Acoustic-emission and force sensor fusion for monitoring the cutting process
Erdal Emel,Elijah Kannatey-Asibu +1 more
TLDR
In this paper, an acoustic emission and force-based sensor fusion system involving pattern recognition analysis has been used to detect tool breakage, chip form and a threshold level of tool flank wear in turning.About:
This article is published in International Journal of Mechanical Sciences.The article was published on 1989-01-01 and is currently open access. It has received 38 citations till now. The article focuses on the topics: Tool wear & Cutting tool.read more
Citations
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Journal ArticleDOI
A brief review: acoustic emission method for tool wear monitoring during turning
TL;DR: A review of acoustic emission (AE)-based tool wear monitoring in turning is presented in this article, where the main contents included: 1. AE generation in metal cutting processes, AE signal classification, and AE signal correction, and 2. AE signal processing with various methodologies, including time series analysis, FFT, wavelet transform, etc.
Journal ArticleDOI
Hidden Markov model-based tool wear monitoring in turning
TL;DR: Experimental results show that successful tool state detection rates as high as 97% can be achieved by using the proposed new modeling framework for tool wear monitoring in machining processes using hidden Markov models.
Journal ArticleDOI
Modelling of tool wear based on cutting forces in turning
TL;DR: In this paper, a development of mathematical models to describe the wear-time and wear-force relationships for turning operation is presented, and the results show that the ratio between force components is a better indicator of the wear process, compared with the estimate obtained using absolute values of the forces.
Journal ArticleDOI
The Application of an ANFIS and Grey System Method in Turning Tool-Failure Detection
TL;DR: In this paper, the results of the application of an adaptive-network-based fuzzy inference system (ANFIS) for tool-failure detection in a single-point turning operation are described.
Journal ArticleDOI
Micro-end-milling—III. Wear estimation and tool breakage detection using acoustic emission signals
TL;DR: In this paper, the authors proposed a tool breakage detection and wear estimation method using acoustic emission (AE) signals using adaptive resonance theory and Abductory Induction Mechanism (AIM).
References
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Journal ArticleDOI
The Fundamental Geometry of Cutting Tools
TL;DR: In this article, a full geometrical analysis of a cutting tool edge is made, in which an effective rake of universal application is defined in terms of the primary rake and the angle of obliquity of the edge.
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