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飞机液压系统故障诊断

李耀华 王星州

计算机工程与应用2019,Vol.55Issue(5):232-236,264,6.
计算机工程与应用2019,Vol.55Issue(5):232-236,264,6.DOI:10.3778/j.issn.1002-8331.1711-0029

飞机液压系统故障诊断

Fault Diagnosis of Aircraft Hydraulic System

李耀华 1王星州1

作者信息

  • 1. 中国民航大学 航空工程学院,天津 300300
  • 折叠

摘要

Abstract

In order to diagnose the faults of aircraft hydraulic system effectively, a method based on entropy weight and ABC-BP neural network is proposed, which is according to the signal of hydraulic system pressure. In this model,extraction of eigenvalues of aircraft hydraulic system pressure signal is the first step, and then, it calculates eigenvalue information entropy according to entropy weight method, the bigger of results as the input of the neural network, and in this paper, BP neural network is optimized by artificial bee colony through replacing the artificial bee colony fitness with the error function of BP neural network, finally, selecting the best fitness individual parameters as the weights and thresholds of the neural network ,this method not only reduces the input dimension of the model, but also improves the diagnostic accuracy. The simulation model of the landing gear retractable control system is established. The simulation results show that the diagnosis model has better fault diagnosis effect, and provides a new idea for the faults diagnosis of aircraft hydraulic system.

关键词

飞机液压系统/熵权法/信息熵/人工蜂群/反向传播(BP)神经网络/故障诊断

Key words

aircraft hydraulic system/ entropy weight method/ information entropy/ artificial bee colony/ Back Propaga-tion(BP)neural network/ fault diagnosis

分类

机械制造

引用本文复制引用

李耀华,王星州..飞机液压系统故障诊断[J].计算机工程与应用,2019,55(5):232-236,264,6.

基金项目

国家自然科学基金面上项目(No.61571314) (No.61571314)

四川省科技厅应用基础项目(No.2014JY0226) (No.2014JY0226)

国家高技术研究发展计划(863)(No.2013AA013803). (863)

计算机工程与应用

OA北大核心CSCDCSTPCD

1002-8331

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