Internet of Things Partial Discharge Detection (PD) System

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One of the main challenges many researchers face is the availability of testbeds and data for training and testing machine learning (ML) models. We use ML models in my research lab to assess and predict the health of electrical power assets such as high voltage (HV) transformers and generators. We are particularly interested in detecting and predicting partial discharge (PD) activities in HV transformers. In the past, we used simulations and artificial data to perform PD analysis and prediction. However, these approaches are considered unrealistic because they rely on synthetic data. The main objectives of the proposed international collaboration are to 1) Establish an international research partnership with Dr. Brian Stewart in PD detection and prediction systems, 2) Understand the requirements and practical limitations of PD data collection systems, and 3) Design a prototype PD data acquisition. The proposed research collaboration will help in attracting interest from Canadian power industries and utilities to support funding research projects to develop real-time PD systems. This will occur by submitting joint funding grants with the collaborator and the industrial partners. These systems will help local industries establish a presence in power equipment manufacturing and help establish Canada as a global leader in innovative smart grid technologies.