Paper Title:
Mode Identification Based on Fuzzy Clustering and Grey System Theory and its Applichation
  Abstract

The helath condition of rotor has been greatly concerned in rotating machinery. But for the lack of information, it is very difficult to judge the actual conditon. Based on the fuzzy and grey characteristics between faults and symptoms, a new method integrated with fuzzy clustering and grey relation analysis was put forward to identify the condition of rotor system. Firstly, eight features, such as average value, peak-peak value, variance value, virtual value and etc., were extracted from the vibration signal of rotor system. Then, fuzzy C-means algorithm was used to cluster forty samples into 4 clusters, meanwhile, the clustering center was acquired and regarded as standard pattern matrix. Finally, the grey relation degree was calculated between pattern to be inspected and the standard pattern matrix. Using this method, the unbalanced conditions of rotor system was precisely identified, which shows that the integrated method is valid and practicable.

  Info
Periodical
Advanced Materials Research (Volumes 171-172)
Edited by
Zhihua Xu, Gang Shen and Sally Lin
Pages
144-149
DOI
10.4028/www.scientific.net/AMR.171-172.144
Citation
L. X. Duan, L. B. Zhang, Y. Meng, "Mode Identification Based on Fuzzy Clustering and Grey System Theory and its Applichation", Advanced Materials Research, Vols. 171-172, pp. 144-149, 2011
Online since
December 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Pan Fu, Wei Lin Li, Wei Qing Cao
Abstract:As one of the most common parts of various rolling mechanical equipments, rolling element bearing is vulnerable. Therefore, great attentions...
510
Authors: Su Qun Cao, Xiao Ming Zuo, Ai Xiang Tao, Jun Min Wang, Xiang Zhi Chen
Chapter 3: Manufacturing Engineering
Abstract:In recent years, machine learning techniques have been widely used in intelligent fault diagnosis field. As a major unsupervised learning...
1628
Authors: Ke Li, Peng Chen, Hao Sun
Chapter 10: Sound, Noise and Vibration Control
Abstract:This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and...
3814
Authors: Xiao Hong Chen, Hui Xu, Sheng Jian Xie, Hong Wu Zhao
Chapter 1: Engineering Science for Manufacturing
Abstract:In actual production, able to predict that their products performance can meet the requirements of the national standard, whether or not to...
27
Authors: Yang Pan, An Hua Chen, Ling Li Jiang
Chapter 3: Mechanical Transmission, Vibration and Noise
Abstract:According to the selection difficulties of initial clustering center of k-means clustering algorithm, this paper proposes a method that is to...
250