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Quality Assessment Using Antipatterns in Machine Building and Operations Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Assessment of Tool Wear Intensity Based on the Frequency Pattern

Authors : Anna Zawada-Tomkiewicz, Dariusz Tomkiewicz

Published in: Innovations Induced by Research in Technical Systems

Publisher: Springer International Publishing

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Abstract

The article is devoted to the issues of finishing machining, in which changes on the cutting edge significantly affect the quality of the machined surface. In tests EN 100Cr6 hardened steel has been used with a hardness of 60 HRC. The cutting tool material for turning tests were coated cemented carbides. Cutting parameters were selected so as not to exceed the permissible value of blade wear. The shortening of the tool has been evaluated from measurement of workpiece surface realized by stylus profilometer along the cutting length. This made it possible to obtain detailed information on blade wear over time. During cutting, the Fc, Ff and Fp components of the cutting forces were measured using a piezoelectric sensor and vibration signal was measured with a seismic sensor. The collected measurement data were then analyzed for diagnostic purposes using the Short Time Fourier Transform (STFT). First the stabilized process pattern was elaborated for one-second time windows. This pattern has been used to distinguish the excited states of the system including states of increased blade wear. Two wear intensity indicators have been determined for each of the recorded signals: mean deviation from the pattern and data dispersion. A moving average of wear intensity indicators has been applied for process state analysis.

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previous chapter Machine Learning Based Heuristic Technique for Multi-response Machining Process
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Metadata
Title
Assessment of Tool Wear Intensity Based on the Frequency Pattern
Authors
Anna Zawada-Tomkiewicz
Dariusz Tomkiewicz
Copyright Year
2020
Book
Innovations Induced by Research in Technical Systems

Print ISBN: 978-3-030-37565-2

Electronic ISBN: 978-3-030-37566-9

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-37566-9_4

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