Analytical Derivation and Comparison of Alarm Similarity Measures

Kargaran, Amir Hossein; Neshastegaran, Amir; Izadi, Iman; Yazdian, Ehsan

doi:10.1016/j.ifacol.2021.08.268

Cited by 1 publication

(10 citation statements)

References 12 publications

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“…Thus, only one of them is kept by merging the two rules into one. The same conclusion is also drawn for first-out rules TP201PV (6).PVHI ⇒ QI400.PVHI and QI204.PVHI ⇒ QI400.PVHI, as they hold significant redundancy according to the hypothesis test. In Figure 7, TP201PV (6).PVHI, TP401PV(4).PVHI, and TP401PV (5).PVHI are the first-out alarms for PC210.PVLL, and after hypothesis testing, it is found that there is no redundancy relationship among the three, so that all the three rules need to be retained.…”

Section: Scenariosupporting

confidence: 68%

“…Under this scenario, an example of first-out rules that should be merged is presented. In Figure 8, TP201PV (6).PVHI is the first-out alarm for QC170.PVLL and QI200.PVLL, and TC202.PVHI is the first-out alarm for TP201PV (6).PVHI, QC170.PVLL and QI200.PVLL. Thus, it needs to be determined whether these two first-out rules should be merged into one first-out rule.…”

Section: Scenariomentioning

confidence: 99%

“…In Figure 7, TP201PV (6).PVHI, TP401PV(4).PVHI, and TP401PV (5).PVHI denote that the temperatures in the reactor (sensor 6), absorber (sensor 4), and absorber (sensor 5) reach a high level and exceed the high alarm limits, thus triggering the corresponding alarms. The alarm TP201PV (6).PVHI is located at a different unit compared to TP401PV(4).PVHI and TP401PV (5).PVHI, and thus their occurrences are not correlated. Alarms TP401PV(4).PVHI and TP401PV (5).PVHI are located at different positions of the reactor and thus also have low correlations.…”

Section: Scenariomentioning

confidence: 99%

“…References [4,5] studied and compared quite a few similarity coefficients and correlation measurements for detection of correlated alarms; in [5], Sorgenfrei and Jaccard coefficients were selected to measure the correlations between binary-valued alarm signals. An event correlation analysis method was designed in [6] to identify the correlated alarms, as well as to detect the relations between alarms and actions. In view of the negative influences caused by random delays between alarm occurrences, binary signals were transformed into continuous-valued pseudo signals in [7,8], and reference [8] proposed a statistical test based on the random occurrence delays to determine correlated alarms.…”

Section: Introductionmentioning

confidence: 99%

“…From the bottom of the item header table, sequentially find the conditional pattern base I k and its corresponding conditional pattern tree. 6.…”

mentioning

confidence: 99%

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A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis

Li,

Cheng

2023

Entropy

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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.

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Section: Scenariosupporting

confidence: 68%

Section: Scenariomentioning

confidence: 99%