Fault diagnosis of wind turbine bearing using wireless sensor networks

Abstract

This paper proposes wireless sensor networks to monitor the condition of wind turbines. It addresses lifetime maximization issue of sensor nodes using stable election protocol for a cluster of upto nine wind turbines. This paper presents results of both experimental and simulation studies of a wind turbine plant, in which the vibration signals from each wind turbine are taken and with the help of machine learning technique, the fault diagnosis is done for a plant with wireless sensor networks. An experimental case study is performed from a wireless sensor networks with a well reported wind turbine bearing fault diagnosis data set. The outcome of the study shows that if the number of wind turbines is five for one base station, then the lifetime of the sensor nodes are maximum using MATLAB.