Detection and Classification of Short Transients and Interruption using Hilbert Transform
Widespread use of electronics from home appliances to the control of more sophisticated and costly industrial processes has raised the awareness of power quality. Power quality disturbance is generally defined as any change in power (voltage, current, or frequency) that interferes with the normal operation of electrical equipment. The study of power quality and ways to control is a major concerned for electric utilities, large industrial companies, businesses, and even home users. The study has intensified due to equipment have become increasingly sensitive to even minute changes in the power supply voltage, current, and frequency. In electrical energy power networks, disturbances can cause problems in electronic devices so their monitoring is very fundamental. In this paper, we address the problem of disturbance detection by using Hilbert transform which is employed as an effective tool for tracking the voltage waveforms in electrical distribution systems. In addition to this classification of disturbance is carried out by using cross correlation technique. Simulation results obtained shows the accuracy and flexibility of Hilbert transform in detecting the time instants during which the disturbance has occurred. This has been tested for oscillatory transients, interruption and multiple event interruption and sag.
