Szerző: rufina | jún 15, 2021 | Alarm Management
SEQUENCE MINING BASED ALARM SUPPRESSION Despite the high-pace improvement of industrial process automation, the management of abnormal events still requires human actions. Alarm systems are becoming crucial in providing situationspecific information to the decreasing...
Szerző: rufina | jún 15, 2021 | Alarm Management
HIERARCHICAL FREQUENT SEQUENCE MINING ALGORITHM FOR THE ANALYSIS OF ALARM CASCADES IN CHEMICAL PROCESSES Faults and malfunctions on complex chemical production systems generate alarm cascades that hinder the work of the operators and make fault diagnosis a complex and...
Szerző: rufina | jún 15, 2021 | Alarm Management
UNDERSTANDING THE IMPORTANCE OF PROCESS ALARMS BASED ON THE ANALYSIS OF DEEP RECURRENT NEURAL NETWORKS TRAINED FOR FAULT ISOLATION The identification of process faults is a complex and challenging task due to the high amount of alarms and warnings of control systems....
Szerző: rufina | jún 15, 2021 | Alarm Management
PROCESS MINING IN PRODUCTION SYSTEMS Due to the increasing automation and integrity of today’s productions systems, thousands of alarms are generated every day in the more and more complex process control units. The core concept of our work is the investigation of the...
Szerző: rufina | jún 15, 2021 | Alarm Management
TOWARDS OPERATOR 4.0, INCREASING PRODUCTION EFFICIENCY AND REDUCING OPERATOR WORKLOAD BY PROCESS MINING OF ALARM DATA A methodology to extract temporal patterns of alarm sequences and operator actions from the log files of alarm management systems is proposed....
Szerző: rufina | jún 14, 2021 | Alarm Management
LEARNING AND PREDICTING OPERATION STRATEGIES BY SEQUENCE MINING AND DEEP LEARNING The operators of chemical technologies are frequently faced with the problem of determining optimal interventions. Our aim is to develop data-driven models by exploring the consequential...
Legutóbbi hozzászólások