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TECHNICAL PAPERS

A Diagnostic Approach for Turning Tool Based on the Dynamic Force Signals

[+] Author and Article Information
S. E. Oraby1

Department of Production and Mechanical Design, Faculty of Engineering, Suez Canal University, Port Said, Egyptsoraby@paaet.edu.kw

A. F. Al-Modhuf

Department of Mechanical Production and Technology, College of Technological Studies, PAAET, P.O. Box 42325, Shuwaikh 70654, Kuwait

D. R. Hayhurst

Department of Mechanical, Aerospace and Manufacturing Engineering, UMIST, P.O. Box 88, Sackville Street, Manchester M60 1QD, UK

1

On leave. Presently at the Department of Mechanical Production Technology, College of Technological Studies, PAAET, P.O. Box 42325, Shuwaikh 70654, Kuwait.

J. Manuf. Sci. Eng 127(3), 463-475 (Sep 01, 2004) (13 pages) doi:10.1115/1.1948397 History: Received February 04, 2004; Revised September 01, 2004

In the current work it is proposed a simple, and fast softwired tool wear monitoring approach, based upon the features of the time series analysis and the Green’s Function (GF) features. The proposed technique involves the decomposition of the force signals into deterministic component and stochastic variation-carrying component. Then, only the stochastic component is processed to detect the adequate autoregressive moving average (ARMA) models representing the tool state at every wear condition. Models are further reduced to form a more representative parameter, the “Green’s Function (GF).” This reflects the dynamic behavior of the tool prior to failure and, may provide a comprehensive and accurate measure of the damping variation of the cutting process subsystem at different forms of tool’s edge wear. As wear enters the high rate region, the cutting process is forced toward the instability domain where it tends to have less damping resistance. It is also explained how a system response surface can be generated based on its Green’s function. It is proposed that this concept can be the basis for a diagnostic technique for use with many systems.

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Copyright © 2005 by American Society of Mechanical Engineers
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Figures

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Figure 1

Experimental set up and signal processing procedures

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Figure 2

Wear-time curve and cutting conditions

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Figure 3

Recorded dynamic force signals

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Figure 4

Tool dynamic characteristics under wear variation of Green’s function within a domain of 100 disturbances (j=1–100)

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Figure 5

Three-dimensional global view of dynamic characteristics of the whole test, variation of Green’s function with 100 disturbances

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Figure 6

Response generation using Green’s function with periodical impacts

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Figure 7

Response generation using Green’s function with random impacts

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Figure 8

3D response surface of the whole test using Green’s function with random impacts

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