A neural network-based machine vision method for surface roughness measurement

Author(s):  
Zhisheng Zhang ◽  
Zixin Chen ◽  
Jinfei Shi ◽  
Ruhong Ma ◽  
Fang Jia
Author(s):  
Richard Y. Chiou ◽  
Yongjin James Kwon ◽  
Yueh-Ting Yang ◽  
Robin Kizirian ◽  
Tzu-Liang Bill Tseng

This paper presents a new method of surface roughness measurement developed for use in a web-enabled production environment. This method employs an Internet-based vision system to measure and analyze the pattern of scattered light from a surface of an object to derive roughness parameters. The roughness parameters are obtained for a number of metal specimens which are machined to different roughnesses. A correlation curve is established between optical intensity and the corresponding average surface roughness. The quality measurement data is monitored through the web browser while surface roughness parameters are inspected using a machine vision system. This allows the system to operate over the Internet since the machine vision system is integrated with LabVIEW-based graphic user interface (GUI).


2017 ◽  
Vol 137 (3) ◽  
pp. 147-152 ◽  
Author(s):  
Tetsuo Fukuchi ◽  
Norikazu Fuse ◽  
Mitsutoshi Okada ◽  
Tomoharu Fujii ◽  
Maya Mizuno ◽  
...  

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