Compression method of electrical signals from rolling mills based on adaptive morphological wavelets
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Abstract
A compression method of electrical signals from rolling mills based on adaptive morphological wavelets was proposed, aiming at the problem of data compression to nonlinear and non-stationary signals. In combination with the morphological characters of electrical signals, the median operator as an updating operator of morphological wavelets was chosen to decompose the signals, so the updating operator for morphological wavelet decomposition is adaptive with the partial morphological characters of the signals. Experimental results of signal compression to electrical signals from rolling mills in industrial environments show that the signals with high compression ratio are acquired and the morphological characters are reserved after processing by the morphological wavelet method. Because of simple calculations, the proposed compression method of electrical signals can be available for online real time monitoring systems.
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