The importance of evaluating valve conditions and detecting the onset of possible
malfunctions is recognized as a key issue in control performance monitoring, as they may …

Oscillatory control loop is a frequent problem in process industries. Its incidence reduces
product uniformity and increases both energy consumption and raw material waste. These …

Oscillations are common in closed-loop controlled processes which, once generated, can
propagate along process flows and feedback paths of the whole plant. It is important to …

A non-invasive method for detecting valves suffering from stiction using multi-layer feed-
forward neural networks (NN) is proposed, via a simple class-based diagnosis. The …

Even though several algorithms have been proposed in the literature for oscillation detection
and diagnosis, they can work reliably only for a specific type of oscillation and there is a lack …

The time series self-supervised contrastive learning framework has succeeded significantly
in industrial fault detection scenarios. It typically consists of pretraining on abundant …

Using neural networks to build a reliable fault detection model is an attractive topic in
industrial processes but remains challenging due to the lack of labeled data. We propose a …

Control valve stiction is a long-standing problem within process industries. In most methods
for shape-based stiction detection, they rely heavily on the traditional controller output (OP) …

This paper proposes a new method based on the discrete cosine transform (DCT), named
as the DCT-based method, to detect oscillations for a single time series. The main idea is to …

Numerous applications in river management require computationally efficient models that
can accurately simulate the state of a river. This paper presents a reduced complexity …