摘要
针对强背景噪声干扰且转速时变下滚动轴承微弱故障难以有效诊断的问题,提出加权奇异值分解(WSVD)重构结合极值点包络阶次跟踪的变转速滚动轴承微弱故障诊断方法。对于奇异值分解(SVD)后对故障特征子分量有效重构的问题,利用周期调制强度(PMI)表征各子分量故障特征信息,并对含有较多故障特征的子分量加权重构,实现微弱故障信号的信噪分离与特征增强;引入极值点包络阶次跟踪方法,通过求取重构信号的极值点包络,对其进行阶次跟踪,根据包络阶次谱图中的阶次信息对故障信息进行分析,达到微弱故障有效诊断的目的。变转速滚动轴承微弱故障的仿真和实例分析结果表明,与传统方法和其他方法相比,所提方法能有效增强微弱故障特征,去除噪声,准确诊断变转速下滚动轴承微弱故障。该方法为变转速下滚动轴承微弱故障诊断提供了新思路。
In view of the fact that the weak fault signal of rolling bearings under the conditions of strong background noise and time-varying rotating speed is difficult to be effectively detected,an improved singular value decomposition(SVD)method named Weighted SVD(WSVD)was proposed to separate the fault transient signal from strong noise.In the method,a factor of periodic modulation intensity(PMI)was introduced to weight the signal components with fault feature information in the original signal and obtain the reconstructed signal after signal-to-noise separation and feature enhancement.The extreme point envelope order tracking was applied to analyze the extreme point envelope of the reconstructed signal,and the weak fault of the rolling beraing was analyzed according to the order information in the envelope order spectrum.The simulation and experimental analysis results show that the proposed WSVD combinedly used with the extreme point envelope order tracking method can effectively show the weak fault characteristics and reliably detect the early fault feature and accurately diagnose the weak fault of rolling bearings under variable speed condition.
作者
张洲
张宏立
马萍
王聪
ZHANG Zhou;ZHANG Hongli;MA Ping;WANG Cong(College of Electrical Engineering,Xinjiang University,Urumqi 830047,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2021年第14期162-169,共8页
Journal of Vibration and Shock
基金
国家自然科学基金(51767022)
国家自然科学基金(51967019)
新疆维吾尔自治区自然科学基金(2019D01C082)。
关键词
加权奇异值重构(WSVD)
周期调制强度(PMI)
极值点包络阶次跟踪
变转速滚动轴承
微弱故障诊断
weighted singular value decomposition(WSVD)
periodic modulation intensity(PMI)
extreme point envelope order tracking
rolling bearing
weak fault diagnosis
variable-speed condition
