基于RBF神经网络的连续采煤机故障诊断研究  

Study on Fault Diagnosis of Continuous Winning Machine Based on RBF Neutral Network

作　　者：罗芳琼[1] 

机构地区：[1]柳州师范高等专科学校,广西柳州54500

出　　处：《煤矿机械》2013年第5期297-299,共3页Coal Mine Machinery

基　　金：广西教育科研基金(201204LX506);柳州师范高等专科学校科研基金(LSZ2011B007)

摘　　要：为了能够提高连续采煤机故障诊断的效率和精度,深入地研究了基于改进遗传算法的RBF神经网络在其中的应用。分析了连续采煤机的主要故障类型;分别研究了RBF神经网络的基本原理和改进遗传算法的基本原理;进行了连续采煤机故障诊断的实例分析,仿真结果验证了该故障诊断技术的有效性。In order to improve efficiency and precision of fault diagnosis for continuous winning machine and application of the RBF neutral network based on improved genetic algorithm on it is studied in depth. The main fault types of continuous winning machine are analyzed, the basic theory of the RBF neutral network and improved genetic algorithm are studied respectively, the case study of fault diagnosis for continuous winning machine is carried out, and simulation results verify effectiveness of this technology.

关 键 词：RBF神经网络 连续采煤机 故障诊断 

分 类 号：TD421.6[矿业工程—矿山机电]