A Method for SDVV Detection and Classification Using Redundant Discrete Wavelet Transform

Short-duration voltage variations (SDVV) are events that require special attention in the power quality area, due to its frequent occurrence. Their constant monitoring is essential to diagnose their causes as well as to minimize their financial losses. Several methods of detecting and classifying SDVV were presented in the literature and, among the most used ones, the root mean square value and the discrete wavelet transform (DWT), stand out. Herein, the Redundant DWT (RDWT), a variant of DWT as well as a SDVV categorizing method are used. The analysis is performed by considering the samples number per cycle, and the window size, and it is validated by using real and simulated signals. The results indicated that the method is capable of not only detecting but also classifying the SDVV in various scenarios.