Detection of micro-sized air bubble defects in optical glass based on Mie theory

The existence of bulk bubbles could decrease the laser-induced damage threshold of optics and affect the beam quality, so the detection of bulk bubbles is an essential step for quality assurance. Currently, the inspection of bubbles in optics relies on manual work, which is not recommended because of the low precision and inconsistency. To improve the quality evaluation process, a real-time detection method for bubbles inside the optics based on deep learning is proposed. Our method can implement bubble detection at 67 fps with a recall of 0.836. As for retrieval of the radius, it costs 58.8 ms on each bubble, and the absolute deviation is 3.73% on average. Our method conducts real-time and accurate detection of the positions and radii of the bubbles in the optics, thus, having significant potential for the manufacturing process.

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Real-time detection method for bulk bubbles in optics based on deep learning

Wang

Cheng

ChangDe

et al. 2022

Appl. Opt.

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Detection of micro-sized air bubble defects in optical glass based on Mie theory

Cited by 1 publication

References 7 publications

Real-time detection method for bulk bubbles in optics based on deep learning

Real-time detection method for bulk bubbles in optics based on deep learning

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