A Statistical Feature-Based Transmission Fault Identification and Classification

This paper presents an efficient algorithm for diagnosing the transmission faults using analytical techniques. An on-site dataset is used in this work. Statistical tools have been adapted to determine the feature set extracted from line current Perk’s vector modulus. Fuzzy logic is incorporated for the classification of faulty and healthy conditions. From the confusion matrix, it is proven that this algorithm has been proven to be accurate as it results accurate values in almost all the cases (>95%).