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.
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