Intelligent automatic fault detection for actuator failures in aircraft

C. H. Lo; Eric H.K. Fung; Y. K. Wong

doi:10.1109/TII.2008.2008642

Intelligent automatic fault detection for actuator failures in aircraft

C. H. Lo, Eric H.K. Fung, Y. K. Wong

Division of Science, Engineering and Health Studies (SEHS)

Research output: Contribution to journal › Article › peer-review

49 Citations (Scopus)

Abstract

This paper applies an intelligent technique based on fuzzy-genetic algorithm for automatically detecting failures in aircraft. The fuzzy-genetic algorithm constructs the automatic fault detection system for monitoring aircraft behaviors. Fuzzy-based classifier is employed to estimates the time of occurrence and types of actuator failure. Genetic algorithms are used to generate an optimal fuzzy rule set for the classifier. The optimization capability of genetic algorithms provides an efficient and effective way to generate optimal fuzzy rules. Different types of actuator failure can be detected online by the fuzzy-genetic algorithm based automatic fault detection system. Simulations with different actuator failures of the nonlinear F-16 aircraft model are reported and discussed.

Original language	English
Article number	4773154
Pages (from-to)	50-55
Number of pages	6
Journal	IEEE Transactions on Industrial Informatics
Volume	5
Issue number	1
DOIs	https://doi.org/10.1109/TII.2008.2008642
Publication status	Published - Feb 2009

Keywords

Actuators failure
Fault diagnosis
Fuzzy system
Genetic algorithm

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10.1109/TII.2008.2008642

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title = "Intelligent automatic fault detection for actuator failures in aircraft",

abstract = "This paper applies an intelligent technique based on fuzzy-genetic algorithm for automatically detecting failures in aircraft. The fuzzy-genetic algorithm constructs the automatic fault detection system for monitoring aircraft behaviors. Fuzzy-based classifier is employed to estimates the time of occurrence and types of actuator failure. Genetic algorithms are used to generate an optimal fuzzy rule set for the classifier. The optimization capability of genetic algorithms provides an efficient and effective way to generate optimal fuzzy rules. Different types of actuator failure can be detected online by the fuzzy-genetic algorithm based automatic fault detection system. Simulations with different actuator failures of the nonlinear F-16 aircraft model are reported and discussed.",

keywords = "Actuators failure, Fault diagnosis, Fuzzy system, Genetic algorithm",

author = "Lo, {C. H.} and Fung, {Eric H.K.} and Wong, {Y. K.}",

note = "Funding Information: Manuscript received June 27, 2008; revised September 10, 2008. First published February 03, 2009; current version published March 06, 2009. This work was supported by the Hong Kong Polytechnic University under Project A-PG68. Paper no. TII-08-06-0083.R1.",

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AB - This paper applies an intelligent technique based on fuzzy-genetic algorithm for automatically detecting failures in aircraft. The fuzzy-genetic algorithm constructs the automatic fault detection system for monitoring aircraft behaviors. Fuzzy-based classifier is employed to estimates the time of occurrence and types of actuator failure. Genetic algorithms are used to generate an optimal fuzzy rule set for the classifier. The optimization capability of genetic algorithms provides an efficient and effective way to generate optimal fuzzy rules. Different types of actuator failure can be detected online by the fuzzy-genetic algorithm based automatic fault detection system. Simulations with different actuator failures of the nonlinear F-16 aircraft model are reported and discussed.

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Intelligent automatic fault detection for actuator failures in aircraft

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Keywords

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