Process fault detection and diagnosis (FDD) is an essential tool to ensure safe production in
chemical industries. After decades of development, despite the promising performance of …

It is well-documented how artificial intelligence can have (and already is having) a big
impact on chemical engineering. But classical machine learning approaches may be weak …

The development of the Internet of Things, cloud computing, and artificial intelligence has
given birth to industrial artificial intelligence (IAI) technology, which enables us to obtain fine …

Abstract Fault Detection and Diagnosis (FDD) for overall modern Wind Energy Conversion
(WEC) systems, particularly its converter, is still a challenge due to the high randomness to …

In this article, a just-in-time-learning (JITL)-aided canonical correlation analysis (CCA) is
proposed for the monitoring and fault detection of multimode processes. A canonical …

Safe and stable operation plays an important role in the chemical industry. Fault detection
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …

Kernel methods are a class of learning machines for the fast recognition of nonlinear
patterns in any data set. In this paper, the applications of kernel methods for feature …

Frequent and wide changes in operation conditions are quite common in real process
industry, resulting in typical wide-range nonstationary and transient characteristics along …

In the multirate sampling processes, the process data are usually collected from various
operating conditions and display multimodal characteristics. To monitor these multirate …

Artificial Intelligence (AI) techniques are transforming various sectors and hold significant
potential to advance sustainable development in Africa. However, their effective integration …