摘要
针对机械振动信号中存在大量噪声和形态学滤波中结构元素长度不能自适应调整的问题,提出一种可自适应调整结构元素长度的滚动轴承故障诊断新方法。结构元素长度的不同会导致对信号特征提取效果的不同,该方法通过以峭度值为指标,找寻出使峭度值较大的一系列结构元素长度。然后通过计算不同长度滤波后信号的故障特征频率能量比值,找寻出使故障特征最突出、最明显的结构元素长度。以此长度为最优长度对信号进行滤波,能够较好地提取出滚动轴承的故障特征,找到故障特征频率。
Aiming at the problem that the structure element length is not adaptively adjustable in morphological filter, a new method of bearing fault diagnosis is presented. In this method, the structure element length can be adjusted adaptively,and different length of the structure element can lead to different effect of the signal feature extraction. A series of structuralelement lengths corresponding to the maximum kurtosis values is found. Then, by calculating the fault- feature frequencyenergyratio of the signals filtered by different lengths, the length which makes the fault feature most prominent is found.With the length as the optimal length of the signal filtering, the fault feature of the bearings can be extracted, and the fault feature frequency can be found.
作者
王建东
马增强
李延忠
王梦奇
WANG Jian-dong;MA Zeng-qiang;LI Yan-zhong;WANG Meng-qi(School of Electrical and Electronic Engineering, Shijiazhuang Railway University,Shijiazhuang 050000, China)
出处
《噪声与振动控制》
CSCD
2017年第1期137-141,共5页
Noise and Vibration Control
基金
国家自然科学基金项目(11227201
11372199
11572206)
河北省自然科学基金项目(A2014210142)
关键词
振动与波
形态学滤波
自适应
峭度值
故障特征频率能量比值
vibration and wave
morphological filter
adaptive
kurtosis
fault feature frequency energy ratio
