Enhanced Convolutional Neural Network for In Situ AUV Thruster Health Monitoring Using Acoustic Signals.

As the demand for ocean exploration increases, studies are being actively conducted on autonomous underwater vehicles (AUVs) that can efficiently perform various missions. To successfully perform long-term, wide-ranging missions, it is necessary to apply fault diagnosis technology to AUVs. In this study, a system that can monitor the health of in situ AUV thrusters using a convolutional neural network (CNN) was developed.