Machine learning based data analysis and anomaly detection for high-voltage bushing health monitoring

POWER HV is a technology company focusing on carbon emission reduction. Through their sensor product, they help power plants increase the efficiency of the grid and improve its stability in challenging weather by tracking every single bushing and predicting a bushing failure. Exploiting the generated massive sensor data can contribute to an automatic and intelligent monitoring system. However, traditional data analysis methods fail to deal with large amounts of data with complex relationships. The emerging machine learning techniques enable us to analyze data efficiently and effectively. This project will apply state-of-the-art machine learning methods on the sensor network data to achieve data analysis and anomaly detection.

Faculty Supervisor:

Cheng Li

Student:

Partner:

Power HV (Manitoba)

Discipline:

Engineering

Sector:

Manufacturing

University:

Memorial University of Newfoundland

Program: