SmartWavAudit: smart technologies for electrical waveform auditing

Reliability of power generators, distribution systems and motors are essential in ensuring the efficient and reliable operation of industrial manufacturing systems. However, different types of machine health threats (fault or attack) may occur. There may be direct or inderict attacks and different types of short circuit faults for the electric devices such as single phase faults, phase to phase faults, three phase faults that occur inside the machine, close to the terminal of the machine or on the distribution lines supplying power to the machine. These different kinds of faults will impact the electrical waveforms for quantities such as voltage, current, power, and frequency across the network. These waveforms, measured with strategically placed sensors, can then be used for fault detection, localization purposes, and root cause analysis. Intelligent Automation Inc. (IAI), along with STTR partner University of Kentucky, proposes to utilize a combination of signal processing, time series analysis, machine learning, and bus impedance/ optimization-based methods to investigate the relationship between patterns in raw and transformed waveform data and different kinds of electrical faults and attacks and to prototype an automated detection and classification engine.