# Assessment of hybrid machine learning models for non-linear system identification of fatigue test rigs

arXiv: https://arxiv.org/abs/2107.03645 · HTML: https://mlsanity.com/paper/2107.03645/

## Key facts

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- First posted on arXiv 8 Jul 2021.

## Abstract (arXiv)

The prediction of system responses for a given fatigue test bench drive signal is a challenging task, for which linear frequency response function models are commonly used. To account for non-linear phenomena, a novel hybrid model is suggested, which augments existing approaches using Long Short-Term Memory networks. Additional virtual sensing applications of this method are demonstrated. The approach is tested using non-linear experimental data from a servo-hydraulic test rig and this dataset is made publicly available. A variety of metrics in time and frequency domains, as well as fatigue strength under variable amplitudes, are employed in the evaluation.