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Related Experiment Video

Updated: Sep 25, 2025

Characterization of Surface Modifications by White Light Interferometry: Applications in Ion Sputtering, Laser Ablation, and Tribology Experiments

Characterization of Surface Modifications by White Light Interferometry: Applications in Ion Sputtering, Laser Ablation, and Tribology Experiments

Published on: February 27, 2013

Phase noise estimation based white light scanning interferometry for high-accuracy surface profiling.

Long Ma, Yuan Zhao, Xin Pei

|April 27, 2022

Summary

This summary is machine-generated.

This study introduces a novel phase noise estimation algorithm for white light scanning interferometry (WLSI) to enhance surface measurement accuracy. The method effectively reduces noise, achieving precise nano-scale measurements and showing potential for industrial applications.

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Last Updated: Sep 25, 2025

Characterization of Surface Modifications by White Light Interferometry: Applications in Ion Sputtering, Laser Ablation, and Tribology Experiments

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Published on: February 27, 2013

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High-speed Particle Image Velocimetry Near Surfaces

High-speed Particle Image Velocimetry Near Surfaces

Published on: June 24, 2013

Area of Science:

Metrology and Surface Characterization
Optical Instrumentation
Signal Processing

Background:

White light scanning interferometry (WLSI) is a powerful technique for precision measurements.
Measurement accuracy in WLSI is often limited by phase noise from systemic and environmental disturbances.
Existing methods require improvement for accurate surface recovery in complex scenarios.

Purpose of the Study:

To propose a phase noise estimation-based surface recovery algorithm for WLSI.
To significantly improve measurement accuracy by reducing phase map noise.
To validate the algorithm's effectiveness in nano-scale metrology and industrial inspections.

Main Methods:

Phase noise analysis in the spectrum domain, defining noise as a linear combination of complex terms.
Establishing a function relating surface features to phase noise based on theoretical linearity.
Applying least square estimation (LSE) to determine an optimal phase noise estimation via a spectral coefficient.

Main Results:

Successful noise reduction in the phase map, leading to more accurate surface reconstruction.
Achieved a measurement of a 9.5nm step height standard as 9.49nm with 0.17nm repeatability.
Demonstrated potential for industrial inspection by testing an aero-engine blade's leading edge.

Conclusions:

The proposed phase noise estimation algorithm effectively reduces noise in WLSI measurements.
The method significantly enhances surface recovery accuracy at the nano-scale.
The technique shows promise for high-precision industrial inspection tasks.