1.

Record Nr.

UNINA9910903794503321

Autore

Wang Jiandong

Titolo

Intelligent Industrial Alarm Systems : Advanced Analysis and Design Methods / / by Jiandong Wang, Wenkai Hu, Tongwen Chen

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024

ISBN

981-9765-16-1

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (XIV, 425 p. 244 illus., 208 illus. in color.)

Disciplina

629.8

Soggetti

Automatic control

Robotics

Automation

Production engineering

Industrial engineering

Control, Robotics, Automation

Process Engineering

Industrial Automation

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Overview of Industrial Alarm Systems -- Optimal Design of Univariate Alarm Systems -- Optimal Design of Multivariate Alarm Systems -- Root-Cause Analysis of Alarm Events -- Analysis of Industrial Alarm Floods -- Alarm Visual Analytics and Applications.

Sommario/riassunto

This book fills a gap in existing literature by providing a comprehensive academic perspective on industrial alarm systems, offering systematic methodologies, practical techniques, and visual analytic tools for engineers to improve system performance and design. Modern industrial plants rely on computerized monitoring systems to track hundreds of process variables in real time, enabling operators to maintain safe and efficient conditions. Automatic industrial alarm systems play a crucial role in alerting operators to abnormalities, such as high vessel levels, that could lead to unsafe conditions if left unaddressed. While contemporary alarm systems can be plagued with issues like nuisance alarms, recent academic research has introduced advanced methodologies, like Markov chain theory and Bayesian



estimation, to optimize alarm parameters and enhance system performance. By integrating these theoretical advancements into practical applications, the goal is to develop intelligent industrial alarm systems that leverage historical data and process knowledge to predict and prevent alarm floods, ultimately ensuring safer and more efficient plant operations.