Research Article | OPEN ACCESS
Fault Diagnosis of Multilevel Cascaded Inverter Using Multi Layer Perceptron Network
1E. Parimalasundar and 2N. Suthanthira Vanitha
1Department of Electrical Engineering, Anna University, Chennai, India
2Department of Electrical and Electronics Engineering, Knowledge Institute of Technology, Salem, India
Research Journal of Applied Sciences, Engineering and Technology 2015 5:336-345
Received: September 07, 2014 | Accepted: October 11, 2014 | Published: February 15, 2015
Abstract
In this study, a fault diagnostic system in a multi-level inverter using a MLP network is developed. Using a mathematical model, it is difficult to diagnose a Multilevel-Inverter Drive (MLID) system, because MLID system complexity has a non-linear factor and it consist of many switching devices. Therefore neural network classification is applied to fault diagnosis of MLID system. Multilayer perceptron networks (MLP) are used to identify the type and location of occurring faults from inverter output voltage measurement. Here, MLP network based fault identification system for five level cascade H-bridge Multilevel Inverter (MLI) is analyzed. The proposed system identifies the fault with a greater accuracy and the results to various input patterns are presented for easy comprehension.
Keywords:
Cascade H-bridge inverter, multi layer perceptron, multilevel inverter, neural network,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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