神经网络技术在破碎机故障诊断中的应用  

APPLICATIONS OF NEURAL NETWORK IN CRUSHER FAULT DIAGNOSIS SYSTEM

作　　者：孙璐[1] 唐广群[2] 张德政[3] 

机构地区：[1]中国地质大学,北京100083 [2]中国有色工程设计研究总院,北京100038 [3]北京科技大学,北京100083

出　　处：《矿冶》2007年第3期85-90,68,共7页Mining And Metallurgy

摘　　要：设备维修费用在冶金矿山生产成本中占有相当的比例。因此迫切需要利用信息技术提高生产和管理的自动化、智能化、数字化、网络化水平,降低单位生产总值的能耗和物耗。本文以破碎机的故障诊断为研究内容,在对国内外研究现状进行深入分析的基础上,给出一种基于神经网络的信息融合的故障诊断方法并进行实际检验。实践证明,这种诊断方法可以显著提高故障诊断的精确程度,减少设备故障的发生。The equipment maintenance cost holds the considerable ratio in the cost of metallurgy production. Therefore it＇s urgent to improve the automation, the intellectualization, the digitization and the network level and reduce output cost by utilizing information technology. This article is mainly about this equipment fault di- agnostic method. Based on analyzing the currently domestic and foreign study, it gives a new diagnostic method by neural net inference. Through practice, this kind of diagnosis method is proved to raise diagnostic precision apparently and reduce the probability of equipment fault occurrence.

关 键 词：神经网络 破碎机 故障诊断 信息融合 

分 类 号：TD451[矿业工程—矿山机电] TP399[自动化与计算机技术—计算机应用技术]