Comparison of electrical and vibration analysis methods for mechanical fault monitoring in wind turbine drivetrains

Pierre Granjon (1) , Pedro Dias Longhitano (1) , Arshpreet Singh (1)

1 GIPSA-SAIGA - GIPSA - Signal et Automatique pour la surveillance, le diagnostic et la biomécanique

Mechanical faults occurring in drivetrains are traditionally monitored through vibration analysis, and more rarely by analyzing electrical quantities measured on the involved electromechanical system. However, a monitoring method able to take into account the whole information contained in three-phase electrical quantities was recently proposed. The goal of this paper is to compare this three-phase electrical approach and the usual vibration-based method in terms of detection capabilities of mechanical faults in drivetrains. In this context, a 2MW geared wind turbine operating in an industrial wind farm was equipped during several months with accelerometers near the main bearing and electrical sensors on the stator of the electrical generator. During this period, an important mechanical fault occurred in the main bearing of this system. The evolution of the fault indicators computed by the two previous approaches are compared all along this period of time. All the indicators behave similarly and show the development of an inner bearing fault in the main bearing. This demonstrate that a mechanical fault occurring in a drive train can be monitored and detected by analyzing electrical quantities, even if the fault is distant from the electrical generator.

Domaines: Traitement du signal et de l'image [eess.SP]; Energie électrique

Pierre Granjon, Pedro Dias Longhitano, Arshpreet Singh. Comparison of electrical and vibration analysis methods for mechanical fault monitoring in wind turbine drivetrains. CM 2018 - MFPT 2018 - 15th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Sep 2018, Nottingham, United Kingdom. ⟨hal-01982739⟩