摘要
针对柱塞泵早期故障时特征信号微弱的问题,首先对采集到的泵壳体振动信号进行极值域均值模式分解(extremum field mean mode decomposition,EMMD),得到有限模态分量IMF及余量C,然后对IMF分量进行Teager能量算子解调,提取特征频率点的能量信息组成能占比特征向量,并利用分类敏感度对向量进行筛选,最终获得有效特征向量。实验结果表明,采用EMMD-Teager方法能有效对信号进行滤波,方便从频域提取特征,经过筛选后的能占比特征向量可以准确分类柱塞泵正常、柱塞孔磨损及滑靴磨损3种状态。
Aiming at the difficulty in early fault diagnosis of pump,according to the method,the vibration signal of pump shell was decomposed into some intrinsic mode funtions(IMF) and residual quantity by extremum field mean mode decomposition;and then,we carried on Teager energy operator demodulation to IMF,and feature peaks appear on the spectrum.The energy information of feature frequency points is extracted to form the feature vector,and the classification sensitivity is used to filter the elements in the vector,and finally the effective feature vectors are obtained.The experimental results show that it can filter the signal effectively so that it can extract feature from spectrum by EMMD-Teager and three conditions contain normal,and the plunger hole wear and sliding shoe wear were clearly distinguished by filtered feature vector.
出处
《兵器装备工程学报》
CAS
2017年第10期165-170,共6页
Journal of Ordnance Equipment Engineering