基于量子计算的独立分量分析算法及应用  

Independent Component Analysis Algorithm and Application Based on Quantum Computation

作　　者：黄晋英[1] 潘宏侠[1] 李悦[1] 常晓磊[1] 

机构地区：[1]中北大学机械与动力工程学院太原,030051

出　　处：《振动．测试与诊断》2014年第1期173-178,197,共6页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(50875247);山西省自然科学基金资助项目(2009011026-1);中北大学校基金资助项目(20130203)

摘　　要：将量子优化原理应用于独立分量分析中,提出了量子独立分量分析算法(quantum independent component analysis,简称QICA),针对3组特定信号进行了混合与分离的仿真实验,得到了较好的分离效果。将该算法用于齿轮箱振动信号的源分离及其故障诊断中,实验结果表明,该算法用于齿轮箱振动信号分离可以明显增强故障信息,降低齿轮箱故障诊断难度。Immune quantum optimization theory is applied to independent component analysis.By elaborated on blind source separation procedure based on quantum optimization algorithm is put forward,that is QICA algorithm.Simulation experiments of mixing and separation for three specific signals are carried out.The experimental results show that it has good separation effect.The new algorithm is used to gearbox vibration signals for blind source separation and fault diagnosis.Results show that the algorithm used to separate vibration signals of gearbox can greatly enhance fault information,reducing difficulty of gearbox fault diagnosis.

关 键 词：量子优化 独立分量分析 量子独立分量分析 故障诊断 

分 类 号：TH133[机械工程—机械制造及自动化] TH115