High-precision large-aperture single-frame interferometric surface profile measurement method based on deep learning

Liang Tang, Mingzhi Han, Shuai Yang, Ye Sun, Lirong Qiu, Weiqian Zhao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Highlights This is the first time that high-precision measurement of large-aperture optical components has been realized by capturing single-frame interferograms without requiring a phase shifter. We integrate deep learning algorithms with interferometry methods to simulate the interferometric process in a deep learning framework. This approach mitigates environmental noise effects on measurement accuracy, eliminates phase shifters, and enables dynamic surface profile measurements of large-aperture optical components. Compared with traditional phase-shifting methods, this approach achieves a 48-fold time reduction while improving measurement efficiency and stability. We demonstrate a highly efficient dynamic measurement method that achieves comparable accuracy without ZYGO interferometers’ ultra-stable environment requirements.

Original languageEnglish
Article number055601
JournalInternational Journal of Extreme Manufacturing
Volume7
Issue number5
DOIs
Publication statusPublished - 1 Oct 2025

Keywords

  • deep learning
  • dynamic high-precision measurement
  • large-aperture optical components
  • single-frame interferometric
  • surface profile

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