The application discloses a
power quality disturbance
feature extraction method and
system based on segmented multi-resolution
S transform, relates to the technical field of
power quality monitoring, and aims to solve the problem that traditional time-
frequency analysis methods are difficult to accurately capture
power quality disturbance features in different frequency bands due to fixed resolution. The application comprises establishing a
mathematical model of power quality disturbance signals, including various single and composite disturbance models; discretizing the signals based on continuous
S transform and applying one-dimensional discrete
S transform; dividing the frequency bands into three segments, i.e., low, medium and high, according to disturbance frequency characteristics; introducing a
Gaussian window function with different adjustment factors into each
frequency band to adaptively adjust the time-
frequency resolution; combining S transform with the
window function to obtain a discrete expression of segmented multi-resolution S transform; and extracting disturbance feature parameters based on the time-
frequency matrix obtained through transformation. The technical scheme realizes
adaptive optimization of time-
frequency resolution, and improves the extraction accuracy and reliability of complex power quality disturbance features.