基于半监督聚元自组织映射的齿轮早期故障检测

自组织特征映射应用于齿轮早期故障检测时,常常导致训练时间长、检测精度低、故障分类结果不直观等问题.提出了基于LDA(线性判别分析)与半监督聚元自组织映射的故障检测方法,首先利用LDA对故障特征集进行降维处理,然后再利用半监督聚元自组织网络对降维后的特征子集进行分类并将结果可视化,Iris数据集的仿真结果验证了该方法的有...

Gear Incipient Fault Diagnosis based on Semi-supervised Grouping Neuron Self-organized Map

Self-organizing feature map is often limited by long training time,low diagnosis accuracy and bad classification visualization when it is applied in gear fault diagnosis.A novel method of semi-supervised LDA-GNSOM(Linear Discriminative Analysis Grouping Neuron Self-organized Map) is proposed for fault diagnosis.Firstly,the fault of original feature space is reduced by using LDA,and then the reduced feature subsets are input into the semi-supervised GNSOM network for classification and visualization.The effe...