基于改进人工鱼群算法的机械故障聚类诊断方法

PDF(976 KB)

振动与冲击 ›› 2012, Vol. 31 ›› Issue (17) : 145-148.

论文

基于改进人工鱼群算法的机械故障聚类诊断方法

陈安华周博张会福文宏

作者信息 +

A method of Clustering in Mechanical Fault diagnosis based on improved Fish-swarm Algorithm

CHEN An-hua ZHOU Bo ZHANG Hui-fu WEN Hong

Author information +

文章历史 +

摘要

发展新的理论或方法快速准确地实现机械故障信号的聚类诊断是众多学者研究热点。由于人工鱼群优化算法具有结构简单，良好的并行性、快速性等特点，把人工鱼群优化算法引入机械故障诊断中。基于人工鱼群算法的基本原理提出了一种改进的人工鱼群追尾聚类算法，定义了相似度因子和聚类判别因子，建立了模拟人工鱼群追尾行为的机械故障聚类诊断模型，并将之应用于机械故障特征信息的聚类分析。实例分析表明了本文方法的有效性。

Abstract

The development of new theories or methods to solve mechanical fault diagnosis is a hot topic to many scholars. Fish-swarm Algorithm is used to the mechanical fault diagnosis because of its simple structure, good parallel and rapid computations. This paper presents an improved fish-swarm rear-end clustering algorithm based on the principle of artificial fish swarm algorithm. The model of fault diagnosis based on Fish-swarm algorithm is funded, and the similarity factor and discriminant factor is also definited .It is used to the analysis of the clustering of mechanical fault diagnosis. The result of an example shows that this method is effective.

导出引用

陈安华周博张会福文宏. 基于改进人工鱼群算法的机械故障聚类诊断方法[J]. 振动与冲击, 2012, 31(17): 145-148

CHEN An-hua ZHOU Bo ZHANG Hui-fu WEN Hong. A method of Clustering in Mechanical Fault diagnosis based on improved Fish-swarm Algorithm [J]. Journal of Vibration and Shock, 2012, 31(17): 145-148