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PUBLICATIONS

A Module-Based Software System for Spindle Condition Monitoring

Published

Author(s)

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

Abstract

Accurate identification of spindle working conditions is one of the key features of next generation smart machining systems with built-in, self-diagnosis capability. This paper presents a module-based software system designed to facilitate online spindle condition monitoring, in which the capability of effective and efficient spindle defect identification and localization has been realized through an analytic wavelet envelope spectrum algorithm. The software is designed in accordance with the architectural structure of OSA-CBM, and implemented using the graphical programming language of LabVIEW. It presents the spindle working conditions in two types of windows: a simplified spindle condition display window for machine operators and an advanced diagnosis window for machine experts. The software provides a user-friendly human-machine interface and contributes directly to the development of a new generation of smart machine tools.
Citation
International Journal of Mechatronics and Manufacturing Systems
Volume
2
Issue
5/6
Pub Type
Journals

Download Paper

Local Download

Keywords

Analytic Wavelet, Modular Software Design, OSA/CBM Architecture, Smart Machining System, Spindle Condition Monitoring, Stochastic Subspace Identification

Citation

Lee, K. , , R. , , R. and , L. (2009), A Module-Based Software System for Spindle Condition Monitoring, International Journal of Mechatronics and Manufacturing Systems, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=901589 (Accessed October 11, 2025)

Issues

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Created April 15, 2009, Updated February 19, 2017
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