Application of Adaptive Generalized Morphological Filter in Disturbance Identification for Power System Signatures

By analyzing basic operations of mathematical morphology (MM) digital filter and the selection of a structuring element (SE), an adaptive generalized morphological filter is presented to fast suppress noise. This new algorithm of the filter has more advantages of simplicity, convenience and flexibility than the conventional ways and has a brighter future in practical application. The filter is cascaded by basic morphological transforms and their combination forms with the same weight value and applied in processing on-line monitoring power system signatures to guarantee the accuracy of further fault diagnosis by higher signal-to-noise. Results of simulation show that the adaptive generalized morphological filter can suppress different kinds of white noises and pulse noises, restore the general regularity of the data effectively, and has better performance compared with single operation of morphological filter and other filtering approaches.