Vibration Analysis Based Interturn Fault Diagnosis in Induction Machines
Top Cited Papers
- 3 July 2013
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Industrial Informatics
- Vol. 10 (1), 340-350
- https://doi.org/10.1109/tii.2013.2271979
Abstract
A vibration analysis based interturn fault diagnosis of induction machines is proposed in this paper, using a neural-network-based scheme, constituting of two parts. The first part finds out the optimum network size of the probabilistic neural network (PNN) using the Orthogonal Least Squares Regression algorithm. This judges the size of the PNN, with an effort to reduce the computation. The feature extraction to model the PNN is made meaningful using dual tree complex wavelet transform (DTCWT), which is nearly shift invariant analytical wavelet transform, giving a true representation of the input space. In the second part, preprocessing using principal component analysis is suggested as an effective way to further reduce the dimension of the feature set and size of the PNN without compromising the performance. The sensitivity, specificity, and accuracy show that the vibration signatures capture the fault more effectively (especially by the axial and radial ones), under varying supply-frequency and load conditions. A comparison with traditional discrete wavelet transform proves the applicability of the proposed scheme. A comparative evaluation with feedforward neural network and naïve Bayes scheme brings out the advantage of the proposed optimized DTCWT-PNN based technique over other machine learning approaches.Keywords
This publication has 29 references indexed in Scilit:
- Early Classification of Bearing Faults Using Morphological Operators and Fuzzy InferenceIEEE Transactions on Industrial Electronics, 2012
- Coupling Pattern Recognition With State Estimation Using Kalman Filter for Fault DiagnosisIEEE Transactions on Industrial Electronics, 2011
- Performance-Oriented Electric Motors Diagnostics in Modern Energy Conversion SystemsIEEE Transactions on Industrial Electronics, 2011
- Induction Machine Condition Monitoring Using Neural Network ModelingIEEE Transactions on Industrial Electronics, 2007
- A Computational Method to Robust Vibration Control of Vehicle Engine-Body System using Haar WaveletsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Multiple Discriminant Analysis and Neural-Network-Based Monolith and Partition Fault-Detection Schemes for Broken Rotor Bar in Induction MotorsIEEE Transactions on Industrial Electronics, 2006
- Descriptor observer approaches for multivariable systems with measurement noises and application in fault detection and diagnosisSystems & Control Letters, 2006
- State/noise estimator for descriptor systems with application to sensor fault diagnosisIEEE Transactions on Signal Processing, 2006
- Pattern recognition-a technique for induction machines rotor broken bar detectionIEEE Transactions on Energy Conversion, 2001
- Wavelet-based system identification for nonlinear controlIEEE Transactions on Automatic Control, 1999