Fault diagnosis is an important topic both in practice and research. There is intense pressure
on industrial systems to continue reducing unscheduled downtime, performance …

Artificial intelligence, big data, machine learning, cloud computing, and Internet of Things
(IoT) are terms which have driven the fourth industrial revolution. The digital revolution has …

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 …

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 …

Industries are using fault diagnosis methods to prevent any downtime, which eventually led
them to make profits and take necessary steps beforehand to avoid any mishaps. In recent …

The massive high-dimensional measurements accumulated by distributed control systems
bring great computational and modeling complexity to the traditional fault diagnosis …

This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex
systems from the perspective of data processing. As a matter of fact, an FDD system is a data …

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 …

Fault prognosis is mainly referred to the estimation of the operating time before a failure
occurs, which is vital for ensuring the stability, safety and long lifetime of degrading industrial …