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Monitoring Health of Underground Mining Equipment
The research will entail modeling of diesel engine emissions to correlate with varying states of diesel engine operations so as to determine normal operating parameters. Using machine learning techniques, develop methods to analyze, alert and report on abnormal operating conditions when the vehicle is monitored in real time. The research will provide an important first step towards the development of a predictive maintenance system for underground mining equipment.
Faculty Supervisor:
Dr. Andrew Wong
Student:
Sepideh Seifzadeh
Partner:
Pattern Discovery Technologies
Discipline:
Engineering - computer / electrical
Sector:
Information and communications technologies
University:
University of Waterloo
Program:
Accelerate
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