Kai Wang 1, Haifeng Guo1, Aidong Xu1, Bingjun Yan1, N. Jordan Jameson2, Michael G. Pecht2
1Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China and Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China.
2CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
The degradation of key components of production equipment can have adverse effects on manufacturing, such as unexpected machine shutdown and product quality decline. Implementing self-aware component by prognostics and health management (PHM) based cyber-physical systems (CPS) are promising technologies that can address this problem. Considering that electromagnetic coils are fundamental energy conversion and transformation components of a variety of machines, like electric motors and solenoid valves, and their insulation failure can cause catastrophic effects, a precursor-based prognostics method is proposed in this paper to create self-aware low-voltage electromagnetic coils for incipient insulation degradation monitoring. Sensory data to insulation health information conversion and component-cyber interface development for integrating insulation health information to cyber space are described, which present opportunities for developing transparency and thus predictive maintenance of machines that incorporate electromagnetic coils.