WIND TURBINE GEARBOX HEALTH STATUS ASSESSMENT BASED ON VINE COPULA BILSTM

Cao Jing; Liu Jie

doi:10.19912/j.0254-0096.tynxb.2023-2098

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (4) : 494-503. DOI: 10.19912/j.0254-0096.tynxb.2023-2098

WIND TURBINE GEARBOX HEALTH STATUS ASSESSMENT BASED ON VINE COPULA BILSTM

Liu Jie, Cao Jing

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Abstract

To accurately and scientifically assess the operational condition of wind turbine gearbox, a health status assessment model based on the Vine-Copula model and Bi-directional Long Short-Term Memory （BiLSTM） algorithm is proposed. Firstly, the coupling relationships between various state parameters in the Supervisory Control and Data Acquisition （SCADA） system are analyzed using the Vine-Copula model. Then, the BiLSTM algorithm is employed to construct standard residuals under healthy conditions, which are used to assess the gearbox's health status. Finally, real-time data are used to compute the residuals, which are compared with the standard residuals under healthy conditions. Mahalanobis distance is utilized to measure the difference between the covnputed residual and standard residual, and a health index is incorporated to categorize the gearbox’s health status into four levels: excellent, normal, attentive and poor. The results demonstrate that the model can provide early fault warnings for gearbox oil temperature overheating under various operating conditions, with lead times of 90 minutes and 1186 minutes, respectively. This model effectively enables the assessment of the operational health status of the wind turbine gearbox.

Key words

wind turbines / status assessment / SCADA system / predictive analysis / neural network

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Liu Jie, Cao Jing. WIND TURBINE GEARBOX HEALTH STATUS ASSESSMENT BASED ON VINE COPULA BILSTM[J]. Acta Energiae Solaris Sinica. 2025, 46(4): 494-503 https://doi.org/10.19912/j.0254-0096.tynxb.2023-2098

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