DocumentCode :
1850502
Title :
Application of Self Organizing Map for Intelligent Machine Fault Diagnostics Based on Infrared Thermography Images
Author :
Widodo, Achmad ; Satrijo, Djoeli ; Huda, Muhammad ; Lim, Gang-Min ; Yang, Bo-Suk
Author_Institution :
Dept. of Mech. Eng., Diponegoro Univ., Semarang, Indonesia
fYear :
2011
fDate :
27-29 Sept. 2011
Firstpage :
123
Lastpage :
128
Abstract :
This paper concerns with implementation of self organizing map (SOM) for intelligent machine fault diagnostics. The present study employs infrared images acquired by thermography camera as data base of machine diagnostics system. Image processing is carried out using thresholding for image segmentation and clustering by means of k-means algorithm. Feature extraction of images is conducted by calculating area, perimeter and central moment of region of interest (ROI). All data of this work was acquired by capturing the images of rolling element bearings from rotating machine fault simulator (MFS). The simulator is able to experiment a normal and seeded fault conditions such as outer and inner race defects of rolling element bearing, unbalance, misalignment and looseness. Pattern recognition technique is then employed to diagnose the machine conditions by mapping the image features through SOM. The result shows that SOM based infrared thermography image can perform intelligent machine fault diagnostics with plausible accuracy.
Keywords :
cameras; condition monitoring; fault diagnosis; image recognition; image segmentation; infrared imaging; pattern clustering; rolling bearings; self-organising feature maps; image feature mapping; image segmentation; image thresholding; infrared thermography images; intelligent machine fault diagnostics system; k-means clustering algorithm; machine condition diagnosis; pattern recognition technique; self organizing map; thermography camera; Cameras; Clustering algorithms; Condition monitoring; Data acquisition; Feature extraction; Neurons; Rolling bearings; infrared thermography; machine fault diagnostics; pattern recognition; self organizing map;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2011 Sixth International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4577-1092-6
Type :
conf
DOI :
10.1109/BIC-TA.2011.15
Filename :
6046884
Link To Document :
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