Reference implementation of Digital Twins for electrical energy conversion systems is an
important and open question in the industrial domain. Digital Twins can predict the future …

Deep learning networks are widely used to realize the intelligent diagnosis of gear faults.
However, the problem of the insufficient number of typical fault samples and strong noise …

There is an increasing need for timely pipeline leak detection and localization methods,
pipeline leak could lead to not only the loss of the goods but also considerable …

The effective fault diagnosis of bearing can guarantee the safety of rotating machinery and is
very important for its stable operation. The information fusion of multisensor data has been a …

Recently, deep learning has been successfully applied in tool wear monitoring systems.
However, since the tool wear accumulates in the cutting process, the state of the cutting tool …

This article proposes a novel online fault diagnosis scheme for industrial powertrains without
using historical faulty or labeled training data. The proposed method combines a one-class …

It is not feasible for a single image sensor to convey all of the information essential to
comprehend a circumstance thoroughly. The output of many image sensors combined in …

Surface wear, which is most likely to occur in early damage of wire ropes (WRs), is a serious
threat to WR safety. Visual perception technology (VPT) can intuitively grasp the surface …

Vibration signals are widely utilized for machinery fault diagnosis. However, the fault-related
components (ie, impulse) in vibration signals are often buried by strong background noises …

Rolling bearings are the key component of large rotating machinery. When such
components fail completely, the equipment will be out of service, causing significant …