新息灰理论在不确定性系统故障预测中的应用  

Application of Innovation Grey Theory to Fault Predication of Uncertainty Systems

作　　者：董立立[1] 魏鑫 黄道[3] 顾幸生[3] 梁林泉[1] 

机构地区：[1]解放军军械工程学院基础部,石家庄050003 [2]焦作市第一建筑公司工程技术中心,焦作454152 [3]华东理工大学工业自动化国家工程研究中心,上海200237

出　　处：《华东理工大学学报（自然科学版）》2006年第12期1482-1486,共5页Journal of East China University of Science and Technology

基　　金：上海市科委重大科技攻关项目(04dz11008)

摘　　要：结构复杂性、运行环境独特性和诱发故障多源性大大增加了现代设备系统的不确定性,从而导致能够反映设备系统主要特征的数据较少。针对不确定性设备系统贫信息的特点,将新息灰预测方法应用于设备系统运行状态的预测。仿真研究给出了基于新息灰理论的工业实例建模过程和故障预测结果,并与BP神经网络方法的计算结果进行比较,验证了新息灰预测方法的有效性与实用性。Structural complexity, uniqueness of operating environments and multi-source of the failure greatly increase the uncertainties of modern equipment system. These uncertainties further result in the less data, which reflect main dynamic characteristic of system. Innovation Grey Prediction Model （IGPM） can get better model by updating data in time. For poor information of uncertainty equipment systems, IGPM is applied to prediction of equipment operation. The modeling procedure of emulation based on FIGPM is presented, and the prediction result is compared with BP neural networks. It is proved that IGPM has good practicability and validity.

关 键 词：不确定性系统 新息 灰预测 状态预测 

分 类 号：TQ050.7[化学工程]