Cutting process diagnostics utilising a smart cutting tool

B. K. Min; G. O'Neal; Y. Koren; Z. Pasek

doi:10.1006/mssp.2001.1453

Cutting process diagnostics utilising a smart cutting tool

B. K. Min, G. O'Neal, Y. Koren, Z. Pasek

Department of Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

A new sensorised boring tool has been developed to enhance the flexibility and precision of line boring processes. A position sensor and tool tip actuator to control and its controller electronics were integrated into a cutting tool. To take further advantage of this highly sophisticated tool, a process diagnostic method based on cutting force measurement method was developed. An observer implemented in the tool controller estimates the disturbance to the actuator using the tool position sensing information. The estimated disturbance is the same as cutting force applied to the tool tip. The algorithm utilising the cutting force to detect cutting process faults, such as tool tip breakage and misalignment of workpiece has been designed and tested experimentally.

Original language	English
Pages (from-to)	475-486
Number of pages	12
Journal	Mechanical Systems and Signal Processing
Volume	16
Issue number	2-3
DOIs	https://doi.org/10.1006/mssp.2001.1453
Publication status	Published - 2002 Mar

Bibliographical note

Funding Information:
The research was sponsored in part by the ERC for Reconfigurable Machining System under NSF grant # EEC-9529125. The Smart Tool research presented in this paper was sponsored in part by NIST ATP grant # 70NANB5H1158. The authors appreciate the support of Dr Phil Szuba from Lamb Technicon.

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Civil and Structural Engineering
Aerospace Engineering
Mechanical Engineering
Computer Science Applications

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10.1006/mssp.2001.1453

Cite this

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note = "Funding Information: The research was sponsored in part by the ERC for Reconfigurable Machining System under NSF grant # EEC-9529125. The Smart Tool research presented in this paper was sponsored in part by NIST ATP grant # 70NANB5H1158. The authors appreciate the support of Dr Phil Szuba from Lamb Technicon.",

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Cutting process diagnostics utilising a smart cutting tool

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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