health status with the use of Artificial Neural Ne...
| Main Authors: | Muhammad, M.B., Sarwar, U., Tahan, M., Karim, Z.A.A. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.21767 / |
| Published: |
IEEE Computer Society
2018
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045260805&doi=10.1109%2fIEEM.2017.8290213&partnerID=40&md5=cc01b39cbcebae732e6a88fb4854d41d http://eprints.utp.edu.my/21767/ |
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