基于自适应多周期微分均值的轴承故障诊断
Bearing Fault Diagnosis Based on Adaptive Multi-period Differential Mean
陈鑫 1郭瑜 1徐万通 1樊家伟 1杨新敏1
作者信息
- 1. 昆明理工大学机电工程学院 昆明,650500
- 折叠
摘要
为解决瞬时角速度信号(instantaneous angular speed,简称IAS)中轴承故障特征微弱的难题,提出一种自适应多周期微分均值(adaptive multi-period differential mean,简称AMPDM)方法.首先,基于微分技术不受幅值干扰的优势,结合多周期均值的累积特性,提出一种多周期微分均值技术对IAS信号中轴承故障特征进行增强,进而抑制编码器安装误差、IAS估计误差和测量噪声等干扰分量;其次,采用一种改进诊断特征(improved diagnosis feature,简称IDF)指标评估在不同周期数K下增强信号中包含轴承故障信息的丰富性,并确定IDF值最大时对应的优化周期数Kop;最后,通过包络阶次谱分析揭示轴承故障特征.仿真和实验结果表明,AMPDM技术可有效增强IAS信号中轴承故障特征,并与可调整多点优化最小熵反卷积、倒谱预白化和快速谱相关3种算法对比,验证了所提方法的优势和有效性.
Abstract
To address the problem that the features of bearing in the instantaneous angular speed(IAS)signal are weak,an adaptive multi-period differential mean(AMPDM)tool is proposed.Firstly,based on the advan-tages of the differential tool without amplitude interference and the accumulative characteristic of multi-period,a multi-period differential mean tool is peoposed to enhence the features related to the faulty bearing in the IAS signal to suppress the interference components,such as the encoder installation error,IAS estimation error and measurem ent noise,etc.Secondly,an improved diagnosis feature(IDF)indicator is proposed to evaluate the richness of fault information contained in the enhanced signal under different period number K conditions,and an optimal Kop corresponding to the maximum IDF is determined.Finally,the envelope order spectrum analysis is used to reveal the features related to the faulty bearing.Simulation and experimental results show that the AMPDM can effectively enhance bearing fault features in the IAS signal,and compared with multipoint optimal minimum entropy deconvolution adjusted,cepstrum pre-whitening and cyclic spectral correlation,the advan-tages of the AMPDM are verified.
关键词
轴承故障/瞬时角速度/编码器信号/多周期微分均值Key words
bearing fault/instantaneous angular speed/encoder signal/multi-period differential mean引用本文复制引用
出版年
2024
NETL
NSTL
万方数据