A module-based software system for spindle condition monitoring. (4th September 2009)

• Record Type: Journal Article
• Authors: Yan, Ruqiang; Gao, Robert X.; Zhang, Li; Lee, Kang B.
• Is Part Of: International journal of mechatronics and manufacturing systems. Volume 2:Number 5/6(2009)
• Page Start: 532
• Page End: 551
• Publication Date: 2009-09-04
• Subjects: modular software design -- OSA-CBM architecture -- spindle monitoring -- condition monitoring -- analytic wavelets -- SSI -- stochastic subspace identification -- smart machining systems -- self-diagnosis -- online defect identification -- defect localisation -- human-machine interface -- HMI -- smart machine tools; Mechatronics -- Periodicals; 629.89
• Languages: English
• ISSNs: 1753-1039

Abstract

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.