Roughness characterization of smooth machined surfaces by light scattering

Area of Science:

• Physics
• Materials Science
• Optical Engineering

Background:

• Traditional surface roughness characterization often relies on limited metrics like RMS deviation.
• A more detailed analysis is needed to understand surface properties across different spatial frequencies.

Purpose of the Study:

• To introduce and validate the surface spectral density function (SDF) for comprehensive surface roughness analysis.
• To compare SDF measurements with traditional interferometric methods.
• To characterize anisotropic and smooth machined surfaces.

Main Methods:

• Calculating the surface spectral density function (SDF) by modeling surfaces as superpositions of sinusoidal gratings.
• Measuring scattered light from a He-Ne laser beam reflected off surfaces.
• Rotating samples to analyze anisotropic surfaces.
• Comparing scattering-based SDF results with interferometric measurements.

Main Results:

• The SDF was successfully calculated from scattered light measurements.
• Anisotropic surfaces were characterized by analyzing the SDF at different rotation angles.
• The SDF provided a detailed examination of roughness as a function of spatial frequency.
• Comparison between interferometric and scattering methods was performed for both rough and smooth surfaces.

Conclusions:

• The surface spectral density function (SDF) offers a powerful method for detailed surface roughness characterization.
• SDF analysis provides insights into surface properties across various spatial frequencies, crucial for diverse applications.
• This technique is effective for both anisotropic and smooth surfaces, complementing existing methods.