A vortex-induced vibration warning method based on ensemble-learning-embedded neural network

Yan, Fei

doi:10.1111/mice.70160

A vortex-induced vibration warning method based on ensemble-learning-embedded neural network

2025-11-01

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DOI：10.1111/mice.70160

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An ensemble-learning-embedded neural network for vortex-induced vibration (VIV) early warning was proposed. The new model consists of a core module based on ensemble learning and peripheral modules. The core module identifies abstract features of VIV, while the peripheral modules handle feature extraction and weight control. The core module of the new model is trained entirely using augmented datasets. Consequently, compared to other models with equivalent parameter counts, the new model can be trained using significantly fewer datasets. Displacement records from three VIV events at a cable-stayed bridge under construction were used to train and test the model. The new model demonstrated superior performance during testing. After retraining with data from a single VIV event at another cable-stayed bridge in the construction phase, the new model successfully achieved VIV early warning for the new bridge. The new model demonstrates significant potential for providing early warning of VIV due to its lower data requirements.

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A vortex-induced vibration warning method based on ensemble-learning-embedded neural network

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