Research of Aircraft Integrated Drive Generator fault diagnostic decision based on attribute reduction in rough sets

For purpose of solve the problems of failure of multi-source and complex diagnostic decision in the process of Aircraft Integrated Drive Generator fault diagnosing, from the perspective of data mining, reference the variable precision rough sets to dispose the diagnostic information system, deduce j...

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Bibliographic Details
Published in2016 IEEE International Conference on Aircraft Utility Systems (AUS) pp. 393 - 397
Main Authors Tao Jing, Feiqi Long, Xudong Shi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2016
Subjects
Aircraft
Aircraft Integrated Drive Generator
Data Mine
Data mining
Diagnostic Decision
Fault diagnosis
Generators
Information systems
Maintenance engineering
Rough sets
Variable Precision Rough Sets
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DOI10.1109/AUS.2016.7748081

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Summary:For purpose of solve the problems of failure of multi-source and complex diagnostic decision in the process of Aircraft Integrated Drive Generator fault diagnosing, from the perspective of data mining, reference the variable precision rough sets to dispose the diagnostic information system, deduce judgment theorems for judging β lower approximation consistent sets by the binary relation and dependence space which defined by a set of objects, put forward the Aircraft Integrated Drive Generator fault diagnostic decision based on β lower approximation attribute reduction algorithm, which by decision system obtained from real generator output fault signal, to demonstrate its effectiveness and universality in case of small samples.
DOI:10.1109/AUS.2016.7748081