[1]马大中,张化光,冯 健,等.一种基于多传感器信息融合的故障诊断方法[J].智能系统学报,2009,4(1):72-75.
MA Da-zhong,ZHANG Hua-guang,FENG Jian,et al.A fault diagnosis method based on multi-sensor information fusion[J].CAAI Transactions on Intelligent Systems,2009,4(1):72-75.
点击复制
MA Da-zhong,ZHANG Hua-guang,FENG Jian,et al.A fault diagnosis method based on multi-sensor information fusion[J].CAAI Transactions on Intelligent Systems,2009,4(1):72-75.
一种基于多传感器信息融合的故障诊断方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
4
期数:
2009年第1期
页码:
72-75
栏目:
学术论文—智能系统
出版日期:
2009-02-25
- Title:
- A fault diagnosis method based on multi-sensor information fusion
- 文章编号:
- 1673-4785(2009)01-0072-04
- Keywords:
- D-S evidence theory; fault diagnosis; multisensor; information fusion
- 分类号:
- TP206.3
- 文献标志码:
- A
- 摘要:
- 针对目前油气管道的预警与泄漏判断误报率和漏报率高的问题，采用一种基于多传感器信息融合的方法来进行诊断.考虑不同的传感器所测得的特征参数不同的特点，在数据融合的过程中采用加权融合，增加系统判断的准确性.实验结果证明了该方法的有效性.
- Abstract:
- At present, there are high misinformation rates and missing report rates in leakage testing and warning systems for oil and gas pipelines. Thus, a method using multisensor information fusion to conduct diagnosis was proposed in this paper. In the process of information fusion, we took advantage of weighted fusion to increase the accuracy of system judgment, since the characteristic parameters of different sensors were distinct. Experimental results showed the effectiveness of the method.
- 参考文献/References:
-
［1］NIU Gang, WIDODO A, SON J D, et al. Decisionlevel fusion based on wavelet decomposition for induction motor fault diagnosis using transient current signal ［J］. Expert Systems with Applications, 2008，35(3): 918-928.
［2］BASIR O, YUAN Xiaohong. Engine fault diagnosis based on multisensor information fusion using DempsterShafer evidence theory ［J］. Information Fusion, 2007,8(4): 379-386.
［3］FAN Xianfeng, ZUO M J. Fault diagnosis of machines based on D-S evidence theory. Part 1: D-S evidence theory and its improvement ［J］. Pattern Recognition Letters, 2006, 27(5): 366-376.
［4］谭 青, 向阳辉. 加权证据理论信息融合方法在故障诊断中的应用［J］. 振动与冲击, 2008, 27(4): 112-116.
TAN Qing, XIANG Yanghui.Application of weighted evidential theory and its information fusion method in fault diagnosis［J］. Journal of Vibration and Shock, 2008,27(4):112-116.
［5］胡晓明, 岳小云. 基于证据理论数据融合的故障诊断研究［J］. 流体传动与控制, 2008, 26(1)：12-14.
HU Xiaoming, YUE Xiaoyun. Study on data fusion fault diagnosis based on evidential theory［J］. Fluid Power Trans〖LL〗mission and Control，2008, 26(1)：12-14.
［6］黄志彦, 张柏书, 于开山，等. D-S证据理论据融合算法在某系统故障诊断中的应用［J］. 电光与控制, 2007, 14(2): 146-149.
HUANG Zhiyan, ZHANG Baishu, YU Kaishan, et al. Application of DS evidence theory data fusion algorithm in fault diagnosis of a certain system［J］. Electronics Optics and Control, 2007, 14(2)：146-149.
［7］SHAFER G. A mathematical theory of evidence ［M］. Princeton, USA: Princeton University Press, 1976.
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备注/Memo
收稿日期：2008-11-07.
基金项目：国家自然科学基金资助项目（60534010，60572070，60521003，60774093）.
作者简介：
马大中，男，1982年生，博士研究生，主要研究方向为神经网络、故障诊断和鲁棒控制.
张化光，男，1959年生，教授，博士生导师，主要研究方向为神经网络的动态特性、近似动态规划、网络控制和模糊控制等.获得十余项国家科技发明专利，分别获国家电子信息科技进步一等奖、辽宁省科技进步一等奖、国家能源部科技进步二等奖、国家教委(甲类)科技进步二等奖、辽宁省科技发明二等奖等.发表的学术论文被SCI收录54篇, EI收录186篇, ISTP收录51篇.
冯 健，男，1971年生， 教授，主要研究方向为故障诊断、信号处理、电力系统自动化、电能质量分析、模糊控制理论、神经网络、数据挖掘、智能控制及智能系统在工业中的应用等.发表学术论文20余篇，其中被SCI收录3篇，EI收录21篇。
更新日期/Last Update:
2009-03-24