Fault diagnostic model for rotating machinery based on principal component analysis and neural network

• 主要な著者: Muhammad, M.B, Sarwar, U., Tahan, M.R., Abdul Karim, Z.A.
• フォーマット: 論文
• 出版事項: Asian Research Publishing Network 2016
• オンライン･アクセス: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009230977&partnerID=40&md5=fca03f86730f7990ca001fa0e14380df; http://eprints.utp.edu.my/25858/

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...