Using non-monotonic reasoning to manage uncertainty in railway asset diagnostics

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Using non-monotonic reasoning to manage uncertainty in railway asset diagnostics. / Lewis, Richard; Roberts, Clive.

In: Expert Systems with Applications, Vol. 37, No. 5, 21.10.2009, p. 3616-3623.

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@article{49340e327a6e42aa8d183542fddd8890,
title = "Using non-monotonic reasoning to manage uncertainty in railway asset diagnostics",
abstract = "When a system instantaneous fails there is no time to perform preventative maintenance. In certain circumstances, where the system subsequently recovers without intervention, the system is left to run undiagnosed. Increasing the certainty of a particular diagnosis leads to a greater likelihood of the corrective action being carried out. Therefore, moving to a situation where available symptom and associated condition data is used to diagnose a failure is desirable. This paper proposes the implementation of a distributed network of semantic nodes that supports the inference of asset status. Querying is then performed to produce concrete facts regarding the status of the asset. The facts are used to support non-monotonic, probabilistic reasoning to increase the certainty that a particular symptom is the cause of the instantaneous failure. (C) 2009 Elsevier Ltd. All rights reserved.",
keywords = "Description logics, Ontology, Railway diagnostics, Non-monotonic reasoning",
author = "Richard Lewis and Clive Roberts",
year = "2009",
month = oct,
day = "21",
doi = "10.1016/j.eswa.2009.10.030",
language = "English",
volume = "37",
pages = "3616--3623",
journal = "Expert Systems with Applications",
issn = "0957-4174",
publisher = "Elsevier",
number = "5",

}

RIS

TY - JOUR

T1 - Using non-monotonic reasoning to manage uncertainty in railway asset diagnostics

AU - Lewis, Richard

AU - Roberts, Clive

PY - 2009/10/21

Y1 - 2009/10/21

N2 - When a system instantaneous fails there is no time to perform preventative maintenance. In certain circumstances, where the system subsequently recovers without intervention, the system is left to run undiagnosed. Increasing the certainty of a particular diagnosis leads to a greater likelihood of the corrective action being carried out. Therefore, moving to a situation where available symptom and associated condition data is used to diagnose a failure is desirable. This paper proposes the implementation of a distributed network of semantic nodes that supports the inference of asset status. Querying is then performed to produce concrete facts regarding the status of the asset. The facts are used to support non-monotonic, probabilistic reasoning to increase the certainty that a particular symptom is the cause of the instantaneous failure. (C) 2009 Elsevier Ltd. All rights reserved.

AB - When a system instantaneous fails there is no time to perform preventative maintenance. In certain circumstances, where the system subsequently recovers without intervention, the system is left to run undiagnosed. Increasing the certainty of a particular diagnosis leads to a greater likelihood of the corrective action being carried out. Therefore, moving to a situation where available symptom and associated condition data is used to diagnose a failure is desirable. This paper proposes the implementation of a distributed network of semantic nodes that supports the inference of asset status. Querying is then performed to produce concrete facts regarding the status of the asset. The facts are used to support non-monotonic, probabilistic reasoning to increase the certainty that a particular symptom is the cause of the instantaneous failure. (C) 2009 Elsevier Ltd. All rights reserved.

KW - Description logics

KW - Ontology

KW - Railway diagnostics

KW - Non-monotonic reasoning

U2 - 10.1016/j.eswa.2009.10.030

DO - 10.1016/j.eswa.2009.10.030

M3 - Article

VL - 37

SP - 3616

EP - 3623

JO - Expert Systems with Applications

JF - Expert Systems with Applications

SN - 0957-4174

IS - 5

ER -