摘要
针对在强背景噪声下,往复机械振动信号中冲击的次数及位置信息难以准确辨识的问题,提出一种结合总体经验模态分解(ensemble empirical mode decomposition,简称EEMD)和自适应变尺度形态学滤波器(adaptive variable scale morphological filter,简称AVSMF)的冲击特征提取方法。通过对信号进行EEMD,由峭度、相关系数指标筛选出隐含冲击成分的本征模态分量(intrinsic mode function,简称IMF),并根据各阶IMF的波形尺度与极值点幅值分布特性,为IMF中每个采样点选择合适的元素宽度进行级联式形态学滤波,实现冲击特征提取。针对信号中冲击成分难以精确定位的问题,提出一种自适应峰值相位检测算法。50次重复仿真实验结果表明,该算法具有较高的精度与稳定性。通过对一台闪蒸气双作用往复式压缩机的低压缸中体加速度信号进行冲击检测,验证了所提算法进行故障早期诊断有效性与准确性。
Faults of reciprocating compressor are observed as impacts in the vibration signal,but their information such as number and location within a period is difficult to identify because of the severe background noise.Therefore,this paper presents an innovative approach to extract impact features from the vibration signal based on combining ensemble empirical mode decomposition(EEMD)method with an adaptive variable scale morphological filter(AVSMF).The method can extract impact components without previous fault information.Since it is difficult to accurately locate the impact components in a signal,an adaptive impact positioning algorithm is proposed.After smoothing the Hilbert envelope of the signal filtered with Teager energy operator,the location of the impacts can be determined.Repeated simulation experiments are carried out 50 times on impact signals with different frequencies and amplitudes.The results show that the algorithm has high accuracy,precise and stability.The effectiveness and accuracy of the proposed algorithm for early fault diagnosis is also verified by impact detection of the low pressure cylinder mid-body acceleration signal of a flash gas double-acting reciprocating compressor.
作者
方志法
王维民
曹颜玉
张秀林
李启行
孟繁城
吴斯琪
赵乐
王志刚
FANG Zhifa;WANG Weimin;CAO Yanyu;ZHANG Xiulin;LI Qihang;MENG Fancheng;WU Siqi;ZHAO Le;WANG Zhigang(Beijing Key Laboratory of Health Monitoring and Self-Recovery for High-End Mechanical Equipment,Beijing University of Chemical Technology Beijing,100029,China;Offshore Oil Engineering Co.,Ltd.Tianjin,300461,China;CNOOC(China)Co.,Ltd.Hainan Branch Haikou,570311,China)
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2023年第4期698-704,828,共8页
Journal of Vibration,Measurement & Diagnosis
基金
国家自然科学基金资助项目(92160203)。
关键词
冲击特征提取
形态学滤波
往复压缩机
故障诊断
impact feature extraction
morphological filter
reciprocating compressor
fault diagnosis
