In continuous chemical processes, variations of process variables usually travel along propagation paths in the direction of flow. The aim of this study was to find a data-driven method for identifying the direction of variation propagation using historical process data. Transfer entropy is a recently proposed method based on the probability density function (PDF) that measures directionality of variation with respect to time. An industrial case study illustrates the method which detects the influence of a temperature controller on downstream temperature measurements. A reversal of directionality was noted during a disturbance and a physical explanation offered
In modern industrial plants, process units are strongly cross-linked with each other, and disturbanc...
Transfer Entropy and Directed Information are information-theoretic measures of the directional depe...
Information-theoretic quantities, such as entropy and mutual information (MI), can be used to quanti...
Abstract: In continuous chemical processes, variations of process variables usually travel along pro...
Abstract The discovery of cause-effect relationships in signals from industrial processes is a chal...
Modern process industries are large and complex. Their units are highly interconnected with each oth...
Oscillations in mineral processes can propagate through multiple units, causing important controlled...
The thesis is concerned with the development of data-driven methods for fault diagnosis of plant-wid...
Causality analysis techniques can be used for fault diagnosis in industrial processes. Multiple caus...
Transfer entropy (TE) is a model-free approach based on information theory to capture causality betw...
Industrial systems often encounter abnormal conditions due to various faults or external disturbance...
Production plants used in modern process industry must produce products that meet stringent environm...
We discuss a recently proposed quantity, called transfer entropy, which uses time series data to mea...
Industrial systems are often subjected to abnormal conditions due to faulty operations or external d...
In modern industrial plants, process units are strongly cross-linked with eachother, and disturbance...
In modern industrial plants, process units are strongly cross-linked with each other, and disturbanc...
Transfer Entropy and Directed Information are information-theoretic measures of the directional depe...
Information-theoretic quantities, such as entropy and mutual information (MI), can be used to quanti...
Abstract: In continuous chemical processes, variations of process variables usually travel along pro...
Abstract The discovery of cause-effect relationships in signals from industrial processes is a chal...
Modern process industries are large and complex. Their units are highly interconnected with each oth...
Oscillations in mineral processes can propagate through multiple units, causing important controlled...
The thesis is concerned with the development of data-driven methods for fault diagnosis of plant-wid...
Causality analysis techniques can be used for fault diagnosis in industrial processes. Multiple caus...
Transfer entropy (TE) is a model-free approach based on information theory to capture causality betw...
Industrial systems often encounter abnormal conditions due to various faults or external disturbance...
Production plants used in modern process industry must produce products that meet stringent environm...
We discuss a recently proposed quantity, called transfer entropy, which uses time series data to mea...
Industrial systems are often subjected to abnormal conditions due to faulty operations or external d...
In modern industrial plants, process units are strongly cross-linked with eachother, and disturbance...
In modern industrial plants, process units are strongly cross-linked with each other, and disturbanc...
Transfer Entropy and Directed Information are information-theoretic measures of the directional depe...
Information-theoretic quantities, such as entropy and mutual information (MI), can be used to quanti...