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

Recent progress on intelligent fault diagnosis (IFD) has greatly depended on deep
representation learning and plenty of labeled data. However, machines often operate with …

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 …

Automatic and reliable fault diagnosis of rotating machinery cross working conditions is of
practical importance. For this purpose, ensemble transfer convolutional neural networks …

Investigation of deep transfer learning on machinery fault diagnosis is helpful to overcome
the limitations of a large volume of training data, and accelerate the practical applications of …

The existing fault prognosis techniques of aeroengine mostly focus on a single monitoring
parameter under stable condition, and have low adaptability to new prognosis scenes. To …

Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

Gears are an important component of industrial machinery and a breakdown of machinery
on account of the failure of gears could result in immense production loss. Timely monitoring …

Bearing fault diagnosis has made some achievements based on massive labeled fault data.
In practical engineering, machines are mostly in healthy and faults seldom happen, it's …

With the development of intelligent manufacturing and automation, the precision and
complexity of mechanical equipment are increasing, which leads to a higher requirement for …