DOI: 10.14704/NQ.2022.20.15.NQ88009

Prognostic Health Monitoring of wind mill using Long Range Wide Area Network

Prof.Sushama Wankhade, Shilpa M. Satre, Dr. Reena Singh

Abstract

Renewable energy sector is prospering very rapidly. This indicates that more maintenance work and activities related to it, as well as handling it quickly would be necessary. IoT, a new and expanding industry, if collaborated with the area of renewable energy sources would be beneficial in monitoring the health condition of wind mills. Our primary purpose is to acquire sensor data for the maintenance of windmills, and transmit this data via GSM & LoRa (Long Range Module). LoRa was chosen because of its chirp spread spectrum and its ability to operate in areas with little to no internet coverage. We also aim is to acquire a precise computer vision-based system to identify exterior faults, such as crack identification in windmill blades, etc. The last assignment is to visualize all of the sensor data that was gathered using ThingSpeak

Keywords

Windmills, IoT, LoRa & GSM, ThingSpeak.

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