Condition Monitoring of Electrical Machines with Internet of Things
Document Type
Conference Proceeding
Publication Date
10-1-2018
Department
Electrical Engineering
Abstract
The Industrial Internet of Things (IIoT) has a potential of profound impact on the move toward smart manufacturing enterprises. The IIoT combines data collected from industrial sensors with machine-to-machine communications and automation technologies to enable smart enterprise control, asset performance management and informed operators. In condition based monitoring (CBM) process, the state of machinery is determined while in operation through a three step data management process. This includes data collection, processing, and assessment for maintenance decision-making and fault diagnostics and prediction. Electrical machines are widely used in industrial manufacturing processes. These machines can develop faults due to a variety of reasons. Traditionally, electromagnetic field monitoring, temperature measurements, noise and vibration monitoring and motor current signature analysis have been used to identify these faults. In this project, we focus on sensing vibration, temperature, current and voltage of the running electrical machines to monitor and analyze its condition. The data from sensors will be wirelessly transmitted to the cloud service for processing. The data will be downloaded from the cloud and analyzed to determine the condition of the machine. © 2018 IEEE.
DOI
10.1109/SECON.2018.8478989
Publication Title
Conference Proceedings - IEEE SOUTHEASTCON
ISBN
9781538661338
Recommended Citation
Barksdale, H., Smith, Q., & Khan, M. S. (2018). Condition monitoring of electrical machines with internet of things. Proceedings from SoutheastCon 2018: 1-4. doi: 10.1109/SECON.2018.8478989.