Threshold optimization in distributed OS-CFAR system by using simulated annealing technique

Abdou, Latifa; Taibaoui, O.; Moumen, Abdelkader; Ahmed, A. Taleb

doi:10.1109/icosc.2015.7153287

Cited by 3 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Correlation degree analysis A measure of the degree of correlation between two factors in a system that varies from time to time or from object to object is called the correlation degree [38]. In a system process, if the trend of change of the two factors is consistent, that is, the degree of synchronous change is high, then the degree of correlation is high.…”

mentioning

confidence: 99%

Correlation Degree and Clustering Analysis-Based Alarm Threshold Optimization

Zhang

Wang

2022

Processes

View full text Add to dashboard Cite

In industrial practice, excessive alarms and high alarm rates are mostly generated from unreasonable settings to variable alarm thresholds, which have become the significant causes of impact on operation stability and plant safety. A correlation degree and clustering analysis-based approach was presented to optimize the variable alarm thresholds in this paper. The correlation degrees of variables are first obtained by analyzing correlation relationships among them. Second, the variables are grouped according to the gray correlation coefficients and clustering analysis, given the weight for fault alarm rate (FAR) in each group. An objective function about the FAR, missed alarm rate (MAR), and the maximum acceptable FAR and MAR is then established with variable weight. Eventually, based on an optimization algorithm, the objective function can be optimized for obtaining the optimal alarm threshold. Cases study of the Tennessee Eastman (TE) industrial simulation process and an actual industrial ethylene production process, in comparison to the initial situation, show that the method can effectively reduce FAR according to correlation degrees among variables in the system, and decrease the number of alarms with reduction rates of 40.5% and 35.3%, respectively.

show abstract

mentioning

confidence: 99%