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 …

The present paper brings together openly available datasets and simulators for testing of
process monitoring and fault diagnosis techniques. Some general characteristics of these …

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 …

Due to unexpected data transition or equipment failures, irregular data with missing values,
which have both irregular sampling intervals and missing values, become very common in …

Missing data are quite common in the industrial field. Since most data driven methods used
in these applications rely on complete and high-quality data set, it is important to handle the …

Soft sensor technology has found widespread application in the real-time detection of
challenging variables like product quality and key process parameters. However, changes in …

Against the backdrop of the new-generation intelligent manufacturing and Industrial Internet
of Things, manufacturing processes are evolving towards integration, large-scale …

Data-driven soft sensor technology has been widely used in process monitoring, quality
prediction, etc. However, there are dynamic time-varying and concept drift problems in …

Process industries are usually composed of several coupled sub-processes, which are
distributed in different positions, connected and transmitted in the form of quality flow and …

In actual manufacturing processes, because of the difference of sampling intervals of
different process and quality variables, most of the collected data have characteristics of …