Math Modeling Seminar: Monitoring Health of Large Machine Diagnostics Using Machine Learning
Math Modeling Seminar
Monitoring Health of Large Machine Diagnostics Using Machine Learning
Dr. Marylesa Howard
Scientist / Mathematician
Nevada National Security Site
National Nuclear Security Administration
You may attend this lecture in person at 2305 Gosnell Hall or virtually via Zoom.
If you’d like to attend virtually, you may register here for Zoom link.
Abstract:
The Department of Energy employs scientists, engineers, mathematicians, and technicians to work on problems ranging from renewable energy resources to global climate change. However, unbeknownst to many people is the fact that the Department of Energy is also the nation’s overseer of our nuclear weapons program. Experiments are designed and executed at the Nevada National Security Site to support the mission: ensuring the safety, security, and reliability of our nation’s nuclear stockpile. Regularly maintained and operated diagnostic machines are a backbone of data collection. Component failures can result in catastrophic downtime for the diagnostic, affecting schedules, cost, and performance. In this presentation, we will share our research into building models to monitor performance of large machine diagnostics using various measurements, like electrical current and voltage at multiple points on the path of the machine, from which we anticipate the ability to assess health, observe declining performance, and predict failures.
Intended Audience:
Undergraduates, graduates, and experts. Those with interest in the topic.
The Math Modeling Seminar will recur each week throughout the semester on the same day and time. Find out more about upcoming speakers on the Mathematical Modeling Seminar Series webpage.
To request an interpreter, please visit myaccess.rit.edu
Event Snapshot
When and Where
Who
This is an RIT Only Event
Interpreter Requested?
No