[1]贺国,曹玉良,明廷锋,等.基于改进倍频带特征的离心泵空化状态识别[J].哈尔滨工程大学学报,2017,38(08):1263-1267,1302.[doi:10.11990/jheu.201611027]
 HE Guo,CAO Yuliang,MING Tingfeng,et al.Cavitation state recognition of centrifugal pump based on features of modified octave bands[J].hebgcdxxb,2017,38(08):1263-1267,1302.[doi:10.11990/jheu.201611027]
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基于改进倍频带特征的离心泵空化状态识别(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
38
期数:
2017年08期
页码:
1263-1267,1302
栏目:
出版日期:
2017-08-25

文章信息/Info

Title:
Cavitation state recognition of centrifugal pump based on features of modified octave bands
作者:
贺国1 曹玉良2 明廷锋2 苏永生2
1. 海军工程大学 管理工程系, 湖北 武汉 430033;
2. 海军工程大学 动力工程学院, 湖北 武汉 430033
Author(s):
HE Guo1 CAO Yuliang2 MING Tingfeng2 SU Yongsheng2
1. Department of Management Science, Naval University of Engineering, Wuhan 430033, China;
2. College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
关键词:
离心泵空化状态识别振动信号频带特征神经网络倍频带
分类号:
U664.33
DOI:
10.11990/jheu.201611027
文献标志码:
A
摘要:
空化状态识别是离心泵状态监测的难点之一。对离心泵的空化进行了试验研究,采集了三种转速时泵壳上两个位置处的振动信号,根据离心泵的特点对标准倍频带进行改进,基于改进倍频带和标准倍频带构建了振动信号的特征向量,利用BP神经网络对离心泵的四类空化状态进行识别。研究表明:改进倍频带比标准倍频带更能有效地提取离心泵空化振动信号的特征;利用任意一处振动信号的频带特征都能够有效地识别扬程降低大于3%的严重空化状态,联合利用两处振动信号的频带特征能够有效地提高对正常状态和空化程度较轻状态的识别率。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-11-06。
基金项目:国家自然科学基金资助项目(51306205);湖北省自然科学基金项目(2015CFB700);海军工程大学博士生创新基金项目(4142C15K).
作者简介:贺国(1965-),男,教授,博士生导师;曹玉良(1988-),男,博士研究生.
通讯作者:曹玉良,E-mail:yuliangc@126.com
更新日期/Last Update: 2017-08-28