Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform

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Main Authors: Paulraj, Murugesa Pandiyan, Prof. Madya, Sazali, Yaacob, Prof. Dr., Zin, M.Z.M.
Format: Working Paper
Language:English
Published: Institute of Electrical and Elctronics Engineering (IEEE) 2010
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/8797
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spelling my.unimap-87972010-08-18T02:03:33Z Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Zin, M.Z.M. Backpropagation neural network Entropy Wavelet analysis International Colloquium on Signal Processing and Its Applications (CSPA) Link to publisher's homepage at http://ieeexplore.ieee.org/ The sound of working vehicle provides an important clue for engine faults diagnosis. Endless efforts have been put into the research of fault diagnosis based on sound. It offers concrete economic benefits, which can lead to high system reliability and save maintenance cost. A number of diagnostic systems for vehicle repair have been developing in recent years. Artificial Neural Network is a very demanding application and popularly implemented in many industries including condition monitoring via fault diagnosis. This paper presents a feature extraction algorithm using total entropy of 5 level decomposition of wavelet transform. The engine noise signal is decomposed into 5 levels (A5, D5, A4, D4, A3, D3, A2, D2, A1, D1) using Daubechies "db4" wavelet family. From the decomposed signals, the entropy is applied for each levels and the feature are extracted and used to develop a backpropagation neural network. 2010-08-18T02:03:33Z 2010-08-18T02:03:33Z 2009-03-06 Working Paper p.47-51 978-1-4244-4150-1 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5069186 http://hdl.handle.net/123456789/8797 en Proceedings of the 5th International Colloquium on Signal Processing and Its Applications (CSPA) 2009 Institute of Electrical and Elctronics Engineering (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Backpropagation neural network
Entropy
Wavelet analysis
International Colloquium on Signal Processing and Its Applications (CSPA)
spellingShingle Backpropagation neural network
Entropy
Wavelet analysis
International Colloquium on Signal Processing and Its Applications (CSPA)
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Zin, M.Z.M.
Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
description Link to publisher's homepage at http://ieeexplore.ieee.org/
format Working Paper
author Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Zin, M.Z.M.
author_facet Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Zin, M.Z.M.
author_sort Paulraj, Murugesa Pandiyan, Prof. Madya
title Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
title_short Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
title_full Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
title_fullStr Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
title_full_unstemmed Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
title_sort entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform
publisher Institute of Electrical and Elctronics Engineering (IEEE)
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/8797
_version_ 1643789251852107776
score 13.214268