面向高维特征故障数据的进化软子空间聚类算法

夏虎; 庄健; 于德弘

doi:10.7652/xjtuxb201305021

您当前的位置：

首页 >

文章列表页 >

面向高维特征故障数据的进化软子空间聚类算法

更新时间：2025-07-09

- 面向高维特征故障数据的进化软子空间聚类算法
- Evolutionary Soft Subspace Clustering Method for Fault Diagnosis of High-Dimensional Features
- 西安交通大学学报 2013年47卷第5期页码：115-120
- 作者机构：
  
  西安交通大学机械工程学院,西安,710049
- 作者简介：
- 基金信息：
  
  : 2012-11-09。作者简介: 夏虎(1986—),男,博士生;庄健(通信作者),男,副教授。基金项目: 中央高校基本科研业务费专项资金资助项目(XJJ20100142);广东省战略性新兴产业核心技术攻关项目(2011A091101004);陕西省科技厅工业攻关项目(2011K09-45)
- DOI：10.7652/xjtuxb201305021
  中图分类号： TP391.41
- 网络首发：2013-05-10，
  
  纸质出版：2013
- 稿件说明：
移动端阅览
夏虎, 庄健, 于德弘. 面向高维特征故障数据的进化软子空间聚类算法[J]. 西安交通大学学报, 2013,47(5):115-120.

Evolutionary Soft Subspace Clustering Method for Fault Diagnosis of High-Dimensional Features[J]. 2013, 47(5): 115-120.
夏虎, 庄健, 于德弘. 面向高维特征故障数据的进化软子空间聚类算法[J]. 西安交通大学学报, 2013,47(5):115-120. DOI： 10.7652/xjtuxb201305021.

Evolutionary Soft Subspace Clustering Method for Fault Diagnosis of High-Dimensional Features[J]. 2013, 47(5): 115-120. DOI： 10.7652/xjtuxb201305021.

摘要

针对复杂机械设备故障诊断中特征量众多且对各种故障敏感程度不同的现象

提出了采用软子空间聚类算法来实现故障的识别方法。同时

针对传统软子空间聚类易陷入局部最优

目标函数设计受限制的缺点

又提出了采用进化计算实现聚类的方法。利用同类样本在相关特征维上方差小的假设

新的目标函数能更好地评价聚类结果的质量。在该算法中

通过设计类中心和权重值的混合编码以及聚类导向搜索算子

使算法更适于聚类问题的优化

而且设计的修复算子可有效地去除不合理的聚类结果。采用5组UCI数据集、2组轴承滚珠故障数据集和3组往复式压缩机气阀故障数据集对算法进行了测试

结果表明:该算法明显好于几种的软子空间聚类算法

在Rand指标上最多可高出0.226 6

并且对2组不同工况下一级缸气阀故障可实现100%的故障识别。

Abstract

Many features can be collected in a complex machine

however

using all these features for fault diagnosis is inappropriate due to different sensitivity of each feature. A soft subspace clustering schedule is proposed. A novel evolutionary algorithm is suggested to avoid the shortages in the traditional soft subspace clustering

such as local optimum and constraint in designing objective function. Under the hypothesis that the samples in the same cluster have small variance in relevant dimensions

a new objective function is constructed in the proposed algorithm to optimize. Considering the special meaning of each gene

a new encoding frame and a cluster-oriented search operator are designed. A repair operator enables to eliminate some meaningless individuals in the evolution process. The experiments on five UCI

two bearing fault and three valve fault of reciprocating compressor datasets demonstrate the better performance of the new algorithm. It is at most 0.226 6 higher than other competitive soft subspace clustering methods on Rand index(RI)

especially for two of the valves

fault diagnosis rate gets 100%.

关键词

Keywords

references

张周锁, 侯照文, 孙闯, 等. 应用粒计算的混合智能故障诊断技术研究 [J]. 西安交通大学学报, 2011, 45(1): 48-53.

ZHANG Zhousuo, HOU Zhaowen, SUN Chuang, et al. Hybrid intelligent diagnosis technology based on granular computing [J]. Journal of Xi'an Jiaotong University, 2011, 45(1): 48-53.

LEI Yaguo, HE Zhengjia, ZI Yanyang, et al. New clustering algorithm-based fault diagnosis using compensation distance evaluation technique [J]. Mechanical Systems and Signal Processing, 2008, 22(2): 419-435.

LEI Yaguo, HE Zhengjia, ZI Yanyang, et al. Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs [J]. Mechanical Systems and Signal Processing, 2007, 21(5): 2280-2294.

