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Bearing Fault Diagnosis using Multiclass Support Vector Machine with efficient Feature Selection Methods

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Figure

Fig. 1. Proposed experimental methodology
Fig. 2. Bearing test rig (experimental set up) and induced bearing faults
Fig. 3(b). Frequency spectrum of various states of bearing (X axis–Frequency, Y axis-Amplitude in „g‟)
TABLE IICHEMATIC REPRESENTATION OF STATISTICAL FEATURES
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