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Creating Self-Aware Low-Voltage Electromagnetic Coils for Incipient Insulation Degradation Monitoring for Smart Manufacturing
Author(s) -
Kai Wang,
Haifeng Guo,
Aidong Xu,
Noel Jordan Jameson,
Michael Pecht,
Bingjun Yan
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2880266
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The degradation of key components of production equipment can have adverse effects on manufacturing, such as unexpected machine shutdown and product quality decline. Implementation of selfaware components by prognostics and health management-based cyber-physical systems is a promising technology that can address this problem. This paper developed a precursor-based prognostics method to create self-aware low-voltage electromagnetic coils for incipient insulation degradation monitoring. Electromagnetic coils are fundamental energy conversion and transformation components of a variety of machines, such as electric motors and solenoid valves, and their insulation failure can cause catastrophic effects. Conversion of sensory data to insulation health information and development of a component/cyberinterface for integrating insulation health information to cyberspace are described. This method presents opportunities for companies to develop transparency and thus predictive maintenance of machines that incorporate electromagnetic coils.

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