Beam pumping units (BPUs) are key equipment in oilfield production. Currently, many fault
diagnosis methods for BPUs have been developed, and most of them are based on feature …

Convolutional neural network (CNN) architectures have been extensively utilized in data-
driven fault diagnosis and have demonstrated significant success. However, there remain …

In any industry, Equipment Asset Management (EAM) is at the core of the production
activities. With the rapid development of Industrial Internet technologies and platforms, the …

Safety state assessment is an important aspect of maintenance decisions for complex
systems. However, assessing the safety state of systems is a challenge due to their …

Intelligent bearing fault diagnosis is a necessary approach to ensure the stable operation of
rotating machinery. However, it is usually difficult to collect fault data under actual working …

Solving the problem of the transmission of mechanical equipment is complicated, and the
interconnection between equipment components in a complex industrial environment can …

Fault diagnosis (FD) has received attention because of its importance in maintaining safe
operations of industrial processes. Recently, modern data-driven FD approaches such as …

The application of a supervised deep convolutional autoencoder was tested against partial
least-squares-discriminant analysis (PLS-DA) for fault detection and diagnosis in a penicillin …

Rotating machine faults are unavoidable; thus, early diagnosis is essential to avoid further
damage to the machine or other machine attached to it. Various signal analysis based …

Deep-learning-based methods used for fault diagnosis show remarkable performance, and
these methods primarily learn features based on the time or frequency domain. Generally …