Title :
Online diagnosis of brick interior fault based on dynamic fuzzy cluster analysis
Author :
Qiao, Zhihua ; Yang, Ming ; Wang, Zijuan
Author_Institution :
Autom. Coll., Shenyang Aerosp. Univ., Shenyang, China
Abstract :
A method to online detect and diagnose brick interior different types of faults was proposed based on striking sound. Applied spectrum analysis to striking sound signals of bricks, picked out characteristic frequencies of every spectrum to form a data matrix, then applied fuzzy cluster analysis to get classification, next computed corresponding average similarity to every cluster, judged bricks fault type by comparing them when online detection. Experiment results show that the method is effective.
Keywords :
brick industry; fault diagnosis; fuzzy set theory; pattern clustering; spectral analysis; data matrix; dynamic fuzzy cluster analysis; online brick interior fault diagnosis; spectrum analysis; striking sound signals; average similarity; brick interior defect; characteristic frequency; fuzzy clustering; online detection; spectrum;
Conference_Titel :
Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6944-4
DOI :
10.1109/CCTAE.2010.5544601
