@inproceedings{b674551727d9445bb59b9394b15c2066,
title = "Cost-efficient real-time condition monitoring and fault diagnostics system for BLDC motor using IoT and Machine learning",
abstract = "A cost-efficient condition monitoring and fault diagnostic system are presented in this paper using the Internet of Things and machine learning. Most condition monitoring systems nowadays are either costly or used to monitor current values without emphasizing the analysis part. On the other hand, predictive maintenance of different electrical machines, including BLDC motors, is becoming the need of the hour. It reduces the cost needed for maintenance and can also be used to evade more significant faults in the machine. The data is transmitted in real-time using a data acquisition system onto the cloud, which is further processed to determine if there is a chance of any fault occurring in the motor. A short comparison of the results of different machine learning algorithms is also discussed related to predictive maintenance.",
keywords = "condition monitoring, fault diagnostic, Internet of Things, IoT",
author = "Raja, {Hadi Ashraf} and Hardik Raval and Toomas Vaimann and Ants Kallaste and Anton Rassolkin and Anouar Belahcen",
note = "Funding Information: This research leading to these results has received funding from the PSG453, Digital twin for propulsion drive of autonomous electric vehicles” and ETAG21001, “Industrial internet methods for electrical energy conversion systems monitoring and diagnostics”. Publisher Copyright: {\textcopyright} 2022 IEEE.; International Conference on Diagnostics in Electrical Engineering, Diagnostika ; Conference date: 06-09-2022 Through 08-09-2022",
year = "2022",
doi = "10.1109/Diagnostika55131.2022.9905102",
language = "English",
series = "Diagnostika 2022 - 2022 International Conference on Diagnostics in Electrical Engineering, Proceedings",
publisher = "IEEE",
editor = "Pavel Trnka",
booktitle = "Diagnostika 2022 - 2022 International Conference on Diagnostics in Electrical Engineering, Proceedings",
address = "United States",
}