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Fault detection of aircraft engine components using fuzzy unordered rule induction algorithm

Htike@Muhammad Yusof, Zaw Zaw and Nyein Naing, Wai Yan (2016) Fault detection of aircraft engine components using fuzzy unordered rule induction algorithm. In: International Conference on Mechanical, Automotive and Aerospace Engineering, 25-27 Jul 2016, Kuala Lumpur, Malaysia. (Unpublished)

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Abstract

Nondestructive Fault monitoring is of paramount importance in safety and reliability of aircraft engine operations and timely maintenance of its critical components. There have been numerous attempts by researchers to tackle the problem of nondestructive fault monitoring. The bottleneck in nondestructive fault monitoring lies in data analysis. State-of-the-art systems are not accurate due to high dimensionality of sensory data. This paper proposes auto encoder neural network for compressing of high dimensional sensory data and classification using Fuzzy Unordered Rule Induction Algorithm (FURIA) with emphasis on detection and isolation of incipient faults. The preliminary results demonstrate the efficacy of the proposed system.

Item Type: Conference or Workshop Item (Other)
Additional Information: 6919/54867
Subjects: A General Works > AC Collections. Series. Collected works
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: . . .
Date Deposited: 08 Feb 2017 03:31
Last Modified: 22 May 2018 09:10
URI: http://irep.iium.edu.my/id/eprint/54867

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