中文摘要：

针对非线性、非平稳信号的数据压缩问题，提出了一种基于自适应形态小波的轧机电气信号压缩方法．结合电气信号的形态特征，采用中值算子作为形态小波的更新算子对信号进行分解，从而实现根据信号的局部形态特征，自适应地调整形态小波分解的更新算子．工业现场实际轧机电气信号的数据压缩实验证明：利用这种形态小波信号压缩方法，可以获得高压缩比的信号，并能保留信号的形态特征；同时，这种形态小波信号压缩方法运算量小，可以应用到实时性要求较高的在线监测系统中．

英文摘要：

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.