Wavelet transform based fuzzy inference system for power quality classification
| dc.contributor.author | Tiwari A.K.; Shukla K.K. | |
| dc.date.accessioned | 2025-05-24T09:58:14Z | |
| dc.description.abstract | The paper presents a hybrid scheme using a Discrete Wavelet Transform and a Fuzzy Expert System for feature extraction and classification. The signal under test (electrical current or voltage for Power Quality study) is processed through a DWT decomposition block to generate the feature extraction curve. The DWT Level and Energy information from the feature extraction curve is then passed through a diagnostic module that computes the truth-value of the signal combination and determines the class to which the signal belongs. The proposed scheme is much simpler and powerful than currently available PQ classification schemes. © Springer-Verlag Berlin Heidelberg 2002. | |
| dc.identifier.doi | https://doi.org/10.1007/3-540-45631-7_21 | |
| dc.identifier.uri | http://172.23.0.11:4000/handle/123456789/23078 | |
| dc.relation.ispartofseries | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
| dc.title | Wavelet transform based fuzzy inference system for power quality classification |