摘要
针对行星齿轮箱的故障诊断问题,提出一种参数优化数学形态谱和支持向量机的行星齿轮箱故障识别方法。该方法考虑形态谱参数选择对同型故障一致性和不同故障差异性的影响,通过相对误差指标值的大小选择形态谱最优参数,对形态谱参数进行优化选择,提取故障特征,并采用支持向量机完成行星齿轮箱故障的故障识别。相较传统行星齿轮箱故障诊断而言,该方法对形态谱参数进行了定量分析,且无需复杂数学建模,和频率成分分析,简化故障识别过程。为了验证该方法的有效性,对行星齿轮箱试验台信号进行了分析实验,结果表明了该方法可有效地识别齿轮故障类型。
Aiming at the problem of fault diagnosis of planetary gearbox,a planetary gearbox fault identification method with mathematical pattern spectrum of optimal parameter and Support Vector Machine was proposed.The method considers the influence of selection with pattern spectral parameter on the homogeneity fault consistency and different fault variability.The optimal parameters for pattern spectrum are selected by the relative error index value,the parameters for pattern spectrum are optimized,the fault features are extracted,and support is adopted.The SVM completes the fault identification of the planetary gearbox failure.Compared with the traditional planetary gearbox fault diagnosis,quantitatively,this method analyzes the pattern spectral parameters,and does not require complex mathematical modeling and frequency component analysis to simplify the fault identification process.In order to verify the effectiveness of the method,the signal analysis of the planetary gearbox test bench is carried out.The results has been showed that the method can effectively identify the fault type of gear.
作者
黄丽丽
范业锐
张文兴
HUANG Li-li;FAN Ye-rui;ZHANG Wen-xing(School of Communication and Information,Jiangxi Environmental Engineering Vocational College,Ganzhou Jiangxi 341000,China;School of Mechanical Engineering,Inner Mongolia University of Science&Technology,Baotou Inner Mongolia 014010,China)
出处
《机械设计与制造》
北大核心
2021年第8期31-33,共3页
Machinery Design & Manufacture
基金
内蒙古自然科学基金重大项目(2018ZD06)。
关键词
支持向量机
形态谱
参数优化
相对误差率
行星齿轮箱
故障诊断
Support Vector Machine
Pattern Spectrum
Parameter Optimization
Planetary Gearbox
Fault Diagnosis
