Abstract
As a clean energy, the development of wind power has attracted wide attention. In view of the characteristics of non-linear and non-stationary mixed signals in the vibration state of wind turbines, the separation of noise is the key problem of information feature extraction. In this study, sensors are utilized to collect blind source signals and mixed matrix information in order to retrieve source signals and extract features from information. This paper integrates EMD (Empirical Model Decomposition) with ICA (Independent Component Analysis) with the aim of extracting feature signals from the wind turbine generator system (WTGS). By analyzing signals with obvious fault characteristics, this approach considerably increases the accuracy in extracting feature signals from the WTGS transmission system.
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Guo, J., Wu, G., Zhao, X., Huang, H., Xu, X. (2023). Study on Feature Extraction of Gearbox Vibration Signal for Wind Turbines. In: Zhang, H., Feng, G., Wang, H., Gu, F., Sinha, J.K. (eds) Proceedings of IncoME-VI and TEPEN 2021. Mechanisms and Machine Science, vol 117. Springer, Cham. https://doi.org/10.1007/978-3-030-99075-6_49
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DOI: https://doi.org/10.1007/978-3-030-99075-6_49
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