Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …

Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …

Deep learning (DL)-based methods have advanced the field of Prognostics and Health
Management (PHM) in recent years, because of their powerful feature representation ability …

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

Collaborative fault diagnosis can be facilitated by multisensory fusion technologies, as these
can give more reliable results with a more complete data set. Although deep learning …

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

Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …

Crop diseases constitute a serious issue in agriculture, affecting both quality and quantity of
agriculture production. Disease control has been a research object in many scientific and …

As one of the most immensely growing renewable energies, the wind power industry also
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …

Gearbox fault diagnosis is expected to significantly improve the reliability, safety and
efficiency of power transmission systems. However, planetary gearbox fault diagnosis …