自适应Chirplet快速变换在轴承故障诊断中的应用

在故障诊断中,针对当前各种时频分析方法存在的问题,作者提出一种基于自适应Chirplet变换的故障诊断方法.该方法在参数粗搜索的基础上,将多维参数的最优化过程转化为传统的曲线拟合问题,不仅解决了交叉干扰项和时频分辨率之间的冲突,而且还具有计算量小、运算速度快和参数估计精度高等优点.实验结果表明,该算法能够有效地提取故障轴承振动信号的时频特征,其诊断效果明显优于其他时频分析方法,因此,是一种有效的故障诊断方法.

Application of fast adaptive Chirplet transform in fault diagnosis of bearing

Aiming at the problems existed in all other TF(time-frequency) analysis methods in the fault diagnosis,a method based on the adaptive Chirplet transform was presented.Based on parameter coarse estimation,it convertsed multi-dimension optimization process to a traditional curve-fitting problem,not only solved the conflict between cross-term interference and TF resolution,but also had some merits,such as computational speed was fast and parameters estimation was more accurate.Experimental results showed that ...