S
Sandeep R. Kondaveeti
Researcher at University of Alberta
Publications - 10
Citations - 363
Sandeep R. Kondaveeti is an academic researcher from University of Alberta. The author has contributed to research in topics: ALARM & Manual fire alarm activation. The author has an hindex of 8, co-authored 10 publications receiving 329 citations. Previous affiliations of Sandeep R. Kondaveeti include CNOOC Limited.
Papers
More filters
Journal ArticleDOI
A Framework for Optimal Design of Alarm Systems
TL;DR: This paper investigates the effect of filtering of process data, adding alarm delay and using alarm deadband on accuracy of the alarm system and detection delay and proposes a framework for designing optimal filter, time delay and deadband to reduce false and missed alarm rates.
Journal ArticleDOI
Graphical tools for routine assessment of industrial alarm systems
TL;DR: Two novel alarm data visualization tools are presented: The High Density Alarm Plot (HDAP) charts top alarms over a given time period and Alarm Similarity Color Map (ASCM) highlights related and redundant alarms in a convenient manner.
Journal ArticleDOI
Quantification of alarm chatter based on run length distributions
TL;DR: An index is proposed to quantify the degree of alarm chatter based on run length distributions obtained exclusively from readily available historical alarm data to play a crucial role in routine assessment of industrial alarm systems.
Journal ArticleDOI
Graphical Representation of Industrial Alarm Data
TL;DR: This work demonstrates some novel visualization tools that can be used for assessing the performance of alarm systems in terms of effectively identifying nuisance alarms and their utility is illustrated using real industrial alarm data.
Journal ArticleDOI
Application of Multivariate Statistics for Efficient Alarm Generation
TL;DR: This work demonstrates the advantages of monitoring the PCA based T 2 and Q statistic over individual process variables overindividual process variables to reduce the false alarm and missed alarm rates and reduces the detection latency which is one of the main drawbacks of monitoring a filtered variable.