Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis
by
Cheng, Xin
, Li, Ding
in
Abnormalities
/ alarm correlation
/ alarm system
/ Alarm systems
/ Alarms
/ Algorithms
/ Analysis
/ association rule
/ Causality
/ Conditional probability
/ Correlation analysis
/ Data mining
/ Data processing
/ Design
/ Entropy
/ False alarms
/ first-out alarms
/ Methods
/ Occupational health and safety
/ Overloading
/ Redundancy
/ Sequences
/ Variables
/ Workloads
2024
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis
by
Cheng, Xin
, Li, Ding
in
Abnormalities
/ alarm correlation
/ alarm system
/ Alarm systems
/ Alarms
/ Algorithms
/ Analysis
/ association rule
/ Causality
/ Conditional probability
/ Correlation analysis
/ Data mining
/ Data processing
/ Design
/ Entropy
/ False alarms
/ first-out alarms
/ Methods
/ Occupational health and safety
/ Overloading
/ Redundancy
/ Sequences
/ Variables
/ Workloads
2024
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis
by
Cheng, Xin
, Li, Ding
in
Abnormalities
/ alarm correlation
/ alarm system
/ Alarm systems
/ Alarms
/ Algorithms
/ Analysis
/ association rule
/ Causality
/ Conditional probability
/ Correlation analysis
/ Data mining
/ Data processing
/ Design
/ Entropy
/ False alarms
/ first-out alarms
/ Methods
/ Occupational health and safety
/ Overloading
/ Redundancy
/ Sequences
/ Variables
/ Workloads
2024
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis
Journal Article
A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis
2024
Request Book From Autostore
and Choose the Collection Method
Overview
Alarm systems are commonly deployed in complex industries to monitor the operation status of the production process in real time. Actual alarm systems generally have alarm overloading problems. One of the major factors leading to excessive alarms is the presence of many correlated or redundant alarms. Analyzing alarm correlations will not only be beneficial to the detection of and reduction in redundant alarm configurations, but also help to track the propagation of abnormalities among alarm variables. As a special problem in correlated alarm detection, the research on first-out alarm detection is very scarce. A first-out alarm is known as the first alarm that occurs in a series of alarms. Detection of first-out alarms aims at identifying the first alarm occurrence from a large number of alarms, thus ignoring the subsequent correlated alarms to effectively reduce the number of alarms and prevent alarm overloading. Accordingly, this paper proposes a new first-out alarm detection method based on association rule mining and correlation analysis. The contributions lie in the following aspects: (1) An association rule mining approach is presented to extract alarm association rules from historical sequences based on the FP-Growth algorithm and J-Measure; (2) a first-out alarm determination strategy is proposed to determine the first-out alarms and subsequent alarms through correlation analysis in the form of a hypothesis test on conditional probability; and (3) first-out rule screening criteria are proposed to judge whether the rules are redundant or not and then consolidated results of first-out rules are obtained. The effectiveness of the proposed method is tested based on the alarm data generated by a public simulation platform.
This website uses cookies to ensure you get the best experience on our website.