Fault Diagnosis of Monoblock Centrifugal Pump Using Stationary Wavelet Features and J48 Algorithm
نویسندگان
چکیده
Fault diagnosis of monoblock centrifugal pump is conceived as a pattern recognition problem. There are three important phases involved in a pattern recognition namely feature extraction, feature selection and classification. In this study, stationary wavelet transform (SWT) is used for feature extraction and J48 algorithm is used for feature selection and classification. The different fault conditions considered for the present study are cavitation (CAV), impeller fault (FI), bearing fault (BF) and both impeller and bearing fault (FBI). The representative signal is acquired for all faulty conditions, features are extracted, classified and the results are presented. The experimental set up and the procedure for conducting the experiments are discussed in detail.
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