RF Plasma Generator Health Monitoring using Machine Learning

Location

James E. Gleason Hall - 2271

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Our project is a machine learning and deep learning approach to failure detection in RF plasma generators. Our project implements and evaluates a linear regression model, a Random Forest machine learning model, and a convolutional neural network (CNN) model. These are implemented on traditional PCs, an ARM processor, and a Xilinx FPGA.

Location

James E. Gleason Hall - 2271

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Topics

Exhibitor
Quinn Leydon
Arjun Thangaraju
Eric Hamm
rnp5285

Advisor(s)
Alan Dawson

Organization
Senior Design


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