Automatic and Full-Band Demodulation for Fault Detection—Validation on a Wind Turbine Test Rig

Marcin Firla (1) , Zhong-Yang Li (1) , Nadine Martin (1) , Tomasz Barszcz (2)

1 GIPSA-SAIGA - GIPSA - Signal et Automatique pour la surveillance, le diagnostic et la biomécanique
2 Department of Mechanical Engineering and Robotics

This paper proposes three algorithms for automatic diagnosis of mechanical system. First of all, an angular resampling with speed measurement correction is introduced. Secondly, a method for the association of detected spectral patterns with the characteristic frequencies of the investigated system is presented. This approach takes into consideration the slippage phenomenon of rolling element bearings. Thirdly, a full-band sideband demodulation method is proposed. It features with multi-rate filtering and offers new health indicators. All methods are applied on the real-world signals of a wind turbine test rig for diagnosis a bearing fault. The comparison of results shows the advantages of the proposed algorithms over well-known health indicators.

Mots clés: Signal processing; Demodulation; Condition monitoring; Angular resampling; Characteristic fault frequencies; Kinematic; Amplitude and frequency modulations; Wind turbine

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

Marcin Firla, Zhong-Yang Li, Nadine Martin, Tomasz Barszcz. Automatic and Full-Band Demodulation for Fault Detection—Validation on a Wind Turbine Test Rig. Advances in Condition Monitoring of Machinery in Non-Stationary Operations, 2015, Proceedings of the Fourth International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO'2014, Lyon, France December 15-17, ⟨10.1007/978-3-319-20463-5_10⟩. ⟨hal-01212474⟩