alexa Arc Energy Characteristics Analysis of AC Square Wave Submerged Arc Welding using WVD
ISSN: 2168-9873

Journal of Applied Mechanical Engineering
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Research Article

Arc Energy Characteristics Analysis of AC Square Wave Submerged Arc Welding using WVD

www.omicsonline.org/archive-applied-mechanical-engineering-open-access.phpSi-Wen X1,3, Wang C1,2, Zhi-Peng Z1,2 and Kuan-Fang H1,2*
1College of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiantan 411201, PR China
2Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiantan 411201, PR China
3Hunan Provincial Key Laboratory of High efficiency precision cutting for Difficult-to-cut Material, Hunan University of Science and Technology, Xiangtan 411201, PR China
*Corresponding Author : Kuan-fang H
College of Mechanical and Electrical Engineering
Hunan University of Science and Technology
Xiantan 411201, PR China
Tel: 13875222691
E-mail: [email protected]
Received: February 13, 2016; Accepted: March 15, 2016; Published: March 18, 2016
Citation: Si-Wen X, Wang C, Zhi-Peng Z, Kuan-Fang H (2016) Arc Energy Characteristics Analysis of AC Square Wave Submerged Arc Welding using WVD. J Appl Mech Eng 5:204. doi:10.4172/2168-9873.1000204
Copyright: © 2016 Si-Wen X, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
 

Abstract

In process of AC square wave submerged arc welding, electric signal waveform determines the arc energy characteristics in the time and frequency domain, which also reflects the arc stability of welding process and quality indirectly. Using Wigner-Ville distribution (WVD), time frequency analysis is conducted to the current signal of AC square wave submerged arc welding. The Pseudo Wigner-Ville and smoothed Wigner-Ville distribution are discussed separately to suppress the cross-term interference. The numerical results indicate that the Choi-Williams kernel function has much superiority for time frequency analysis of the submerged arc welding electric signal. It can effectively suppress cross-term and eliminate noise in the Wigner-Ville distribution of welding electric signal, as well as owing the ability to portray the local feature of arc energy in AC square wave submerged arc welding.

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