FLAMES: A fuzzy logic ATMS and model-based expert system for analog diagnosis

Mohamed, Firas; Marzouki, Meryem; Touati, M.H.

doi:10.1109/edtc.1996.494158

Cited by 7 publications

(10 citation statements)

References 8 publications

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“…As a result, robust discrepancy detection methods are required which discriminate between inaccuracies and true faults. A number of different approaches can be found in MBR literature using possibility theory [16], fuzzy set theory [17], and probability [8].…”

Section: B Dealing With Model/world Differencesmentioning

confidence: 99%

A toolset for applying model-based reasoning techniques to diagnostics for power systems protection

Davidson

McArthur

McDonald

2003

IEEE Trans. Power Syst.

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Section: B Dealing With Model/world Differencesmentioning

confidence: 99%

A toolset for applying model-based reasoning techniques to diagnostics for power systems protection

Davidson

McArthur

McDonald

2003

IEEE Trans. Power Syst.

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“…Reasoning on assumptions is very general. In electronics, for example, an assumption might be the correct functioning of each component [32]. A resistance for example is modeled by:…”

Section: Fuzzy Atms Unit: Fuzzy Intervals Propagationmentioning

confidence: 99%

“…An expert can use this supplementary information and his experience to choose between candidates. When possible, the diagnosis can be helped by some rules describing the unit under test, its qualitative correct behavior and its faulty one [32].…”

Section: Fuzzy Atms Unit: Fuzzy Intervals Propagationmentioning

confidence: 99%

“…To move away from this approach with its heavy calculus and hard assumptions (a priori probabilities of modules, mutual exclusiveness of hypotheses, and conditional independence of evidence), we have considered an approach based on fuzzy logic. This approach which reduces the calculation needed, and replaces numbers by qualitative linguistic terms, has been developed within the laboratory [32].…”

Section: Best Test Strategiesmentioning

confidence: 99%

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Test and diagnosis of analog circuits: When fuzziness can lead to accuracy

Mohamed

Marzouki

1996

J Electron Test

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Editor: B. Kaminska Abstract.Testing and diagnosing analog circuits is a very challenging problem. The inaccuracy of measurement and the infinite domain of possible values are the principal difficulties. AI approaches were the base of many systems which tried to overcome these problems. The first part of this paper is a state of the art of this research area. We present two fundamental approaches, model-based reasoning and qualitative reasoning, and the systems implementing them; a discussion and an evaluation of these systems are given. In the second part, we present and propose a novel approach based on fuzzy logic in order to go further in dealing with analog circuits testing and diagnosis. Tolerance is treated by means of fuzzy intervals which are more general, more efficient and of higher fidelity to represent the imprecision in its different forms than other approaches. Fuzzy intervals are also able to be semi-qualitative which is more suitable to the simulation of analog systems. We use this idea to develop a best test point finding strategy based on fuzzy probabilities and fuzzy decision-making methodology. Finally, a complete expert system which implements this approach is presented.

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“…Günümüzde en yaygın kullanılan alarm ilintilendirme yöntemi model bazlı uzman sistemlerdir [4,9,10]. Bu uzman sistem çözümleri farklı yöntemlerle alarm ilintilendirme problemini çözmeye çalışmaktadır.…”

Section: Introductionunclassified

Alarm correlation using Apriori algorithm

Sarkan

Akcakoca

Kucukakdag

et al. 2015

2015 23nd Signal Processing and Communications Applications Conference (SIU)

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ÖZETÇEHaberleşme şebekeleri her gün milyonlarca alarm üreten binlerce ekipman içerebilmektedir. Sürdürülebilir kaliteli hizmeti sağlayabilmek için şebeke gözlem uzmanlarının bu alarmları incelemesi ve altlarında yatan arıza nedenlerini bulmaları gerekmektedir. Yüksek sayıda şebeke alarmının neden olduğu alarm kirliliği sadece şebeke gözlem uzmanlarının harcadığı zamanı arttırmaz, aynı zamanda önemli arızaların belirlenip giderilmesini geciktirir. Alarm kirliliği probleminin üstesinden gelmenin bir yöntemi şebeke aksaklıkları belirlenmeden alarmları filtreleyip sayısını azaltmaktır. Alarm ilintilendirme, aynı aksaklıklara işaret eden alarmları otomatik olarak belirleyip gruplayarak ilgilenilmesi gereken alarm sayısını azaltan bir tekniktir. Bu makalede, şebeke alarm tarihçesi incelenerek otomatik olarak alarm ilintilendirme kuralları üreten yeni bir istatistiksel yaklaşım sunulmaktadır. Bu çalışmada, ilintili alarm tipi gruplarının belirlenmesinde Pazar Sepet Analizi teknikleri arasında en bilinenlerden biri olan Apriori algoritması Kayan Zaman Penceresi tekniği ile beraber kullanılmıştır.Anahtar Kelimeler: Apriori algoritması; alarm ilintilendirme; sıra madenciliği; kayan zaman penceresi; pazar sepet analizi. ABSTRACTCommunication networks usually contain thousands of components producing millions of alarms every day. To ensure sustainable high quality network services, network surveillance experts need to inspect these alarms and determine the underlying faults. High number of network alarms cause alarm pollution which may cause not only extra time spent by the network surveillance experts but also delays in handling of important faults. One way of overcoming this alarm pollution problem is to filter and reduce the number of alarms before the network faults can be located. Alarm correlation techniques are used to automatically detect and group related alarms which point to the same root cause faults, and therefore they reduce the number of alarms. In this paper, we present new statistical approaches which automatically produce alarm correlation rules by investigating network alarm history. We apply the, Apriori algorithm which is one of the well-known Market Basket Analysis techniques together with the Sliding Time Window technique on alarm history in order to automatically determine correlated alarm type patterns.

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FLAMES: A fuzzy logic ATMS and model-based expert system for analog diagnosis

Cited by 7 publications

References 8 publications

A toolset for applying model-based reasoning techniques to diagnostics for power systems protection

A toolset for applying model-based reasoning techniques to diagnostics for power systems protection

Test and diagnosis of analog circuits: When fuzziness can lead to accuracy

Alarm correlation using Apriori algorithm

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