文章摘要
刘进,阎兆立,程晓斌,杨军,乔文孝.基于空化辐射噪声的检测方法实验研究[J].,2014,33(1):60-65
基于空化辐射噪声的检测方法实验研究
Experimental Research on Pump Cavitation Detection Based on Acoustic Radiation
投稿时间:2013-03-07  修订日期:2014-01-06
中文摘要:
      空化空蚀严重影响水利设备的正常工作和使用寿命,为此本文研究了基于水听器信号的水泵空化检测方法,从空化噪声辐射基本特性出发,分析并选取强度、脉冲以及频谱结构等特征参数组成最优分类特征向量,使其既有较强的稳定性,也有较好的灵敏度。以此特征向量训练获得的支持向量机(SVM)分类器进行水泵空化状态识别准确率平均能有99.6%。检测其他结构水泵的空化,识别准确率也在96.5%以上。在较高环境噪声单一能量特征无法识别的情况下,依然有较好的识别准确率。表明该方法对不同结构的水泵及较高环境噪声具有一定的鲁棒性,有较好的应用价值。
英文摘要:
      Cavitation is a dynamic phenomenon typically associated with liquid. Researches on acoustic methods for monitoring pump cavitation have been doing for the purpose of regular work and working life. A method of pump cavitation detection based on hydrophone signal was studied. An optimal feature vector, including energy, pulse, spectrum structure, was extracted based on the essential features of cavitation physical phenomenon and noise radiation in different degrees, which showed strong stability and good sensitivity. The experiment shows that the recognition accuracy average rate for cavitation condition is over 99.6%. and the accuracy rate is over 96.5% when the classifier is used to identify cavitation of other pumps. The cross-validation experiment shows that the proposed classifier has a good generality. The classifier is competent even in strong background noise. It shows that the method is robust for different pumps and different noise condition which has a better practical value.
DOI:10.11684/j.issn.1000-310X.2014.01.009
中文关键词: 空化检测,声辐射特征,分类准确率
英文关键词: Cavitaion detection, Acoustic radiation characteristics, Classification accuracy
基金项目:舰船声学故障识别中的样本扩容机理与容量控制研究
作者单位E-mail
刘进 中国石油大学(北京)中国科学院声学研究所 jsyzlj2010@yahoo.cn 
阎兆立 中国科学院声学研究所 zl_yan@mail.ioa.ac.cn 
程晓斌 中国科学院声学研究所  
杨军 中国科学院声学研究所  
乔文孝 中国石油大学(北京)  
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