2024
DOI: 10.1088/1361-665x/ad5c24
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Addressing data scarcity using audio signal augmentation and deep learning for bolt looseness prediction

Nikesh Chelimilla,
Viswanath Chinthapenta,
Srikanth Korla

Abstract: Deep learning models such as convolutional neural networks (CNNs) encounter challenges, including instability and overfitting, while predicting bolt looseness in data-scarce scenarios. In this study, we proposed a novel audio signal augmentation approach to classify bolt looseness in the event of data deficiency using CNN models. Audio signals at varied bolt torque conditions were extracted using the percussion method. Audio signal augmentation was performed using signal shifting and scaling strategies after s… Show more

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