Authors : AVIJIT BHOWMICK

Volume/Issue : Volume 6 - 2021, Issue 4 - April

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/3ngpWaS

Abstract : The Internet of Things (IoT) concept facilitates our life in many areas. One of the facilities provided in this area is undoubtedly condition monitoring. Unlike regular maintenance, IoT systems that perform continuous control operations can provide great advantages to the company with a warning that a serious failure will occur. It is a vital importance to determine defective bearings during the rotation of the power generating and power consuming machines without reaching the critical level. In this study, a setup was created, in two bearings (Driving end and non-driving end) of a coal screening machine and a Condition Monitoring (CM) was performed in the industry environment which could monitor temperature for defective bearing detection. Challenges: We cannot monitor vibration and acoustic parameter because of huge fluctuating vibration and noise of the coal screening machine. Also, we cannot use contactless/infrared temperature sensors due to full of dusty environmental air

Keywords : Internet of Things, Condition Monitoring, Machine Learning, Bearing, Coal screening, iLens.