Author : Clayton Alan Cooper
Publisher :
ISBN 13 :
Total Pages : 45 pages
Book Rating : 4.:/5 (116 download)
Book Synopsis Milling Tool Condition Monitoring Using Acoustic Signals and Machine Learning by : Clayton Alan Cooper
Download or read book Milling Tool Condition Monitoring Using Acoustic Signals and Machine Learning written by Clayton Alan Cooper and published by . This book was released on 2019 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this research is to further document and bring feasibility to milling tool condition monitoring using acoustic signals. In order to accomplish this objective, a sound signal model is developed which characterizes the acoustic signals of the milling process. Using this model, two machine learning methods are developed to detect tool wear. One method utilizes data from all tool wear classes available for learner training and the other utilizes only a single class for training. The latter technique solves a data availability issue regarding running milling machines under suboptimal conditions, which is discussed herein. Each machine learning model is shown to be effective at tool wear detection tasks.This research demonstrates the power of machine learning in acoustic tool condition monitoring and makes significant novel contributions to the field. This research demonstrates the feasibility of the monitoring technique and lays a groundwork for future work in the field.