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ASME Press Select Proceedings

International Conference on Mechanical Engineering and Technology (ICMET-London 2011)

Editor
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859896
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011

The structure of Printing machine is complex, different parts have the same frequency signal in running, so it is very difficult to obtain the fault and status signal. In this paper we present a new method to monitor printing machine condition based on printing image texture. First we collect GATF images from different printing, then use gray level co-occurrence matrices (GLCM) to extract feature from GATF pictures, the features are classified by BP neural network methods, it can reflect part of printing machine condition.

Abstract
Keywords
Introduction
The Relationship of GATF Star Deformation and Ink Change
GLCM and Textrue
Experiment and Analysis Texture
Experiment and Analysis
Conclusion and Outlook
Acknowledgments
References
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