The traditional fault diagnosis models cannot achieve good fault diagnosis accuracy when a
new unseen fault class appears in the test set, but there is no training sample of this fault in …

Fault detection has long been a hot research issue for industry. Many common algorithms
such as principal component analysis, recursive transformed component statistical analysis …

Incipient fault detection (IFD) is important to the normal operation of modern complicated
industrial systems, kee** people safe and preventing property damage. In recent years …

Fault diagnosis that identifies the root of the abnormal status is of great importance to
eliminate faults in the complex chemical processes. Many data-driven fault diagnosis …

Data-driven fault detection has made significant advancements. However, detecting
incipient faults is still a challenging problem for traditional data-driven methods, because it …

The nonlinear and dynamic nature of complex industrial processes presents a significant
challenge for monitoring incipient faults. To this end, this article proposes a novel deep …

Although quality-related process monitoring has achieved the great progress, scarce works
consider the detection of quality-related incipient faults. Partial least square (PLS) and its …

Modern industry processes are typically composed of multiple operating units with reaction
interaction and energy–mass coupling, which result in a mixed time-varying and spatial …

Timely fault detection plays a critical role in modern complex industrial processes. While
statistical process monitoring has gained significant practical application in recent years …

The injection of an auxiliary input signal for active fault diagnosis may cause the change of
system control performance in closed‐loop operation. This paper presents a novel …