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A hierarchical symptom classification for model based causal reasoning

Authors:

C. Lee,

P. Liu,

S. Clark,

M. Y. ChiuAuthors Info & Claims

IEA/AIE '88: Proceedings of the 1st international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1

Pages 54 - 59

https://doi.org/10.1145/51909.51916

Published: 03 June 1988 Publication History

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Abstract

Model based causal reasoning has been widely used for physical systems diagnosis. The system fault is localized with the causal relation of system structure and behavior. In such applications, if the system fault is not localized with the observed behavior, then a subsequent observation is made. This research studies a hierarchical symptom classification for guiding a subsequent observation in model based causal reasoning. The diagnostic symptoms are mapped to the system functional hierarchy and the symptoms are classified by partitioning the functional hierarchy. The dependency relation of symptoms guides subsequent observation. This strategy enhances the control of subsequent observation by hierarchically structuring and classifying the symptoms.

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Sottile JHolloway L(1994)An overview of fault monitoring and diagnosis in mining equipmentIEEE Transactions on Industry Applications10.1109/28.31524730:5(1326-1332)Online publication date: Jan-1994
https://doi.org/10.1109/28.315247
Sottile JHolloway L(1992)Fault monitoring and diagnosis in mining equipment: current and future developmentsConference Record of the 1992 IEEE Industry Applications Society Annual Meeting10.1109/IAS.1992.244201(2026-2033)Online publication date: 1992
https://doi.org/10.1109/IAS.1992.244201
Holloway LKrogh B(1990)Fault detection and diagnosis in manufacturing systems: a behavioral model approach[1990] Proceedings. Rensselaer's Second International Conference on Computer Integrated Manufacturing10.1109/CIM.1990.128107(252-259)Online publication date: 1990
https://doi.org/10.1109/CIM.1990.128107

Index Terms

A hierarchical symptom classification for model based causal reasoning

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Published In

IEA/AIE '88: Proceedings of the 1st international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1

June 1988

636 pages

ISBN:0897912713

DOI:10.1145/51909

Editor:
Moonis Ali
Univ. of Tennessee Space Institute, Tullahoma, TN

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 June 1988

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IEA/AIE88

Sponsor:

SIGAI

IEA/AIE88: 1st International Conference on Idustrial and Engineer Application of Art. Intell & Expert Sys.

June 1 - 3, 1988

Tennessee, Tullahoma, USA

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Cited By

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Sottile JHolloway L(1994)An overview of fault monitoring and diagnosis in mining equipmentIEEE Transactions on Industry Applications10.1109/28.31524730:5(1326-1332)Online publication date: Jan-1994
https://doi.org/10.1109/28.315247
Sottile JHolloway L(1992)Fault monitoring and diagnosis in mining equipment: current and future developmentsConference Record of the 1992 IEEE Industry Applications Society Annual Meeting10.1109/IAS.1992.244201(2026-2033)Online publication date: 1992
https://doi.org/10.1109/IAS.1992.244201
Holloway LKrogh B(1990)Fault detection and diagnosis in manufacturing systems: a behavioral model approach[1990] Proceedings. Rensselaer's Second International Conference on Computer Integrated Manufacturing10.1109/CIM.1990.128107(252-259)Online publication date: 1990
https://doi.org/10.1109/CIM.1990.128107

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Causal Reasoning and Meno’s Paradox

A causal model for diagnostic reasoning

Causal reasoning: initial report of a naturalistic study of causal inferences