A bearing fault classifier using Artificial Neuro-Fuzzy Inference System (ANFIS) based on statistical parameters and Daubechies wavelet transform features

A bearing fault classifier using Artificial Neuro-Fuzzy Inference System (ANFIS) based on statistical parameters and Daubechies wavelet transform features

This paper presents an investigation process in building a bearing fault classifier based on wavelet coefficients and statistical parameter features. The building process starts by processing raw vibration data that was acquired from a bearing test rig. The data acquisition process was carried out f...

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Bibliographic Details
Main Authors: Latuny, Jonny, Entwistle, Rodney
Other Authors: Andrei Kotousov
Format: Conference Paper
Published: Engineers Australia 2012
Subjects:
ANFIS
bearing fault classifier
diagnosis
Daubechies wavelet
wavelet energy level
statistical parameters
Online Access:http://hdl.handle.net/20.500.11937/34796

Internet

http://hdl.handle.net/20.500.11937/34796

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