Condition Monitoring of Induction Motor Using Internet of Things (IoT)

In the era of globalization, manufacturing industries are facing intense pressure to prevent unexpected breakdowns, reduce maintenance cost and increase plant availability. Due to increasing trend of Internet of things (IoT), numerous sensors deployed around the world are developing at a rapid pace. In this paper, an IoT-based wireless control and monitoring system has been presented for determining the health of induction motor (IM). A module of sensors has been employed to monitor the different parameters, viz. current, voltage, temperature, and speed which were processed using microcontroller for analysis and display purposes. Further, the Ethernet module has been used for sending the information from the microcontroller to cloud (Cayenne) database for wireless remote monitoring and controlling of induction motor. The system has been implemented to monitor and control various parameters in real time, and also improving the detectability of different faults due to over limiting of the current, voltage, temperature, and speed values. The proposed system has significant potential in industrial environment with complex systems to economically monitor the condition of machine safely in real time.

[1]  S. S. Dhami,et al.  Non-contact sensor placement strategy for condition monitoring of rotating machine-elements , 2019, Engineering Science and Technology, an International Journal.

[2]  Corneliu Lazar,et al.  Vision-Guided Robot Manipulation Predictive Control for Automating Manufacturing , 2014, Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics.

[3]  Min Xia,et al.  Closed-loop design evolution of engineering system using condition monitoring through internet of things and cloud computing , 2016, Comput. Networks.

[4]  S. E. Zouzou,et al.  Static eccentricity fault diagnosis using the signatures analysis of stator current and air gap magnetic flux by finite element method in saturated induction motors , 2013, Int. J. Syst. Assur. Eng. Manag..

[5]  Arkady B. Zaslavsky,et al.  Context Aware Computing for The Internet of Things: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[6]  Dawn M. Tilbury,et al.  Real-Time Manufacturing Machine and System Performance Monitoring Using Internet of Things , 2018, IEEE Transactions on Automation Science and Engineering.

[7]  B. S. Pabla,et al.  Development of non-contact structural health monitoring system for machine tools , 2016 .

[8]  B. S. Pabla,et al.  The Vibration Monitoring Methods and Signal Processing Techniques for Structural Health Monitoring: A Review , 2016 .

[9]  S. L. Shimi,et al.  Condition Monitoring and Fault Diagnosis of Induction Motors: A Review , 2018, Archives of Computational Methods in Engineering.

[10]  Deepam Goyal,et al.  Optimization of condition-based maintenance using soft computing , 2016, Neural Computing and Applications.

[11]  Bong-Hwan Kwon,et al.  Online Diagnosis of Induction Motors Using MCSA , 2006, IEEE Transactions on Industrial Electronics.

[12]  B. S. Pabla,et al.  Condition based maintenance of machine tools—A review , 2015 .

[13]  Dieter Hayn,et al.  The Internet of Things for Ambient Assisted Living , 2010, 2010 Seventh International Conference on Information Technology: New Generations.