| 基于SOM网络可视化技术的液压系统故障分类研究 |
| |
| 引用本文： | 王楠,谷立臣.基于SOM网络可视化技术的液压系统故障分类研究[J].流体传动与控制,2009(3):5-9. |
| |
| 作者姓名： | 王楠 谷立臣 |
| |
| 作者单位： | 西安建筑科技大学机械电子技术研究所,陕西西安,710055 |
| |
| 基金项目： | 国家自然科学基金，陕西省工业攻关项目 |
| |
| 摘 要： | 针对SOM网络（自组织特征映射神经网络）可视化方法简单、直观的特点，文中将其应用到液压系统的故障分类中。以电流信号的频域能量作为特征参数，用db2共轭正交滤波器组对所获数据进行小波包分解，提取系统在正常及故障运行状态下的特征向量，作为训练样本，然后利用U矩阵图和D矩阵图等可视化T具对分类结果进行仿真与分析，并与一般结果进行比较。结论表明，该方法可行且对故障的判别率高。
|
| 关 键 词： | 液压动力系统 故障分类 SOM神经网络 可视化 |
Research on Fault Classification for Hydraulic Power System Based on Visual Analysis of SOM Network |
| |
| WANG Nan,GU Li-chen.Research on Fault Classification for Hydraulic Power System Based on Visual Analysis of SOM Network[J].Fluid Power Transmission & Control,2009(3):5-9. |
| |
| Authors: | WANG Nan GU Li-chen |
| |
| Affiliation: | WANG Nan ,GU Li-chen |
| |
| Abstract: | SOM network(self-organizing feature map neural network) visual method which is simple,intuitionistic used for hydraulic power system fault classification in this paper.The parameters gained with frequency domain energy of signals,the data obtained is decomposed used wavelet packet(Db2 conjugate orthogonal filter bank) and the feature vector is extracted in normal and fault operating state of system.Then use the U matrix map and D matrix map as visual tools to simulate and analyse the classification results.... |
| |
| Keywords: | self-organizing feature map neural network visualization hydraulic power system fault classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
