Abstract
The permanent magnet synchronous (PMS) type Induction motor is utilized as a part of most of the modern applications. Induction motors use the majority of the electrical energy. The fundamental explanation behind the utilization of the PMS motor is its consistent quality and effortlessness of operation. A PMS motor’s full load effectiveness is higher than different sorts of an induction motor. Furthermore, in this manner, it’s essential to monitor the execution of the PMS motor without changing its working. In this work, presents another propelled innovation in which embedded framework is coordinated into the remote sensor network given stochastic rule control (SRC) technique. Amid this procedure, distinctive sensors have associated with the motor, and the qualities are extricated utilizing a microcontroller. It’s at that point transmitting to the base station through remote correspondence, and at the base station, a graphical user interface with cloud server (IoT) given which provide the client can interface with the framework by using SRC algorithm. The proposed SRC based induction motor control system is validated through simulation in Matlab_2013a Simulink environment. A hardware setup is also developed to validate the simulation. Overall 95% efficiency is achieved at full load condition based on the proposed SRC algorithm.
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Hsiao, C.-H., & Liu, M.-K. (2017). Failure mode analysis of induction motor model. In International conference on applied system innovation (ICASI), 2017, pp. 25–28.
Patil Dattraj, N., Khatal Hannant, D., & Kumbhar Vikram, R. (2017). Protection and monitoring of single phase induction motor with RPM detector. Resincap International Journal of Science & Engineering, 1(5), 2808–2811.
Khant, A. A., Khachar, C. V., Kandoriya, J. K., & Solanki, K. M. (2017). Controlling and performance analysis of induction motor using GSM module. International Journal of Engineering Development and Research, 1257–1260.
Ugale, R. T., & Chavhan, K. B. (2016). Web-based automated electric machine test-bench with data acquisition and remote control. In IEEE international conference on power electronics, drives and energy systems (PEDES), 2016, pp. 1279–1293.
Sandip, R. A., Manisha, K., Kaustubh, K., & Harshda, S. (2017). Wireless electrical motor parameter monitoring system for three phase induction motor prof. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering ISO 3297:2007 Certified, 5(5), 502–505.
Dinesh Kumar, R. (2017). Design and implementation of PLC-based monitoring control system for induction motor. International Journal of Advanced Science and Engineering Research, 1279–1293.
Venkata Ramana Naik, N., & Singh, S. P. (2016). A two-level fuzzy based DTC using PLLC to improve the induction motor performance. In IEEE international conference on power electronics, drives and energy systems (PEDES), pp. 1767–1769.
Mitra, S., & Koley, C. (2016). An automated SCADA based system for identification of induction motor bearing fault used in process control operation. In 2nd International Conference on Control, Instrumentation, Energy and Communication (CIEC), pp. 1556–1561.
Krishnara, K., & Vishnupriya, R. (2017). Induction motor control using android application. Asian Journal of Applied Science and Technology (AJAST), 1(3), 130–132.
Ben Brahim, S., Vuong, T. H., David, J., Bouallegue, R., & Pietrzak-David, M. (2015). Feasibility study of wireless communication for the double fed induction machine. In 12th international conference on fuzzy systems and knowledge discovery (FSKD), 2015, pp. 1706–1709.
Chavan, L., Chafekar, P., Bhatt, A., Patel, M., & Kuhikar, S. (2017). PIC based protection of single phase induction motor. International Advanced Research Journal of Science, Engineering and Technology, 389–392.
Elavenil, P. E., & Kalaivani, R. (2013). Overload protection and speed monitoring of induction motor using ZigBee wireless sensor networks and GSM technology. Power Electronics and Renewable Energy Systems, 2750–2753.
Arun, N., & Lakshmi Praba, N. (2013). Automatic speed and torque monitoring in induction motors using ZigBee and SMS. In IEEE international conference on emerging trends in computing, communication and nanotechnology (ICECCN), 2013, pp. 2486–2494.
Lima-Filho, A. C., Gomes, R. D., Adissi, M. O., da Silva, T. A. B., Belo, F. A., & Spohn, M. A. (2014). Embedded system integrated into a wireless sensor network for online dynamic torque and efficiency monitoring in induction motors. IEEE/ASME Transactions on Mechatronics, 1249–1252.
Pradeep, A., Thomas, E., & Kavya Mohan, K. A protection of induction motor from abnormal conditions using PLC. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2317–2322.
Misra, R., & Pahuja, G. L. (2015). An experimental study of rotor fault detection using motor current signature analysis based on neural networks. International Journal of Advanced Science and Technology, 79, 948–951.
Jose, G., & Jose, V. (2013). Induction motor fault diagnosis methods: A comparative study. In International conference on electrical engineering (ICEE—2013), July 6–7, 2013, Hyderabad, India international academic and industrial research solutions (IAIRS), pp. 863–866.
Lu, B., & Gungor, V. C. (2009). Online and remote motor energy monitoring and fault diagnostics using wireless sensor networks. IEEE Transactions on Industrial Electronics, 56(11), 4651–4659.
Baroni, P., Pillai, P., Chook, V. W. C., Chessa, S., Gotta, A., & Hu, Y. F. (2007). Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Computer Communications, 30(7), 1655–1695.
Salvadori, F., de Campos, M., Sausen, P. S., de Camargo, R. F., Gehrke, C., Rech, C., et al. (2009). Monitoring in industrial systems using wireless sensor network with dynamic power management. IEEE Transactions on Instrumentation and Measurement, 58(9), 3104–3111.
Willig, A. (2008). Recent and emerging topics in wireless industrial communications: some selection. IEEE Transactions on Industrial Informatics, 4(2), 102–124.
Gungor, V. C., & Hancke, G. P. (2009). Industrial wireless sensor networks: Challenges, design principles, and technical approaches. IEEE Transactions on Industrial Electronics, 56(10), 4258–4265.
Wei, H., Chen, Y., Tan, J., & Wang, T. (2011). Spambot: A self-assembly modular robot system. IEEE/ASME Transactions on Mechatronics, 16(4), 745–757.
Takahashi, J., Yamaguchi, T., Sekiyama, K., & Fukuda, T. (2009). Communication timing control and topology reconfiguration of a sink-free meshed sensor network with mobile robots. IEEE/ASME Transactions on Mechatronics, 14(2), 187–197.
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Geetha, E., Nagarajan, C. Stochastic Rule Control Algorithm Based Enlistment of Induction Motor Parameters Monitoring in IoT Applications. Wireless Pers Commun 102, 3629–3645 (2018). https://doi.org/10.1007/s11277-018-5397-y
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DOI: https://doi.org/10.1007/s11277-018-5397-y