Abstract
In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.
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Supported by the National High-Tech Research and Development Plan (863) of China (No.2006AA01Z232, No.2009AA01Z212, No.200901Z202), the Natural Science Foundation of Jiangsu Province (No. BK2007603), High-Tech Research Plan of Jiangsu Province (No.BG2007045), Research Climbing Project of NJUPT (No.NY2007044) and Foundation of Nanjing University of Information Science and Technology(No.20070025).
Communication author: Xu Zhanyang, born in 1975, male, Ph.D. candidate, lectorate.
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Xu, Z., Zhan, C. & Zhang, S. A new non-invasive method for valve stiction dection using wavelet technology. J. Electron.(China) 26, 673–680 (2009). https://doi.org/10.1007/s11767-009-0017-3
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DOI: https://doi.org/10.1007/s11767-009-0017-3