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Fault diagnosis system using LPC coefficients and neural network

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3 Author(s)
Hyungseob Han ; Dept. of Comput. Eng. & Inf. Technol., Univ. of Ulsan, Ulsan, South Korea ; Sangjin Cho ; Uipil Chong

As rotating machines perform an important role in industrial applications, many researchers have developed various condition monitoring system and fault diagnosis system by applying various techniques such as signal processing and pattern recognition. Recently, fault diagnosis systems using artificial neural network have been proposed. This paper proposes the neural-network-based fault diagnosis system using the proper feature vectors by LPC (linear predictive coding) coefficients. This method has not been reported yet. For the effective fault diagnosis, a MLP (multi-layer perceptron) network is used. From the experiment results, the proposed system shows a perfect fault diagnosis for each faulty case.

Published in:

Strategic Technology (IFOST), 2010 International Forum on

Date of Conference:

13-15 Oct. 2010