The intelligent bearing diagnosis with big data has been widely researched. Despite high
performance diagnosis models are constantly being proposed, these models are difficult to …

In recent years, convolutional neural networks (CNNs) have achieved worth seeing results
in mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) due to their powerful …

Automated fault diagnosis can significantly reduce the workload of condition monitor-ing
personnel. Deep learning based methods are one way to automate fault diagnosis. These …

In the field of chemical process fault diagnosis, there is a common objective problem of less
effective fault samples. In many practical chemical process fault application scenarios, the …

The uncertainty prediction of pavement performance can promote intelligent highway tunnel
operation and maintenance, but it encounters the challenges of small and non-normality …

The cost of coal and environmental protection make coal-fired power plants focus on energy
conservation and emission reduction in the boiler's combustion process. And in the context …

Deep learning-based methods have been extensively studied in rotating machinery defect
diagnosis. However, training an accurate and robust diagnostic model is still a challenge …

Recent refinements in Industry 4.0 and Machine Learning demonstrate the positive effects of
using deep learning models for intelligent maintenance. The primary benefit of Deep …