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Strip Rupture Detection System of Cold Rolling Mill using Transient Current Signal  

Yang, S.W. (부경대학교 대학원)
Oh, J.S. (부경대학교 대학원)
Shim, M.C. (부경대학교 대학원)
Kim, S.J. (부경대학교 기계자동차공학과)
Yang, B.S. (부경대학교 기계자동차공학과)
Lee, W.H. ((주)포스코 기술연구원)
Publication Information
Journal of Power System Engineering / v.14, no.2, 2010 , pp. 40-47 More about this Journal
Abstract
This paper proposes a fault detection system to detect the strip rupture in six-high stand Cold Rolling Mills based on transient current signal of an electrical motor. For this work, signal smoothing technique is used to highlight precise feature between normal and fault condition. Subtracting the smoothed signal from the original signal gives the residuals that contains the information related to the normal or faulty condition. Using residual signal, discrete wavelet transform is performed and acquire the signal presenting fault feature well. Also, feature extraction and classification are executed by using PCA, KPCA and SVM. The actual data is acquired from POSCO for validating the proposed method.
Keywords
Cold Rolling Mill; Strip Rupture; Transient Analysis; Wavelet Transform; Feature Extraction; Fault Classification;
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