文章摘要
吴 江.基于LVQ神经网络的飞机减震器故障预测[J].润滑与密封,2014,39(7):107-110
基于LVQ神经网络的飞机减震器故障预测
  
DOI:10.3969/j.issn.0254-0150.2014.07.022
中文关键词: 起落架  减震器  密封  LVQ神经网络  故障预测
英文关键词: landing gear  shock absorber  seal  LVQ neural network  fault prediction
基金项目:中国民航飞行学院重点科学基金项目(ZJ2012-04).
作者单位E-mail
吴 江 中国民航飞行学院 飞机修理厂 wjcafc@126.com 
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中文摘要:
      针对起落架减震器密封失效导致油液泄漏故障,提出一种利用LVQ神经网络对故障进行预测的方法。利用维修信息中的总起落次数、密封件使用时间、密封有效期间的起落次数和运行环境影响因子作为输入向量,油液是否泄漏作为输出向量,建立LVQ神经网络故障预测模型。利用历史维修信息对预测模型进行训练,将当前维修信息输入已训练好的预测模型,实现故障预测。仿真实例表明,该预测模型具有简捷、高效以及预测精度高的特点,使用该预测模型预测时,无需对输入向量进行预处理,预测结果与实际情况较吻合。
英文摘要:
      For oil leakage fault of landing gear shock absorber because of seal failure,a fault prediction method based on LVQ neural network was put forward.The maintenance data such as total flight takeoff landing number,seal ring working time,flight takeoff landing number in available period of seal and working environment impact factors were served as input vector,the oil leakage fault was served as output vector,a LVQ neural network fault prediction model was established.The historical maintenance data were presented to train the prediction model,the current maintenance data were inputted to the trained prediction model to achieve fault prediction.The simulation result of an example shows that the prediction model has the advantages of simplicity,high efficiency and high accuracy of prediction,the input vector is no need to be pretreated when using this prediction model,and the prediction results are in good accordance with the actual results.
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