基于阈值降噪的行星传动轮系特征故障诊断  

Fault Diagnosis of Planetary Gear System Based on Threshold De-noising

作　　者：龙雄辉[1] 

机构地区：[1]广州铁路职业技术学院实训管理与设备处,广东广州510430

出　　处：《科技通报》2014年第8期71-73,共3页Bulletin of Science and Technology

基　　金：广州市教育科学规划青年专项课题(11B099)

摘　　要：行星传动齿轮故障信号频谱中蕴含重要的特征信息,但故障信号湮没大量噪声,通常的谱分析算法难于有效提取故障特征。提出一种多维小波分块阈值降噪方法,通过计算行星轮内环通过频率特征、外环通过频率特征和自转频率特征,得到加速度频谱和位移频谱双频谱,实现对行星轮故障的双谱分析。仿真实验通过建构信号和行星传动轮系多分布点采集故障信号进行测试。结果表明,降噪算法比传统算法性能优越,可以有效诊断齿轮故障,得出诊断结论,有效实现故障状态监测。The planetary gear fault signal contains important information, but it also contains lots of noise. Traditional spec-trum method cannot effectively extract the fault characteristic spectrum. An improved block threshold de-noising method with multidimensional wavelet analysis was proposed for noise reduction. Through the calculation of planetary ring through a frequency characteristic, the outer ring frequency characteristics and the rotation frequency characteristics, we got the ac-celeration spectrum and the displacement spectrum as the double spectrum. Simulation was implemented with the real multi point distribution fault signal. Simulation result shows that noise reduction algorithm is superior to traditional algo-rithm, and it can effectively diagnose the gear fault diagnosis with the detail conclusions. It can be applied in the real-time fault monitoring.

关 键 词：小波 行星齿轮 频谱分析 故障诊断 

分 类 号：TH165.3[机械工程—机械制造及自动化]