Identification of mining steel rope broken wires based on improved EEMD Online publication date: Mon, 15-Aug-2016
by Tie-Zhu Qiao; Zhao-Xing Li; Bao-Quan Jin
International Journal of Mining and Mineral Engineering (IJMME), Vol. 7, No. 3, 2016
Abstract: Metal magnetic memory (3M), which is used to evaluate the stress concentration and fatigue damage of ferromagnetic materials, belongs to a weak magnetic detection. When 3M technology is used to detect working steel rope, the detected signal contains lots of interfering signals to distort real signal. To improve signal to noise ratio (SNR), ensemble empirical mode decomposition (EEMD) is used to denoise the original signal. A new method of confirming white noise standard deviation (WNSD) added to EEMD has been proposed, which has a higher accuracy. Besides, a self-adaptive method of selecting intrinsic mode functions (IMFs) has been proposed. The method is used to denoise magnetic memory signal of steel rope metal and the result is better than other common denoising methods. After denoising the tested signal of steel rope, the broken wires field of the rope can be recognised by the normal component of 3M crossing zero point.
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