粒子群优化模糊聚类算法在煤气鼓风机组振动故障诊断的应用
DOI:
作者:
作者单位:

作者简介:

通讯作者:

基金项目:


Application of PSO Fuzzy Clustering Algorithm to Fault Diagnosis of Gas Blower Group Vibration
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    针对模糊C均值聚类算法容易陷入局部极值和对初始值敏感的缺点,提出了一种粒子群优化模糊聚类算法,该算法利用粒子群优化算法寻找最优聚类中心,运用WFCM进行加权模糊聚类,能较大提高聚类的有效性;将该算法应用于煤气鼓风机组振动故障诊断中进行诊断仿真,结果表明:该算法较大提高了故障诊断的正确率。

    Abstract:

    According to the fault that fuzzy C-means clustering algorithm is easily involved in loal extreme and is sensitive to initial value,a kind of PSO fuzzy clustering algorighm is proposed,this algorithm searches the optimal clustering center based on PSO algorithm,uses WFCW to conduct weighted fuzzy cluster and is able to relatively more largely improve the validity of the cluster.This algorithm is used in diagnosis simulation in the fault diagosis of gas blower group vibation and the results show that this algorithm can relatively more largely improve the accurate rate of fault diagnosis.

    参考文献
    相似文献
    引证文献
引用本文

赵 欣.粒子群优化模糊聚类算法在煤气鼓风机组振动故障诊断的应用[J].重庆工商大学学报(自然科学版),2013,30(2):37-41
ZHAO Xin. Application of PSO Fuzzy Clustering Algorithm to Fault Diagnosis of Gas Blower Group Vibration[J]. Journal of Chongqing Technology and Business University(Natural Science Edition),2013,30(2):37-41

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期:
×
2023年《重庆工商大学学报(自然科学版)》影响因子稳步提升