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Introduction

The use of advanced signal processing tools and techniques in the electrical machines and power electronics condition monitoring area has drawn the attention of many researchers over recent years. Conventional diagnosis techniques relying on classical tools such as the Fast Fourier Transform are being complemented, or even replaced in some cases, by new methods based on modern signal processing tools suited for the analysis of non-stationary signals. These methods can be used for the analysis of transients in electrical machines and are often advantageous compared to traditional techniques. In particular their use is rapidly increasing for diagnosing variable speed drive (VSD)-fed machines due to the special suitability of these techniques in such applications.

This is partially due to the fact that these modern signal processing techniques provide reliable patterns related to the failure (sometimes under the form of an image), able to be automatically detected by advancedpattern recognition algorithms. This fact makes them ideal for their possible implementation in condition monitoring devices. This special session is intended to attract research papers showing novel applications of these signal analysis techniques in the electric machines and power electronics condition monitoring area. The scope also covers papers including applications of pattern recognition algorithms or image processing techniques for diagnostic or prognostic purposes both in electrical machines and drives.

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Submission Topics

Topics of the Session

  • Time-frequency decomposition tools

  • Pattern recognition algorithms

  • Signal analysis techniques

  • Image processing tools

  • Classification methods

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Important Date
  • Conference Date

    Oct 29

    2017

    to

    Nov 01

    2017

  • Nov 01 2017

    Registration deadline

Sponsored By
IEEE工业电子学会
Organized By
Institute of Automation, Chinese Academy of Sciences
Southeast University
School of Mathematics and Systems Science, Chinese Academy of Sciences
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