中国机械工程Issue(12)：1659-1664,6.DOI:10.3969/j.issn.1004-132X.2014.12.019
基于量子遗传算法的轴向柱塞泵故障特征选择
Fault Feature Selection Method for Axial Piston Pump Based on Quantum Genetic Algorithm
摘要
Abstract
In order to reduce feature dimension ,shorten calculation time and improve classification accuracy ,a fault feature selection method for axial piston pump was proposed based on quantum ge-netic algorithm .In this method ,chromosomes were coded by quantum bits ,and population was up-dated with quantum gate .Firstly ,the vibration signals of axial piston pump were decomposed by wavelet transform ,and the statistic features were extracted from original signals and each wavelet co-efficient .Then ,the optimal feature set was selected form original feature set by QGA .Finally ,by u-sing neural network as classifier ,the optimal feature set was used as input for fault diagnosis .This proposed method was used for distinguishing different operating states of axial piston pump .The ex-perimental results show ,compared with common genetic algorithm ,QGA can reduce feature dimen-sion more effectively and improve classification accuracy greatly .关键词
量子计算/量子遗传算法/轴向柱塞泵/特征选择Key words
quantum computation/quantum genetic algorithm (QGA)/axial piston pump/feature selection分类
机械制造引用本文复制引用
李胜,张培林,李兵,王国德..基于量子遗传算法的轴向柱塞泵故障特征选择[J].中国机械工程,2014,(12):1659-1664,6.基金项目
国家自然科学基金资助项目 （）
