Development of Advanced Mathematical Morphology Algorithms and their Application to the Detection of Disturbances in Power Systems
Jiangmiao Zhu · University of Liverpool · 2018
This thesis is concerned with the development of Mathematical morphology (MM)-based algorithms and their applications to signal processing in power systems, including typical power quality disturbances such as low frequency oscillations (LFO) and harmonics. Traditional morphological operators are extended to advanced ones in the thesis, including multi-resolution morphological gradient (MMG) algorithms, envelope extraction morphological filters (MF), LFO extraction MF and convolved morphological filters (CMF). These advanced morphological operators are applied to the detection and classification of power disturbances, detection of continuous and damped LFO, and the detection and removal of harmonics in power systems.