Mechanical fault diagnosis is one of the important technologies in the fourth industrial
revolution. In recent years, mechanical fault diagnosis based on audio signal analysis …

In fault diagnosis, machine learning theories are gaining popularity as they proved to be an
efficient tool that not only reduces human effort but also identifies the health conditions of the …

In general, training fault samples of aero-engines are very rare and only collected under one
or a few operating conditions. However, due to diverse operating conditions and fault …

From smart sensors on assembly lines to robots performing complex tasks, the fourth
industrial revolution is rapidly transforming manufacturing. The growing prominence of 3D …

Industrial equipment failure diagnosis is a crucial issue that impacts the national industrial
manufacturing level, economic cycle development, and sustainable technological …

The existing intelligent monitoring methods are hard to apply directly to hydraulic machinery
due to fault data collection difficulties and the uncertainty of fault occurrence. To monitor the …

In the field of fault transfer diagnosis, many approaches only focus on the distribution
alignment and knowledge transfer between the source domain and target domain. However …

Plenty of maximum mean discrepancy (MMD)-based domain adaptation models have been
applied to the fault transfer diagnosis. MMD uses the mean statistic in Hilbert space to …

In the rapidly evolving field of machine learning engineering, access to large, high-quality,
and well-balanced labeled datasets is indispensable for accurate product classification. This …

Class imbalance and class overlap create difficulties in the training phase of the standard
machine learning algorithm. Its performance is not well in minority classes, especially when …