|本期目录/Table of Contents|

[1]汤明敏,王华,黄筱调.基于多特征参量的回转支承智能健康状态评估[J].南京工业大学学报(自然科学版),2014,36(02):101-106.[doi:10.3969/j.issn.1671-7627.2014.02.017]
 TANG Mingmin,WANG Hua,HUANG Xiaodiao.Intelligent health condition assessment on slewing bearing based on multiple characteristic parameters[J].Journal of NANJING TECH UNIVERSITY(NATURAL SCIENCE EDITION),2014,36(02):101-106.[doi:10.3969/j.issn.1671-7627.2014.02.017]
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基于多特征参量的回转支承智能健康状态评估()
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《南京工业大学学报(自然科学版)》[ISSN:1671-7627/CN:32-1670/N]

卷:
36
期数:
2014年02期
页码:
101-106
栏目:
出版日期:
2014-03-30

文章信息/Info

Title:
Intelligent health condition assessment on slewing bearing based on multiple characteristic parameters
文章编号:
1671-7627(2014)02-0101-06
作者:
汤明敏王华黄筱调
南京工业大学 机械与动力工程学院,江苏 南京 210009
Author(s):
TANG MingminWANG HuaHUANG Xiaodiao
College of Mechanical and Power Engineering,Nanjing Tech University,Nanjing 210009,China
关键词:
多特征参量 健康评估 Elman网络 遗传算法 回转支承
Keywords:
multiple characteristic parameters health assessment Elman network genetic algorithm slewing bearing
分类号:
TP183
DOI:
10.3969/j.issn.1671-7627.2014.02.017
文献标志码:
A
摘要:
为了提高回转支承运行可靠性,及时发现其潜在的失效,实施良好的设备维护与管理,有必要对其进行健康状态评估。选取表征回转支承健康状态的温度和扭矩作为特征参量,建立了一种采用遗传算法优化动态递归Elman神经网络的回转支承多参量健康状态评估模型,并利用3 MW变桨回转支承疲劳寿命实验数据对该模型进行了网络训练和测试。结果表明,该模型评估结果与实验值相符,可准确地对回转支承进行健康状态评估。
Abstract:
It was necessary to estimate their health conditions of slewing bearing, improve its operational reliability, and find out the potential fault and implement good equipment maintenance and management. The temperature and the torque were selected as characteristic parameters, they reflected slewing bearing status. Then, a multi-parameter health state evaluation model was established with Elman dynamic recursive neural network based on genetic algorithm(GA). Finally, the model was trained and tested by test data from 3 MW variable pitch slewing bearing fatigue life experiments. Results showed that the evaluation results from the model were in agreement with experiment data, and the model could preciously assess the health state of slewing bearing.

参考文献/References:

[1] 王兴东,刘源,严爱军,等.大型回转支承寿命预测方法的研究[J].湖北工业大学学报:自然科学版,2006,21(3):33-36.
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备注/Memo

备注/Memo:
收稿日期:2013-05-13
基金项目:国家自然科学基金(51105191); 江苏省自然科学基金(BK2011797); 江苏省高校“青蓝工程”
作者简介:汤明敏(1989—),男,江苏常州人,硕士,主要研究方向为机械制造及自动化; 王华(联系人),副教授, E-mail:wanghua0710@126.com..
更新日期/Last Update: 2014-03-20