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PUBLICATIONS

Design of a Real-time Spindle Health Monitoring and Diagnosis System  Based on Open Systems Architecture

Published

Author(s)

Li Zhang, Ruqiang Yan, Robert Gao, Kang B. Lee

Abstract

Accurate identification of spindle health in real time is an important feature of next generation smart machining systems that are capable of self-diagnosis. This paper presents a software design for an automated spindle health monitoring system based on open systems architecture. An analytic wavelet-based envelope spectrum algorithm is proposed and coded this in software for effective and efficient spindle degradation identification, defect localization, and damage growth tracking. The software is functionally adaptive and contributes directly to the development of a new generation of smart machine tools.
Conference Dates
March 13, 2007
Conference Location
Gaithersburg, MD
Conference Title
International Conference on Smart Machining Systems
Pub Type
Conferences

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Local Download

Keywords

Analytic Wavelet, Condition-Based Maintenance, Open Systems Architecture, Remaining Useful Life, Smart Machining Systems

Citation

Zhang, L. , Yan, R. , Gao, R. and Lee, K. (2007), Design of a Real-time Spindle Health Monitoring and Diagnosis System  Based on Open Systems Architecture, International Conference on Smart Machining Systems, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=823023 (Accessed October 17, 2025)

Issues

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Created March 13, 2007, Updated January 27, 2020
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