Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …

With movement toward complication and automation, modern machinery equipment
encounters the problems of diversity and complex origination of faults, incipient weak faults …

With the development of industry, more and more crucial mechanical machinery generate
wildness demand of effective fault diagnosis to ensure the safe operation. Over the past few …

Fault diagnosis is critical in industrial systems since early detection of problems can not only
save valuable time but also reduce maintenance costs. The feature extraction process of …

For the past few years, In the research of intelligent monitoring of industrial equipment, deep
learning is becoming a method that get the widespread concern of researchers. In general …

Deep learning applications have been thriving over the last decade in many different
domains, including computer vision and natural language understanding. The drivers for the …

In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …

In the era of Industry 4.0, highly complex production equipment is becoming increasingly
integrated and intelligent, posing new challenges for data-driven process monitoring and …

Early fault detection, both in equipment and the products in process, is of paramount
importance in industrial processes to ensure the quality of the final product, avoid abnormal …

Abstract Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …