摘要
研究了小波包分解和矩阵分形相结合在齿轮箱故障诊断中的应用,讨论了小波包分解的计算方法和分形矩阵的计算方法。首先对采集的齿轮箱各种工况信号运用小波包三重分解的方法对进行分解,通过计算其分解得到的分量信号的广义维数构建分形矩阵,分析发现在不同工况下通过小波包分解得到的分形矩阵明显不同。通过计算样本信号和待检测信号的相关系数,用柱状图做直观比较确定了待检测信号故障类型,验证了该方法能够有效应用于应齿轮箱故障诊断中。
The wavelet packet decomposition and matrix fractal combined gearbox fault diagnosis,discussed the calculation method based on wavelet packet decomposition and fractal matrix. First,various conditions gearbox signal wavelet packet double decomposition,by calculating its generalized fractal dimension construct matrix analysis found that under different conditions by fractal matrix of wavelet packet decomposition was significantly different,and by computing the signal of sample and correlation coefficient of the signal to be detected,the fault types of the signal to be detected was determined by the intuitive comparison of histogram,the method can be applied should gearbox fault diagnosis.
出处
《机械设计与制造》
北大核心
2016年第4期20-23,共4页
Machinery Design & Manufacture
基金
国家自然科学基金项目:基于粒子群优化和滤波技术的复杂传动装置早期故障诊断研究(50875247)
关键词
小波包分解
矩阵分形
齿轮箱
故障诊断
Wavelet Packet Decomposition
Matrix Fractal
Gear Box
Fault Diagnosis
