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A module-based software system for spindle condition monitoring

  • University of Connecticut
  • General Electric
  • Global Research Centre of the General Electric Corporation
  • National Institute of Standards and Technology

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

Accurate identification of spindle working conditions is one of the key features of the next generation smart machining systems with built-in, self-diagnosis capability. This paper presents a module-based software system for online spindle defect identification and localisation 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 LabVIEW. Spindle condition is displayed online in both a basic window for machine operators and a diagnosis window for advanced analysis. The software provides a user-friendly human-machine interface and contributes to realising a smart machine tool.

源语言英语
页(从-至)532-551
页数20
期刊International Journal of Mechatronics and Manufacturing Systems
2
5-6
DOI
出版状态已出版 - 9月 2009
已对外发布

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