Cover Image

Loudspeaker fault detection using artificial neural network

Link to publisher's homepage at http://ieeexplore.ieee.org/

Saved in:
Bibliographic Details
Main Authors: Paulraj, Murugesa Pandiyan, Prof. Madya, Sazali, Yaacob, Prof. Dr., Saad, M. R.
Format: Working Paper
Language:English
Published: Institute of Electrical and Elctronics Engineering (IEEE) 2010
Subjects:
Fast Fourier transform
Harmonic distortion
Loudspeaker
Neural network
International Colloquium on Signal Processing and Its Applications (CSPA)
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/8815
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-8815
record_format dspace
spelling my.unimap-88152010-08-18T03:47:13Z Loudspeaker fault detection using artificial neural network Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Saad, M. R. Fast Fourier transform Harmonic distortion Loudspeaker Neural network International Colloquium on Signal Processing and Its Applications (CSPA) Link to publisher's homepage at http://ieeexplore.ieee.org/ Traditionally, loudspeaker's quality control has been done manually and inspection of loudspeaker faults is time consuming and causes error in the quality evaluation. In order to reduce the time consumption and errors in the quality evaluation, in this research work, a simple loudspeaker diagnosing system is developed based on the harmonic distortion. The faulty and normal loudspeakers are tested using the sound emanated from the loudspeaker in the frequency range between 20 Hz and 20,000 Hz. A Fast Fourier Transform (FFT) is applied on the recorded signal to transform from time domain to frequency domain and the frequency spectrum is obtained. From the frequency spectrum, the total energy in the first 6 frequency bands are computed and chosen for further analysis. These frequency band energy signals obtained are then used as features for training the neural network. A simple neural network model is developed for the automatic detection of loudspeaker faults. From the result it is observed that the proposed method is able to classify the faults with an accuracy level of 82%. 2010-08-18T03:47:13Z 2010-08-18T03:47:13Z 2009-03-06 Working Paper p.362-366 978-1-4244-4150-1 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5069251 http://hdl.handle.net/123456789/8815 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 Fast Fourier transform
Harmonic distortion
Loudspeaker
Neural network
International Colloquium on Signal Processing and Its Applications (CSPA)
spellingShingle Fast Fourier transform
Harmonic distortion
Loudspeaker
Neural network
International Colloquium on Signal Processing and Its Applications (CSPA)
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Saad, M. R.
Loudspeaker fault detection using artificial neural network
description Link to publisher's homepage at http://ieeexplore.ieee.org/
format Working Paper
author Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Saad, M. R.
author_facet Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Saad, M. R.
author_sort Paulraj, Murugesa Pandiyan, Prof. Madya
title Loudspeaker fault detection using artificial neural network
title_short Loudspeaker fault detection using artificial neural network
title_full Loudspeaker fault detection using artificial neural network
title_fullStr Loudspeaker fault detection using artificial neural network
title_full_unstemmed Loudspeaker fault detection using artificial neural network
title_sort loudspeaker fault detection using artificial neural network
publisher Institute of Electrical and Elctronics Engineering (IEEE)
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/8815
_version_ 1643789252447698944
score 13.214268

Similar Items