张云, 冯博琴, 麻首强, 等. 蚁群-遗传融合的文本聚类算法 [J]. 西安交通大学学报, 2007, 41(10): 1146-1150.

ZHANG Yun, FENG Boqin, MA Shouqiang, et al. Text clustering based on fusion of ant colony and genetic algorithms [J]. Journal of Xi'an Jiaotong University, 2007, 41(10): 1146-1150.

董红斌, 杨宝迪, 刘佳媛, 等. 协同演化算法在聚类中的应用 [J]. 模式识别与人工智能, 2012, 25(4): 676-683.

DONG Hongbin, YANG Baodi, LIU Jiayuan, et al. A co-evolutionary algorithm for clustering [J]. Pattern Recognition and Artificial Intelligence, 2012, 25(4): 676-683.

WU Qi, LAW R, WU Shuyan. Fault diagnosis of car assembly line based on fuzzy wavelet kernel support vector classifier machine and modified genetic algorithm [J]. Expert Systems with Applications, 2011, 38(8): 9096-9014.

ZHU Lin, CAO Longbing, YANG Jie. Multiobjective evolutionary algorithm-based soft subspace clustering [C]∥Proceedings of the 2012 IEEE Congress on Evolutionary Computation. Piscataway, NJ, USA: IEEE, 2012:1-8.

GAN Gaojun, WU Jianhong, YANG Zijiang. A fuzzy subspace algorithm for clustering high dimensional data [C]∥Proceedings of the 2nd International Conference on Advanced Data Mining and Applications. Berlin, Germany: Springer-Verlag, 2006: 271-278.

JING Liping, NG M K, HUANG J Z. An entropy weighting k-means algorithm for subspace clustering of high-dimensional sparse data [J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(8): 1026-1041.

DENG Zhaohong, CHOI K S, CHUNG F L, et al. Enhanced soft subspace clustering integrating within-cluster and between-cluster information [J]. Pattern Recognition, 2012, 43(3): 767-781.

王跃飞,张振涛,张波,等.利用声发射的往复空压机环状阀泄漏故障诊断试验.2012,46(9):26-30.

陈景龙,訾艳阳,何正嘉,等.自适应冗余多小波及其在故障诊断中的应用.2012,46(7):44-49.

徐宇亮,孙际哲,陈西宏,等.采用多目标粒子群算法的模拟电路故障诊断研究.2012,46(6):92-97.

栗茂林,梁霖,王孙安,等.结合交叠区异点统计和相关分析的免疫克隆特征选择方法.2012,46(5):50-56.

薛士明,曹军义,林京,等.分数阶阻尼裂纹转子的非线性动力学特性分析.2012,46(1):76-80.

杨攀,桂小林,田丰,等.一种高效的用于话题检测的关键词元聚类方法.2012,46(10):24-28.

邵必林,边根庆,张维琪,等.采用k-means algorithm for subspace clustering of high-dimensional sparse data [J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(8): 1026-1041.

DENG Zhaohong, CHOI K S, CHUNG F L, et al. Enhanced soft subspace clustering integrating within-cluster and between-cluster information [J]. Pattern Recognition, 2012, 43(3): 767-781.

王跃飞,张振涛,张波,等.利用声发射的往复空压机环状阀泄漏故障诊断试验.2012,46(9):26-30.

陈景龙,訾艳阳,何正嘉,等.自适应冗余多小波及其在故障诊断中的应用.2012,46(7):44-49.

徐宇亮,孙际哲,陈西宏,等.采用多目标粒子群算法的模拟电路故障诊断研究.2012,46(6):92-97.

栗茂林,梁霖,王孙安,等.结合交叠区异点统计和相关分析的免疫克隆特征选择方法.2012,46(5):50-56.

薛士明,曹军义,林京,等.分数阶阻尼裂纹转子的非线性动力学特性分析.2012,46(1):76-80.

杨攀,桂小林,田丰,等.一种高效的用于话题检测的关键词元聚类方法.2012,46(10):24-28.

邵必林,边根庆,张维琪,等.采用聚类算法的资源搜索模型研究.2012,46(10):55-59.

杨清宇,孙凤伟,张曌,等.利用测地线距离的改进谱聚类算法.2012,46(8):1-7.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

电力变压器故障诊断多智能体大模型构建与应用

采用双小波字典的齿轮箱复合故障特征提取方法

一维卷积神经网络在机械故障特征提取中的可解释性研究

蜉蝣优化双通道网络在齿轮箱故障诊断中的应用

一种双阻尼小波赋能的可解释卷积神经网络在轴承故障诊断中的应用