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基于灰色理论的机械设备智能状态预测
引用本文:董振兴,史定国,张东山,杨汝清.基于灰色理论的机械设备智能状态预测[J].华东理工大学学报(自然科学版),2001,27(4):392-394.
作者姓名:董振兴  史定国  张东山  杨汝清
作者单位:1. 上海交通大学机器人研究所
2. 华东理工大学化工机械研究所
摘    要:提出了基于灰色理论并与神经网络有机结合的机械设备智能状态预测方法,着眼于机械设备“内在”规律的研究,根据机械设备自身历史数据建立动态微分方程,并预测自身的发展,具有数据量小,计算简单、预测准确的特点,该方法已在实际工程中应用,结果表明方法是行之有效的。

关 键 词:灰色理论  状态预测  故障诊断  神经网络  机械设备  灰色预测模型
文章编号:1006-3080(2001)04-0392-03
修稿时间:2000年9月7日

Intelligent Condition Prediction of Mechanical Equipment Based on the Gray-theory
DONG Zhen xing ,SHI Ding guo ,ZHANG Dong shan ,YANG Ru qing.Intelligent Condition Prediction of Mechanical Equipment Based on the Gray-theory[J].Journal of East China University of Science and Technology,2001,27(4):392-394.
Authors:DONG Zhen xing  SHI Ding guo  ZHANG Dong shan  YANG Ru qing
Institution:DONG Zhen xing 1*,SHI Ding guo 2,ZHANG Dong shan 2,YANG Ru qing 1
Abstract:Based on the gray theory, a novel prediction method of intelligent condition to detect the performance of mechanical equipment, was proposed in this paper, which combined the gray predictive model GM(1,1) and neural networks intimately and organically. With a view to investigate the inherent law of mechanical equipment and according to the own historical data of mechanical equipment, a dynamic different equation is established to predict its own trend. The characters of the gray predictive model GM(1,1) are simple calculation and accurate prediction with smaller amount of data. This method has been applied to a condition monitoring and fault diagnosis system. The industry application shows this method is useful and effective.
Keywords:gray theory  condition prediction  fault diagnosis  neural networks  
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