Real-Time Monitoring of Voltage Variations Using Mathematical Morphology

The monitoring of short-and long-duration root-mean-square voltage variations is still an open and demanding issue for academic and industrial fields. In this work, a methodology based on mathematical morphology operations such as dilation and erosion for monitoring of voltage variations is proposed. It consists of three stages: 1) denoising, 2) tracking and detection, and 3) final classification according to the IEEE Std. 1159. In order to validate and test the proposal, a set of synthetic and real signals is used, including the database of the IEEE work group P1159.3. The obtained results demonstrate the proposal effectiveness to detect and classify voltage variations, even when they are embedded in high-level noise. Finally, a hardware implementation based on a field programmable gate array (FPGA) is also developed as a system-on-a-chip (SoC) solution to offer an online and real-time monitoring of voltage variations, which is also possible thanks to the low complexity of the proposal.