کنفرانس مهندسی برق ایران

صفحه اصلی / سی و دومین کنفرانس بین المللی مهندسی برق

Gearbox Fault Detection Using Continuous Wavelet Transform and Vision Transformer (ViT)

نویسندگان :

Ali Asadian¹ Yassin Riyazi² Moosa Ayati³

1- دانشگاه تهران 2- دانشگاه تهران 3- دانشگاه تهران

کلمات کلیدی :

Gearbox fault detection،Imaging time-series،Multi-channel،Vision Transformers

چکیده :

Managing the substantial volume of data generated by gearbox operations and the inherent complexities underscores the strategic advantage of employing deep learning methods. This study addresses fault detection in the gearbox using a Vision Transformer (ViT), whose images were prepared by continuous wavelet transformation. The dataset from the Open Energy Data Initiative (OEDI) serves as the foundation for our analysis. Data recorded by four vibration sensors, situated in the time domain and various operating loads, transform into two-dimensional images which, after some manipulations, are fed into a ViT, allowing us to tackle the classification challenge with 'Healthy' and 'Damaged' classes. Remarkably, we achieved an outstanding accuracy of %99.1554, coupled with a reduction in the loss function to 0.040100. These results demonstrate the ViT's remarkable efficacy in detecting faults using images derived from signals recorded in the time domain.