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

نویسندگان

  • Li Zhang
  • Ruqiang Yan
  • Robert X. Gao
  • Kang Lee
چکیده

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 waveletbased envelope spectrum algorithm is proposed and coded 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.

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تاریخ انتشار 2007