IOT-Enabled Fault Diagnosis and Monitoring for Small Wind Turbine

¹ Department of EEE, St. Martin’s Engineering College, Secunderabad, Telangana, India - 500100
² Department of EEE, Vardhaman College of Engineering, Hyderabad, Telangana, India – 501218
³ Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India – 522302
⁴ Department of EEE, Anurag University, Hyderabad, Telangana, India – 500088

^* Corresponding Author: kv.govardhanrao@gmail.com

Abstract

Electrical energy is the most dependable form of energy. The advancement of technology demands substantial energy use. Conventional energy sources are producing pollution, and fossil fuels are diminishing daily, so paving the way for renewable energy sources. Wind energy is the most reliant renewable energy source. The maintenance of wind turbines is intricate, continuous monitoring is challenging due to their elevated positions, and they are situated in rural locations. A dependable condition monitoring system is crucial for turbines working on wind. to reduce downtime and enhance output. The objective of this project is to monitor the parameters of turbine working on wind and enhance early defect identification. Sensors are employed to assess the state of the wind turbine. The utilized sensors are a temperature sensor, a vibration sensor, and a voltage sensor. Should any sensor provide an anomalous value, the data is transmitted to the IoT cloud within a matter of seconds. This project utilizes an Arduino UNO and a Wi-Fi module. The Arduino UNO gathers sensor data from several wind turbine sensors, and the Wi-Fi module transmits this information to an IoT cloud application, such as Telegram, already loaded on our mobile devices. The operation of the kit and the performance evaluation have been conducted on the suggested system.