Signal Analysis of Magnetic Control Seam Tracking Based on the Hilbert-Huang Transform

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Abstract:

According to the fact that the nonlinear magnetic control welding signal is not smooth, this paper proposes a signal extraction and an analytical method of the system based on Hilbert-Huang transform magnetic control arc seam tracking sensor. First, the magnetic control to track the signal motivated by cycle is decomposed into several intrinsic mode functions from high frequency to low frequency component by using the empirical mode decomposition. On the basis of the Hilbert marginal spectrum of each component, distribution of time-frequency transform to each component can effectively restrain cross terms and extract the real-time signal dynamic law reflecting magnetic control seam tracking. This method used in a certain experimental platform for magnetic control arc welding seam tracking sensor platform signal analysis, has produced a good effect and extracted the seam tracking signal, which can offer more valuable information and help to further reveal the frequency and spectrum characteristics of various interference sources in the weld automatic tracking system. Furthermore, It also provides a theoretical basis for establishing the welding signals with excitation source as well as a new nonlinear model.

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559-563

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Yuenong. Fei: Basic theory of arc sensor and research of weld seam tracking system( Tsinghua University Publications, Beijing1990).

Google Scholar

[2] Jiluan. Pan : Modern Welding Control(Mechanical Industry Publications, Beijing 2000).

Google Scholar

[3] Shen Yi, Shen Zhiyuan. A new adaptive nonlinear non-stationary signal processing method - the Hilbert-Huang transform overview: the development and application. Techniques of Automation and Applications. 2010; 29 (5): 1-5.

Google Scholar

[4] Hong Bo, Wei Fuli, Lai xin. etc. A magnetic control arc used in seam tracking sensor . Journal of welding, 2008, 29 (5): 1-4.

Google Scholar

[5] Huang N. E, Shen Z, Long S. R: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 1998, 454(1971).

DOI: 10.1098/rspa.1998.0193

Google Scholar

[6] Zhao H. W, Huang N.E. Ensemble empirical mode decomposition: A noise assisted data analysis method. Advances in Adaptive Data Analysis,2009,1(1):1—41.

DOI: 10.1142/s1793536909000047

Google Scholar

[7] Yang J. N, Lei Y. Identification of natural frequencies and damping ratios of linear structures via Hilbert transform and empirical mode decomposition. Proc. of International Conference on Intelligent Systems and Control, IASTED/Acta press, Anaheim, CA, 1999: 310-315.

Google Scholar