|SUBJECT:||M.S. Thesis Presentation|
|TIME:||Wednesday, April 21, 2021, 10:00 a.m.|
|PLACE:||Microsoft Teams, Online|
|TITLE:||The Effect of Sampling Rate and Signal-to-Noise Ratio on Methods for the Automated Determination of Sustained Maximum Amplitudes in Vibration Signals|
|COMMITTEE:||Dr. Christopher Saldana, Co-Chair (ME)
Dr. Katherine Fu, Co-Chair (ME)
Dr. Thomas Kurfess (ME)
Machine down time and productivity has been proven to benefit from machine health monitoring. A common approach is to observe vibration data for tasks such as anomaly detection. Vibration monitoring has also been integrated into other aspects of manufacturing such as tool wear detection. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration such as optical linear encoders in a manufacturing environment. When the optical linear encoder scanning head is vibrating in relation to the scale, positional errors are introduced, and in extreme cases, this causes a loss of position. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring where an accurate representation of the maximum sustained vibration is needed. To do this, techniques for determining sustained peaks in vibration signals need to be formalized and tested. This work fills this gap by testing six methods for detecting sustained vibration signals and determining the effects of sampling rate and the signal-to-noise ratio on each of them. Results from this thesis can be used to inform engineers on the most accurate methods for the automated monitoring of equipment sensitive to sustained vibrations.