Application of Deep Transfer Learning in Fault Diagnosis of Integrated Transmission

Abstract

The emergence of deep learning and transfer learning techniques has provided new ideas and methods for the detection and prediction of faults in complex systems. In practical engineering, the integrated transmission device plays a crucial role as an important transmission component, and its fault detection is essential to ensure the normal operation of tracked vehicles. This article will introduce the application of deep transfer learning in the fault detection of integrated transmission devices, as well as the concepts of deep learning and transfer learning. Then, we will discuss the background and challenges of fault detection in integrated transmission devices. Based on a simple model experiment, we will summarize this article and look forward to future research directions.