An adaptive morphological lifting wavelet and its application on power disturbances detection

摘要

This paper presents a novel algorithm, named adaptive morphological lifting wavelet (AMLW). It is the first time to be applied for the detection of power quality disturbances (PQD). AMLW is a nonlinear wavelet transform which is based on morphological operation and the lifting scheme. The adaptability of AMLW lies in that the algorithm can select between two filters, the morphological gradient filter and average filter, to update the approximation signal based on the gradient information of the signal being analyzed in the decomposition process. A variety of power disturbances have been simulated to evaluate the validity of AMLW. Meanwhile, the advantage of AMLW is also addressed in comparison with traditional linear lifting scheme wavelet.