摘要
针对往复压缩机气阀故障信号冲击性、非连续性特点,采用EMD方法分解提取各频率故障信号。然后通过对数据重新筛选、提出主要振动信息对分解波形进行了重构。并对往复压缩机故障信号分解及重构数据进行了分析,提取了故障信息。针对正常与故障信号分解结果复杂度不一致的特点,对EMD分解后包含的故障信息主要分量进一步通过样本熵进行量化识别。最后通过对正常、阀片缺口、弹簧失效的实测信号进行EMD分解、重构和样本熵分析,精确提取了故障信息,验证了方法的有效性。
Aiming at the characteristics of fault signals of for a reciprocating compressor valve：shock and discontinuity, the EMD method was taken to decompose and extract the fault signal of every frequency, which was reconstructed through screening the data and finding the main vibration information. The decomposition results and recon-struction data of the reciprocating compressor fault signals were analyzed, and the fault information was extracted. For the complexity of decomposition results of the normal and fault signal, the sample entropy（ SampEn） method was used to quantitatively analyze the fault information of every main IMF. EMD combined with reconstruction, and SampEn methods were applied to analyze the vibration signals of three kinds of conditions：normal state, valve gap, and valve less spring. The practical application abstracted the fault information exactly and proved the feasibility of the proposed method.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2014年第6期696-700,共5页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(10772061)
关键词
往复压缩机
压缩机气阀
经验模态分解
气阀故障
信息重构
量化分析
样本熵
reciprocating compressor
compressor value
empirical model decomposition（ EMD）
valve faults
in-formation reconstruction
quantitative analysis
sample entropy（ SampEn）
作者简介
张思阳（1971-），男，高级工程师；通信作者：张思阳，E-mail：z90sy@163．com
徐敏强（1965-），男，教授，博士生导师
