Compression method of electrical signals from rolling mills based on adaptive morphological wavelets
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摘要: 針對非線性、非平穩信號的數據壓縮問題,提出了一種基于自適應形態小波的軋機電氣信號壓縮方法.結合電氣信號的形態特征,采用中值算子作為形態小波的更新算子對信號進行分解,從而實現根據信號的局部形態特征,自適應地調整形態小波分解的更新算子.工業現場實際軋機電氣信號的數據壓縮實驗證明:利用這種形態小波信號壓縮方法,可以獲得高壓縮比的信號,并能保留信號的形態特征;同時,這種形態小波信號壓縮方法運算量小,可以應用到實時性要求較高的在線監測系統中.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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Key words:
- rolling mills /
- electrical signals /
- signal processing /
- wavelet decomposition /
- data compression
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