A Principal Components Rearrangement Method for Feature Representation and Its Application to the Fault Diagnosis of CHMI

Zhuo Liu, Tianzhen Wang, Tianhao Tang and Yide Wang
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Zhuo Liu: Department of Electrical Automation, Shanghai Maritime University, Shanghai 201306, China
Tianzhen Wang: Department of Electrical Automation, Shanghai Maritime University, Shanghai 201306, China
Tianhao Tang: Department of Electrical Automation, Shanghai Maritime University, Shanghai 201306, China
Yide Wang: Institut d’Electronique et Télécommunications de Rennes, UMR CNRS 6164, Polytech Nantes, Rue Christian Pauc, BP 50609, 44306 Nantes CEDEX 3, France

Energies, 2017, vol. 10, issue 9, 1-15

Abstract: Cascaded H-bridge Multilevel Inverter (CHMI) is widely used in industrial applications thanks to its many advantages. However, the reliability of a CHMI is decreased with the increase of its levels. Fault diagnosis techniques play a key role in ensuring the reliability of a CHMI. The performance of a fault diagnosis method depends on the characteristics of the extracted features. In practice, some extracted features may be very similar to ensure a good diagnosis performance at some H-bridges of CHMI. The situation becomes even worse in the presence of noise. To fix these problems, in this paper, signal denoising and data preprocessing techniques are firstly developed. Then, a Principal Components Rearrangement method (PCR) is proposed to represent the different features sufficiently distinct from each other. Finally, a PCR-based fault diagnosis strategy is designed. The performance of the proposed strategy is compared with other fault diagnosis strategies, based on a 7-level CHMI hardware platform.

Keywords: fault diagnosis; feature representation; principal components rearrangement; cascaded H-bridge multilevel inverter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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