Data-Driven Design of Fault Diagnosis Systems
Nonlinear Multimode Processes
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Beschreibung
In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes.
The main objective of Adel Haghani Abandan Sari is to study efficient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, different methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements.
Contents
- Process monitoring
- Fault diagnosis and fault-tolerant control
- Data-driven approaches and decision making
Target Groups
- Graduate students and scientists of automatic control and process engineering
- Engineers in field of process control and monitoring, mechatronic
About the Author
Adel Haghani Abandan Sari is research assistant with Instituteof Automation, university of Rostock. His research interests include data-driven process monitoring and fault-tolerant control with focus on large-scale industrial processes.In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes.
The main objective of Adel Haghani Abandan Sari is to study efficient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, different methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements.
Publication in the field of technical sciences Includes supplementary material: sn.pub/extras
Autor*in
Adel Haghani Abandan Sari
Themen in »Data-Driven Design of Fault Diagnosis Systems«
Data-driven approaches Decision making Fault detection and diagnosis Process monitoring