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Article

An Application of Instantaneous Spectral Entropy for the Condition Monitoring of Wind Turbines

1
Department of Mechanical and Aerospace Engineering—DIMEAS, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
2
Department of Structural, Geotechnical and Building Engineering—DISEG, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Wei Huang
Appl. Sci. 2022, 12(3), 1059; https://doi.org/10.3390/app12031059
Received: 16 December 2021 / Revised: 10 January 2022 / Accepted: 18 January 2022 / Published: 20 January 2022
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
For economic and environmental reasons, the use of renewable energy sources is a key aspect of the ongoing transition to a sustainable industrialised society. Wind energy represents a major player among these natural, carbon-neutral sources. Nevertheless, wind turbines are often subject to mechanical faults, especially due to ageing. To alleviate Operation and Maintenance costs, Vibration-Based Inspection and Condition Monitoring have been proposed in recent times. This research proposes Instantaneous Spectral Entropy and Continuous Wavelet Transform for anomaly detection and fault diagnosis, departing from gearbox vibration time histories. The approach is validated on experimental data recorded from a turbine suffering bearing failure and total gearbox replacement. From a computational point of view, the proposed algorithm was found to be efficient and therefore even potentially applicable for real-time monitoring. View Full-Text
Keywords: structural health monitoring; condition monitoring; fault detection; rotating machinery; wind turbines; instantaneous entropy; generalised morse wavelet structural health monitoring; condition monitoring; fault detection; rotating machinery; wind turbines; instantaneous entropy; generalised morse wavelet
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MDPI and ACS Style

Civera, M.; Surace, C. An Application of Instantaneous Spectral Entropy for the Condition Monitoring of Wind Turbines. Appl. Sci. 2022, 12, 1059. https://doi.org/10.3390/app12031059

AMA Style

Civera M, Surace C. An Application of Instantaneous Spectral Entropy for the Condition Monitoring of Wind Turbines. Applied Sciences. 2022; 12(3):1059. https://doi.org/10.3390/app12031059

Chicago/Turabian Style

Civera, Marco, and Cecilia Surace. 2022. "An Application of Instantaneous Spectral Entropy for the Condition Monitoring of Wind Turbines" Applied Sciences 12, no. 3: 1059. https://doi.org/10.3390/app12031059

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