With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …

With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …

Sensor techniques and emerging CNN models have greatly facilitated the development of
collaborative fault diagnosis. Existing CNN models apply different fusion schemes to …

The existing intelligent fault diagnosis methods of rotor-bearing system mainly focus on
vibration analysis under steady operation, which has low adaptability to new scenes. In this …

As a typical manufacturing equipment, CNC machine tool (CNCMT) is the mother machine
of industry. Fault of CNCMT might cause the loss of precision and affect the production if …

Diagnosis of mechanical faults in manufacturing systems is critical for ensuring safety and
saving costs. With the development of data transmission and sensor technologies …

Intelligent fault diagnosis techniques play an important role in improving the abilities of
automated monitoring, inference, and decision making for the repair and maintenance of …

Hydraulic systems are a class of typical complex nonlinear systems, which have been widely
used in manufacturing, metallurgy, energy, and other industries. Nowadays, the intelligent …

Deep transfer learning algorithm is regarded as a promising method to address the issue of
rolling bearing fault diagnosis with limited labeled data. Stacked autoencoder (SAE) has …

Recently, deep transfer learning based intelligent fault diagnosis has been widely
investigated, and the tasks that source and target domains share the same fault categories …