Multiple Fault Classification Using Support Vector Machine in a Machinery Fault Simulator
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-09918-7_90
Reference15 articles.
1. Jack LB, Nandi AK (2002) Fault detection using support vector machines and artificial neural networks, augmented by genetic algorithms. Mech Syst Signal Process 16(2–3):373–390
2. Widodo A, Yang B (2007) Support vector machine in machine condition monitoring and fault diagnosis. Mech Syst Signal Process 21:2560–2574
3. Samanta B, Al-Balushi KR, Al-Araimi SA (2003) Artificial neural network and support vector machines with genetic algorithms for bearing fault detection. Eng Appl Artif Intell 16:657–665
4. Samanta B (2004) Gear fault detection using artificial neural networks and support vector machines with genetic algorithms. Mech Syst Signal Process 18:625–644
5. Yang B, Hwang W, Kim D, Tan AC (2005) Condition classification of small reciprocating compressor for refrigerators using artificial neural networks and support vector machines. Mech Syst Signal Process 19:371–390
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