计算机与现代化

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基于HHT变换和FOA_LSSVM的电缆故障诊断

  

  1. 毕节供电局,贵州  毕节  551700
  • 收稿日期:2016-12-28 出版日期:2017-09-20 发布日期:2017-09-19
  • 作者简介:苏立(1987-),男,陕西蒲城人,毕节供电局工程师,本科,研究方向:信息技术,电力工程。

Cable Fault Diagnosis Based on HHT Transform and FOA_LSSVM

  1. Bijie Power Supply Bureau, Bijie 551700, China
  • Received:2016-12-28 Online:2017-09-20 Published:2017-09-19

摘要: 针对现有的地下电缆故障诊断方法存在准确率不高、误差较大的缺点,提出一种基于HHT变换和FOA_LSSVM的地下电缆故障诊断方法。针对地下电缆故障信号,通过HHT变换提取地下电缆故障信号的特征分量,将提取的特征分量和地下电缆故障类型作为FOA_LSSVM的输入和输出,实现地下电缆故障类型的识别。以150组地下电缆故障数据为实验对象,结果表明,FOA_LSSVM比GA_LSSVM,PSO_LSSVM和DE_LSSVM具有更高的准确率,更适合地下电缆故障的诊断和识别。

关键词: 果蝇优化算法, 最小二乘支持向量机, 电缆故障, HHT变换

Abstract: In view of the shortcomings of the existing methods of fault diagnosis for underground cables with low accuracy and large error, a method of cable fault diagnosis based on HHT transform and FOA_LSSVM is proposed. According to the underground cable fault signal, through the HHT transform to extract the feature component of underground cable fault signals, the characteristic components and underground cable fault types were extracted as the input and output of FOA_LSSVM, to identify the fault types of underground cables. Taking 150 sets of underground cable fault data as the test object, the experimental results show that FOA_LSSVM has higher accuracy than GA_LSSVM, PSO_LSSVM and DE_LSSVM, and is more suitable for the diagnosis and identification of underground cable fault.

Key words: fruit fly optimization algorithm, least square support vector machine, cable fault, HHT transform

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