Industrial process supervision is an important subject nowdays due to the increased requirement for safer processes for operators and effective for companies. Control loops affected by disturbs, are grouped with PCA, based on their increased variability and the causal relationships between them are detected via Granger causality. A graph drawing algorithm allows indicating the source of the disturbance. The procedure is applied to data from a simulated chemical process CSTR. The proposed procedeture correctly indicated the sources of disturbances
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
Model-based fault diagnosis tends to be too expensive or time-consuming to apply in the mineral proc...
The plant-wide disturbance can affect the product quality, manufacturing costs, process safety and e...
2014-08-06A typical industrial process or plant operates with hundreds of control loops and those pr...
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...
Multivariate statistical process monitoring (MSPM) has received a considerable amount of attention i...
Causality analysis techniques can be used for fault diagnosis in industrial processes. Multiple caus...
Industrial systems are often subjected to abnormal conditions due to faulty operations or external d...
Fault diagnosis is a challenging problem, particularly for a large-scale industrial process. An up-t...
Dissertação de Mestrado Integrado em Engenharia Química apresentada à Faculdade de Ciências e Tecnol...
This brief reviews concepts of inter-relationship in modern industrial processes, biological and soc...
In large-scale chemical processes, disturbances can easily propagate through the process units and t...
Causal knowledge in complex process systems is a powerful representational model that permits a rang...
In continuous chemical processes, disturbances in the process conditions can propagate widely and ca...
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
Model-based fault diagnosis tends to be too expensive or time-consuming to apply in the mineral proc...
The plant-wide disturbance can affect the product quality, manufacturing costs, process safety and e...
2014-08-06A typical industrial process or plant operates with hundreds of control loops and those pr...
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...
Multivariate statistical process monitoring (MSPM) has received a considerable amount of attention i...
Causality analysis techniques can be used for fault diagnosis in industrial processes. Multiple caus...
Industrial systems are often subjected to abnormal conditions due to faulty operations or external d...
Fault diagnosis is a challenging problem, particularly for a large-scale industrial process. An up-t...
Dissertação de Mestrado Integrado em Engenharia Química apresentada à Faculdade de Ciências e Tecnol...
This brief reviews concepts of inter-relationship in modern industrial processes, biological and soc...
In large-scale chemical processes, disturbances can easily propagate through the process units and t...
Causal knowledge in complex process systems is a powerful representational model that permits a rang...
In continuous chemical processes, disturbances in the process conditions can propagate widely and ca...
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
Model-based fault diagnosis tends to be too expensive or time-consuming to apply in the mineral proc...
The plant-wide disturbance can affect the product quality, manufacturing costs, process safety and e...