Two-Dimensional Surface Roughness Measurement Using Scattered Light(Optical Method 3)

2001 ◽  
Vol 2.01.03 (0) ◽  
pp. 851-856
Author(s):  
Masanori KURITA ◽  
Katuhiro TANAKA
Keyword(s):  
Surface Roughness ◽  
Optical Method ◽  
Scattered Light ◽  
Two Dimensional ◽  
Roughness Measurement ◽  
Surface Roughness Measurement ◽  
Dimensional Surface

A Consideration of Surface Roughness Measurement by Optical Method

1987 ◽  
Vol 109 (2) ◽  
pp. 100-105 ◽  
Author(s):  
M. Shiraishi
Keyword(s):  
Surface Roughness ◽  
Computer Simulations ◽  
Optical Method ◽  
Measuring System ◽  
Roughness Measurement ◽  
Surface Roughness Measurement ◽  
Reflection Theory ◽  
Simulation Results ◽  
Reflection Characteristics ◽  
Good Agreement

A modified reflection theory based on Beckmann and Spizzichino is described which evaluates the surface roughness in connection with Rmax roughness value. Computer simulations due to this theory are relatively in good agreement with the experiments. Further, the simulation results suggest that the reflection characteristics can be freely changed to some extent by varying the incidence and acceptance angles of light. Also, the proposed measuring system is easily applicable to the real-time detection of turned surfaces without affecting its working accuracy.

Non-Contact Surface Roughness Measurement for Remote Quality Control

2010 ◽  
Author(s):  
Richard Y. Chiou ◽  
Yongjin James Kwon ◽  
Yueh-Ting Yang ◽  
Robin Kizirian ◽  
Tzu-Liang Bill Tseng
Keyword(s):  
Surface Roughness ◽  
Machine Vision ◽  
Vision System ◽  
Scattered Light ◽  
Measurement Data ◽  
Machine Vision System ◽  
Production Environment ◽  
Roughness Parameters ◽  
Roughness Measurement ◽  
Surface Roughness Measurement

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).

Sign in / Sign up

Export Citation Format

Share Document