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 …

Among the greatest challenges in soft sensor development for bioprocesses are variable
process lengths, multiple process phases, and erroneous model inputs due to sensor faults …

Data-based process monitoring has become a key technology in process industries for
safety, quality, and operation efficiency enhancement. This paper provides a timely update …

With ever-accelerating advancement of information, communication, sensing and
characterization technologies, such as industrial Internet of Things (IoT) and high-throughput …

In order to provide more sensitive monitoring results, the time dynamics and steady-state
operating conditions should be separately monitored by distinguishing time information from …

Projection to latent structures or partial least squares (PLS) produces output-supervised
decomposition on input X, while principal component analysis (PCA) produces …

In industrial manufacturing, most batch processes are inherently multistage/multiphase in
nature. To ensure both quality consistency of the manufactured products and safe operation …

A nonlinear kernel Gaussian mixture model (NKGMM) based inferential monitoring method
is proposed in this article for chemical process fault detection and diagnosis. Aimed at the …

Complex industrial processes may be formulated with hybrid correlations, indicating that
linear and nonlinear relationships simultaneously exist among process variables, which …

A novel batch process monitoring approach is proposed in this article to handle batch
processes with multiple operation phases. The basic idea is to combine the Gaussian …