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Vol. 94, Issue 7, July 2008, pp.150-160




Intelligent Sensing in Inverter-fed Induction Motors: Wavelet-based Symbolic Dynamic Analysis


1Rohan SAMSI, 2Asok RAY

1Primarion Inc., 2780 Skypark Drive, Suite 100

Torrance, CA 90505, USA

E-mail: rohan.samsi@primarion.com

 2The Pennsylvania State University, 329 Reber Building

University Park, PA 16802, USA

E-mail: axr2@psu.edu http://www.mne.psu.edu/Ray



Received: 10 June 2008   /Accepted: 21 July 2008   /Published: 31 July 2008


Abstract: Wavelet transform allows adaptive usage of windows to extract pertinent information from sensor signals, and symbolic dynamic analysis provides coarse graining of the underlying information for enhanced computational speed and robustness of sensor-data-driven decision-making. These two concepts are synergistically combined for real-time intelligent sensing of faults whose signatures are small compared to coefficients of dominant frequencies in the signal. Feasibility of the proposed intelligent sensing method is demonstrated on an experimental apparatus for early detection of rotor bar breakage in an inverter-fed induction motor.


Keywords: Wavelet Analysis; Symbolic Analysis; Induction Motors; Fault Detection


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