摘要
船用柴油机轴瓦磨损引起的振动通常表现为具有一定随机性的周期性脉冲响应,属于多分量信号,通常被其它确定性分量所掩盖,这会降低传统包络分析用于故障特征提取的效率。为了提取船用柴油机曲轴轴瓦弱故障特征,采用Hilbert变换在时域和频域计算包括离散频率分量和循环冲激响应在内的多分量信号的包络。信号的平方包络通过零频率谐振器以精确定位周期脉冲。谐振器输出的频谱在故障频率处出现峰值。用周期脉冲模拟噪声信号解释该算法的工作原理。以实验数据验证该方法有效。通过与基于Hilbert-Haung变换(HHT)的方法的比较,证明该方法的有效性。
The vibration caused by wear of bearing bushes usually shows periodic impulse response with certain randomness in marine diesel engines,which belongs to multi-component signal,and was usually covered by some other deterministic components,which will reduce the efficiency of traditional envelope analysis in fault feature extraction.In order to extract the weak fault features of the crankshaft bearing bushes of marine diesel engines,Hilbert transform in time domain and frequency domains was used to calculate the envelope of multi-component signal including discrete frequency component and cyclic impulse response.The square envelope of the signal was used to accurately locate the periodic pulse through the zero frequency resonator.A peak appeared at the fault frequency in the output frequency spectrum of the resonator.The working principle of the algorithm was explained by simulating the noise signal with periodic pulse.The effectiveness of the method was also verified by experimental data.Compared with the method based on Hilbert Haung transform(HHT),the effectiveness of this method is proved.
作者
李炳强
周宏根
刘金峰
康超
LI Bingqiang;ZHOU Honggen;LIU Jinfeng;KANG Chao(School of Mechanical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,Jiangsu,China)
出处
《噪声与振动控制》
CSCD
北大核心
2021年第5期134-138,168,共6页
Noise and Vibration Control
基金
国防基础科研资助项目(JCKY2018414C015)。
关键词
故障诊断
多分量信号
轴瓦
弱故障信号
fault diagnose
multi-component signal
rolling bearing bush
weak fault signal
作者简介
李炳强(1986-),男,沈阳市人,博士,讲师,主要研究方向为非线性振动、故障诊断研究。E-mail:ibingqiang@aliyun.com。
