Alarm clustering analysis and ACO based multi-variable alarms thresholds optimization in chemical processes

Tian, Wende; Zhang, Guixin; Liang, Huiting

doi:10.1016/j.psep.2017.09.020

Cited by 17 publications

(5 citation statements)

References 17 publications

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“…At present, an alarm system is important for safety, which generally utilizes FAR and MAR as efficiency indices to measure the accuracy of detecting operation conditions [36]. Based on the operation conditions, industrial processes usually contain normal and abnormal situations, which generally use the FAR and MAR to represent the probability directly for a variable when its measured values go beyond the threshold in normal operations, and within the threshold in abnormal operations in an alarm system [37].…”

Section: Alarm Efficiency Indexmentioning

confidence: 99%

Correlation Degree and Clustering Analysis-Based Alarm Threshold Optimization

Zhang

Wang

2022

Processes

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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.

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Section: Alarm Efficiency Indexmentioning

confidence: 99%

Correlation Degree and Clustering Analysis-Based Alarm Threshold Optimization

Zhang

Wang

2022

Processes

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“…Optimizing alarms of monitoring variables, based on operating MHIs, is more practical in a real CIP. In the same line, Tian et al [109] proposed a clustering analysis based method for alarm optimization using the ant colony algorithm. Their objective was to adjust the alarm thresholds to solve false alarm issues due to multivariable of chemical processes.…”

Section: Monitoring and Warningmentioning

confidence: 99%

A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks

et al. 2020

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The increasing demand for chemical products has driven the construction and development of chemical industrial areas, or so-called ‘chemical industrial parks’ (CIPs), but this has intrinsically raised the risk of major accidents. Therefore, it is significant and urgent to summarize the state of art and research needs in the field of CIP safety. In this paper, a keyword co-occurrence analysis of 116 scientific articles was conducted to support the classification of research topics in this field, then an overview of those research topics was presented to investigate the evolution of safety research with respect to CIPs. Specifically, the way that safety assessments are conducted, as well as how safety management and safety technology in such areas are classified and investigated, followed by detailed descriptions of representative methods and their contributions to CIP safety, are discussed. An integrated safety framework for CIPs is proposed to organize safety approaches and measures systematically. Based on the classification and analysis of studies on management, assessment, and technology related to CIP safety, the research trends and future directions and challenges are discussed and outlined. Those results are useful for improving theoretical method and industrial strategies, and can advance the safety and sustainability development of CIPs.

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“…In the past studies, many scholars have used different technologies to deal with the problem of redundant alarms generated by the IDS [16]. These methods can be generally divided into clustering-based methods [17][18][19], attribute-similarity-based methods [1,20], expertsystem-based methods [21,22], genetic-algorithm-based methods [23,24], data-miningbased methods [25,26], etc.…”

Section: Introductionmentioning

confidence: 99%

Research on Alarm Reduction of Intrusion Detection System Based on Clustering and Whale Optimization Algorithm

Wang¹,

Gu²,

Tang³

2021

Applied Sciences

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With the frequent occurrence of network security events, the intrusion detection system will generate alarm and log records when monitoring the network environment in which a large number of log and alarm records are redundant, which brings great burden to the server storage and security personnel. How to reduce the redundant alarm records in network intrusion detection has always been the focus of researchers. In this paper, we propose a method using the whale optimization algorithm to deal with massive redundant alarms. Based on the alarm hierarchical clustering, we integrate the whale optimization algorithm into the process of generating alarm hierarchical clustering and optimizing the cluster center and put forward two versions of local hierarchical clustering and global hierarchical clustering, respectively. To verify the feasibility of the algorithm, we conducted experiments on the UNSW-NB15 data set; compared with the previous alarm clustering algorithms, the alarm clustering algorithm based on the whale optimization algorithm can generate higher quality clustering in a shorter time. The results show that the proposed algorithm can effectively reduce redundant alarms and reduce the load of IDS and staff.

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Alarm clustering analysis and ACO based multi-variable alarms thresholds optimization in chemical processes

Cited by 17 publications

References 17 publications

Correlation Degree and Clustering Analysis-Based Alarm Threshold Optimization

Correlation Degree and Clustering Analysis-Based Alarm Threshold Optimization

A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks

Research on Alarm Reduction of Intrusion Detection System Based on Clustering and Whale Optimization Algorithm

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