Early Fault detection in the main bearing of wind turbines based on Wireless sensor network

Abstract

Wind turbines are highly important in the field of renewable energy production, but the unforeseen breakdowns of components especially in the main bearings may cost a lot of downtime and money. The paper suggests a real-time fault detection system of wind turbine primary bearings with the help of a Wireless Sensor Network (WSN) with an embedded monitoring system. This system comprises of voltage, current, and temperature sensors as well as Arduino ATmega328 microcontroller to acquire and process real-time data. Following a controlled power supply is a steady operation of the system and the measured parameters are indicated on an LCD on-site and sent wirelessly to a remote monitoring device. A detection system is introduced that is based on a threshold to detect abnormal operating conditions including over current and excessive temperature increase. Experimental validation shows that the system is able to identify faults in real time, and produces early warning signals before the system breaks down in a critical state. This method is both economical, easy to apply and applies in a real world situation in health monitoring of wind turbines.