This paper proposes advancement in the fault diagnosis of induction motors (IMs) based on the wavelet packet transform (WPT) and the support vector machine (SVM). The aim of this work is to develop and perform the fault diagnosis of IMs at intermediate operating conditions (i.e., the speed and the load) to take care of situations where the data are limited or difficult to obtain at required speeds and loads. In order to check the capability of proposed fault diagnosis, ten different IM fault (mechanical and electrical) conditions are considered simultaneously. In order to obtain the useful information from raw time series data that can characterize each of the fault classes at various operating conditions, the wavelet packet is applied to decompose the data of vibration and current signals from the experimental test rig. Fault features are then obtained using the decomposed data and further used for the diagnosis. In this work, five different wavelet functions (i.e., the Haar, Daubechies, Symlet, Coiflet, and Discrete Meyer) are considered in order to analyze the impact of different wavelets on the IM fault diagnosis. The proposed fault diagnosis has been initially attempted for the same speed and load cases and then extended innovatively to the intermediate speed and load cases. In order to check the robustness of the proposed methodology, the diagnosis is performed for a wide range of motor operating conditions. The results show the feasibility of the proposed fault diagnosis for the successful detection and isolation of various faults of IM, even with limited data or information at some motor operating conditions.
Multifault Diagnosis of Induction Motor at Intermediate Operating Conditions Using Wavelet Packet Transform and Support Vector Machine
Indian Institute of Technology Guwahati,
Guwahati 781 039, Assam, India
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received September 18, 2017; final manuscript received January 11, 2018; published online March 13, 2018. Assoc. Editor: Shankar Coimbatore Subramanian.
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Gangsar, P., and Tiwari, R. (March 13, 2018). "Multifault Diagnosis of Induction Motor at Intermediate Operating Conditions Using Wavelet Packet Transform and Support Vector Machine." ASME. J. Dyn. Sys., Meas., Control. August 2018; 140(8): 081014. https://doi.org/10.1115/1.4039204
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