SOM神经网络在全液压钻机液压系统故障诊断中的应用  

Application of SOM Neural Network in Fault Diagnosis for Hydraulic System of Hydraulic Drilling Rig

作　　者：贺康[1] 庞海荣[1] 代粉蕾[1] 

机构地区：[1]煤炭科学研究总院西安研究院,西安710054

出　　处：《煤矿机械》2011年第4期249-250,共2页Coal Mine Machinery

摘　　要：利用神经网络的非线性映射及其高度的自组织和自学习能力,将SOM网络应用于钻机液压系统的故障诊断。根据钻机液压系统故障的特点,选取能够表征全液压钻机故障特点的样本,设计相应的SOM神经网络,并在MATLAB环境下实现了对网络的训练和仿真实验,表明该方法有很强的实用性,为全液压钻机的故障诊断提供了一种途径。SOM network is applied to the fault diagnosis of hydraulic drilling rig by using nonlinear mapping of neural network and its ability of self-organization and self-learning. According to the characteristics of hydraulic system of drilling rig, take fault sample that can be characterize the hydraulic characteristics of drilling rig, building the SOM neural network corresponding sample, and training and simulation experiment in the MATLAB environment. Results show that the method is effective on the fault diagnosis of hydraulic drill rig.

关 键 词：SOM神经网络 故障诊断 全液压钻机 

分 类 号：TD421.2[矿业工程—矿山机电] TP183[自动化与计算机技术—控制理论与控制工程]