[1]杜晓敏,王立德,李召召,等.基于波形特征提取和 FA-Grid SVM 的MVB 故障诊断[J].机车电传动,2020,(02):71-74.[doi:10.13890/j.issn.1000-128x.2020.02.015]
 DU Xiaomin,WANG Lide,LI Zhaozhao,et al.MVB Fault Diagnosis Based on Waveform Feature Extraction and FA-Grid SVM[J].Electric Drive for Locomotives,2020,(02):71-74.[doi:10.13890/j.issn.1000-128x.2020.02.015]
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基于波形特征提取和 FA-Grid SVM 的MVB 故障诊断()
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机车电传动[ISSN:1000-128X/CN:43-1125/U]

卷:
期数:
2020年02期
页码:
71-74
栏目:
研究开发
出版日期:
2020-03-10

文章信息/Info

Title:
MVB Fault Diagnosis Based on Waveform Feature Extraction and FA-Grid SVM
文章编号:
1000-128X(2020)02-0071-04
作者:
杜晓敏王立德李召召宋 辉
(北京交通大学 电气工程学院,北京 100044)
Author(s):
DU Xiaomin WANG Lide LI Zhaozhao SONG Hui
( School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China )
关键词:
MVB 网络故障诊断波形特征提取FA-Grid SVM列车通信
Keywords:
MVB network fault diagnosis waveform feature extraction FA-Grid SVM train communication
分类号:
U266.2;TP393
DOI:
10.13890/j.issn.1000-128x.2020.02.015
文献标志码:
A
摘要:
列车通信网络的故障诊断一直是列车健康管理的难点,文章针对列车 MVB(多功能车辆总线)网络,提出了一种基于波形特征提取和联合萤火虫网格寻优支持向量机 (FA-Grid Support Vector Machines, FA-Grid SVM) 相结合的故障诊断方法。通过提取 MVB 总线物理波形的时域特征,作为支持向量机的样本,构建 MVB故障数据集;基于 SVM 较优参数点基本集中于同一区域这一现象,提出 FA-Grid 两步寻优的参数优化模型。试验结果表明,与传统网格寻优和遗传算法(GA)相比
Abstract:
The fault diagnosis of train communication network has always been achallenge in train health management. A fault diagnosis method based on waveform feature extraction and FA-Grid SVM for multi-function vehicle bus(MVB) was proposed. The time-domain features were extracted from physical waveform of the MVB bus and used as inputs of SVM which construct MVB fault dataset. Due to the concentration of optimal parameters of SVM, a two-step parameter optimization method based on FA-Grid was provided. Experimental results show that compared with traditional grid optimization and genetic algorithm (GA), the proposed FA Grid optimization model has lower complexity and higher efficiency and could accurately diagnose MVB faults.

参考文献/References:

[1] 聂晓波 , 王立德 , 申萍 . 轨道车辆 MVB 网络实时性能分析与优化研究 [J]. 铁道学报 , 2011, 33(9): 40-44.?

[2] 季高 , 张峰 , 张士文 . 基于多功能车辆总线的地铁车辆远程监测系统研究 [J]. 城市轨道交通研究 , 2019, 22(6): 99-103.
[3] 李召召 , 王立德 , 岳川 , 等 . 基于 MKLSVM 的 MVB 端接故障诊断 [J]. 北京交通大学学报 , 2019, 43(2): 100-106.
[4] LEI Y, XIE H B, YUAN Y,et al. Fault location for the intermittent connection problems on CAN networks[J]. IEEE transactions on Industrial Electronics, 2015, 62(11): 7203-7213.
[5] 郝建新 , 贾春宇 . 基于 SVM 与改进 D-S 理论电路板故障诊断算法 [J]. 现代电子技术 , 2019, 42(22): 15-20.
[6] 张文雅 , 雨强 , 韩华 , 等 . 基于交叉验证网格寻优支持向量机的产品销售预测 [J]. 计算机系统应用 , 2019, 28(5): 1-9.
[7] YANG S X . Firefly algorithm, stochastic test functions and design optimisation[J]. International Journal of Bio-Inspired Computation, 2010, 2(2): 78-84.
[8] 王奉涛 , 刘晓飞 , 敦泊森 , 等 . 基于萤火虫优化的核自动编码器在中介轴承故障诊断中的应用 [J]. 机械工程学报 , 2019, 55(7): 58-64.
[9] 田梦楚 , 薄煜明 , 陈志敏 , 等 . 萤火虫算法智能优化粒子滤波 [J].自动化学报 , 2016, 42(1): 89-97.
[10] 何大伟 , 彭靖波 , 胡金海 , 等 . 基于改进 FOA 优化的 CS-SVM轴承故障诊断研究 [J]. 振动与冲击 , 2018, 37(18): 108-114.
[11] 时培明 , 梁凯 , 赵娜 , 等 . 基于分形维数和 GA-SVM 的风电机组齿轮箱轴承故障诊断 [J]. 计量学报 , 2018, 39(1): 61-65.

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备注/Memo

备注/Memo:
作者简介:杜晓敏(1995—)女,硕士研究生,研究方向为列车通信网络故障诊断。
更新日期/Last Update: 2020-03-10