A systematic fuzzy rule based approach for fault classification in transmission lines

The paper presents a new approach for fault classification in transmission line using a systematic fuzzy rule based approach. Fault classification is one of the important requirements in distance relaying for identifying the accurate phases involved in the fault process. The proposed technique starts with preprocessing the fault current signal using advanced time–frequency transform such as S-transform to compute various statistical features. After the required features are extracted, the Decision Tree (DT), a knowledge representation method, is used for initial classification. From the DT classification boundaries, the fuzzy membership functions (MFs) and corresponding fuzzy rule-base is developed for final classification. Thus a systematic fuzzy rule base is developed for fault classification, reducing the redundancies and complexities involved compared to Heuristic fuzzy rule-based approach. Also a qualitative comparison is made between S-transform and Wavelet transform, where S-transform based DT-fuzzy provides highly improved results compared to the later during simulation as well as experimental tests.

Figure optionsDownload as PowerPoint slideHighlights
► A systematic and compact fuzzy classifier for fault classification is proposed.
► DT-induced–fuzzy rule base provides the systematic if-then rules.
► Similarity measure reduces the complexity and redundancies.
► Real coded GA fine tunes the fuzzy MFs for generalizing the complete rule base.