| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 567143 | Signal Processing | 2008 | 13 Pages |
Abstract
This paper presents a novel algorithm, morphological gradient wavelet (MGW), for the detection of power disturbances. MGW is a nonlinear wavelet transform that involves morphological operation in the decomposition process and presents the gradient information in the output. Applied to power systems, MGW extracts the features of disturbances and detects their location and duration. A variety of power disturbances have been simulated to evaluate the validity of MGW. Moreover, the advantages of the new algorithm are also addressed in comparison with Daubechies DB4 wavelet transform (DB4).
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
T.Y. Ji, Z. Lu, Q.H. Wu,