A classifier fusion system for bearing fault diagnosis

Author:

Batista Luana,Badri Bechir,Sabourin Robert,Thomas Marc

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference35 articles.

1. Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine;Abbasion;Mechanical Systems and Signal Processing,2007

2. Monitoring and diagnosis of rolling element bearings using artificial neural networks;Alguindigue;IEEE Transactions on Industrial Electronics,1993

3. Bhavaraju, K., Kankar, P., Sharma, S., & Harsha, S. (2010). A comparative study on bearings faults classification by artificial neural networks and self-organizing maps using wavelets (vol. 2, no. 5, pp. 1001–1008).

4. Case Western Reserve University, Bearing Data Center. .

5. Chang, C., & Lin, C. (2001). LIBSVM: a library for Support Vector Machines. In .

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