Artificial Neural Network Based Classification for Monoblock Centrifugal Pump Using Wavelet Analysis

Fault diagnosis of monoblock centrifugal pump as pattern recognition problem has three major steps. Feature extraction, Feature selection and classification. Numbers of advanced algorithms are being used for feature extraction and classification. However, all the features extracted from raw signal need not have useful information for the study. Presences of redundant features are also possible. There are many algorithms which can be used to filter such redundant features. In this paper, Discrete Wavelet Transform (DWT) is used for feature extraction and best features are selected using decision tree algorithm and classification is done using ANN and the results are presented. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print) ISSN 0976 – 6359(Online) Volume 1 Number 1, July Aug (2010), pp. 28-37 © IAEME, http://www.iaeme.com/ijmet.html IJMET © I A E M E International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 1, Number 1, July Aug (2010), © IAEME 29