The extraction of wind turbine condition related features using air-borne acoustic signals

Abouhnik, A, Ibrahim, G, Deng, Rongfend, Brethee, K, Badawood, A, Abushanab, W, Zhang, X, Batunlu, C and Albarbar, A ORCID: https://orcid.org/0000-0003-1484-8224 (2023) The extraction of wind turbine condition related features using air-borne acoustic signals. In: TEPEN 2022: International conference on the Efficiency and Performance Engineering Network, 18 August 2022 - 21 August 2022, Baotou, China.

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Abstract

Wind turbines vibration signals carry useful information about their conditions. However, such signals are usually very complex and comprise high number of vibratory signatures. Moreover, the cost of setting up vibration measurement systems using conventional accelerometers is very high especially in the case of multi-location measuring points are required. This paper contributes towards developing an inexpensive and accurate condition monitoring method based on remotely measured air-born acoustic signals. Fault detection capabilities are assessed by determining its coherence with the well-understood vibration induced signals. A new generation of recently improved condenser microphone used as input for the proposed coherence analysis algorithm. Special arrangement to eliminate reverberation problems associated with air-borne acoustic signals was designed. Consequently, coherence analysis is carried out to compare the information supplied by the accelerometer and the microphone of a three bladed horizontal wind turbine under different operating conditions. The air-borne acoustic signal exhibits good coherence with the vibration ones at rotating speed, gear meshing frequencies and fan passing frequency bands. More important, air-borne acoustic data was found to contain more pronounced information within wider spectrum compared with the vibration measurements. The presented results open doors for deeper investigations on the diagnostic capabilities of such technique and probably lead to fully adoption by the wind turbine industry.