Electrical signature analysis (ESA) is a prognostic tool used to assess the performance and health of electric machine systems, including power quality and powertrain, by analyzing voltage and current waveforms. Originally developed by Oak Ridge National Labs (ORNL) to detect electric motor, bearing, and gear wear in motor-operated valves, ESA has evolved to evaluate electrical and mechanical conditions in all types of equipment that involve the interaction of magnetic fields.
This article focuses on the specific application of ESA in doubly fed induction generators (DFIG),
wind turbine generators, and powertrains that make up over 80% of the more than 73,000 active
turbines in the USA generating over 152 GigaWatts of power.
Posted inAlternative Energy Artificial Intelligence Data Science Electric Machine energy efficiency expert system infrastructure Internet of Things Machine Learning Power Power Quality Remaining Useful Life Time to Failure Estimation Uncategorized
NETA Article Evaluating Wind Turbines with Electrical Signature Analysis
