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Fault detection in milling, using parameter estimation and classification methods

Konrad, Heiko (1996)
Fault detection in milling, using parameter estimation and classification methods.
In: Control Engineering Practice, 4 (11)
doi: 10.1016/0967-0661(96)00172-4
Article, Bibliographie

Abstract

In this paper a new method of fault detection in milling is reported. Based on measured cutting forces, model parameters are estimated for each insert of the milling cutter. Using a classifier, the patterns of these estimated parameters are processed further, and the state of the milling process is determined. The method was first tested with simulated data, and then verified with measurements on a machining center.

Item Type: Article
Erschienen: 1996
Creators: Konrad, Heiko
Type of entry: Bibliographie
Title: Fault detection in milling, using parameter estimation and classification methods
Language: English
Date: 1 November 1996
Publisher: Elsevier
Journal or Publication Title: Control Engineering Practice
Volume of the journal: 4
Issue Number: 11
DOI: 10.1016/0967-0661(96)00172-4
Abstract:

In this paper a new method of fault detection in milling is reported. Based on measured cutting forces, model parameters are estimated for each insert of the milling cutter. Using a classifier, the patterns of these estimated parameters are processed further, and the state of the milling process is determined. The method was first tested with simulated data, and then verified with measurements on a machining center.

Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik
Date Deposited: 19 Nov 2008 16:00
Last Modified: 20 Jul 2023 12:18
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