Sub surface damage measurements based on short coherent interferometry

Sergeeva, Maria V.; Khrenikov, K.; Hellmuth, Thomas; Boerret, Rainer

doi:10.2971/jeos.2010.10003

Cited by 19 publications

(5 citation statements)

References 3 publications

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“…SSD depth can be empirically predicted with the size of abrasive grains during grinding or lapping, for which several researchers arrived at different results [40,[55][56][57][58]. Lambropoulos et al [59] proposed a relationship between the damage depth and the size of abrasive grains, expressed as Eq.…”

Section: Predictive Methodsmentioning

confidence: 99%

“…However, the images were blur because of the strong surface scattering, weak subsurface scattering and big tomography interval. Sergeeva et al [57] used the short coherent interferometry to measure the artificial SSD in a glass, and reported that the depth and lateral resolution were 10 μm and 4 μm, respectively. While in a practical situation, cracks show more complex configurations, such as "chevron", "branch" and "fork" [73].…”

Section: (8)mentioning

confidence: 99%

See 1 more Smart Citation

Methods for Detection of Subsurface Damage: A Review

Yin

Bai

2018

Chin. J. Mech. Eng.

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Subsurface damage is easily induced in machining of hard and brittle materials because of their particular mechanical and physical properties. It is detrimental to the strength, performance and lifetime of a machined part. To manufacture a high quality part, it is necessary to detect and remove the machining induced subsurface damage by the subsequent processes. However, subsurface damage is often covered with a smearing layer generated in a machining process, it is rather difficult to directly observe and detect by optical microscopy. An efficient detection of subsurface damage directly leads to quality improvement and time saving for machining of hard and brittle materials. This paper presents a review of the methods for detection of subsurface damage, both destructive and non-destructive. Although more reliable, destructive methods are typically time-consuming and confined to local damage information. Non-destructive methods usually suffer from uncertainty factors, but may provide global information on subsurface damage distribution. These methods are promising because they can provide a capacity of rapid scan and detection of subsurface damage in spatial distribution.

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Section: Predictive Methodsmentioning

confidence: 99%

Section: (8)mentioning

confidence: 99%

Methods for Detection of Subsurface Damage: A Review

Yin

Bai

2018

Chin. J. Mech. Eng.

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“…Guss et al 112 used OCT to accurately obtain SSD images from fused silicon and measure cracks 300 μm below the surface. Sergeeva et al 113 used OCT to measure the SSDs in optical glass lenses and obtained depth direction and transverse resolutions of 10 and 4 μm, respectively.…”

Section: Nondestructive Detectionmentioning

confidence: 99%

3D microscopy in industrial measurements

You

Liu

et al. 2022

Journal of Microscopy

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Quality control is essential to ensure the performance and yield of microdevices in industrial processing and manufacturing. In particular, 3D microscopy can be considered as a separate branch of microscopic instruments and plays a pivotal role in monitoring processing quality. For industrial measurements, 3D microscopy is mainly used for both the inspection of critical dimensions to ensure the design performance and detection of defects for improving the yield of microdevices. However, with the progress of advanced manufacturing technology and the increasing demand for high‐performance microdevices, 3D microscopy has ushered in new challenges and development opportunities, such as breakthroughs in diffraction limit, 3D characterisation and calibrations of critical dimensions, high‐precision detection and physical property determination of defects, and application of artificial intelligence. In this review, we provide a comprehensive survey about the state of the art and challenges in 3D microscopy for industrial measurements, and provide development ideas for future research. By describing techniques and methods with their advantages and limitations, we provide guidance to researchers and developers about the most suitable technique available for their intended industrial measurements.

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“…They expose SSDs through physical or chemical means, and will cause irreversible damage to the optics. Non-destructive methods based on optical imaging include total internal reflection microscope (TIRM) [11] , confocal laser scanning microscope(CLSM) [12,13] , and optical coherence tomography(OCT) [14] , etc. They illuminate the detection area in different ways, receive the optical signal modulated by SSDs, and will not cause damage.…”

Section: Introductionmentioning

confidence: 99%

Detection Of Surface Defects And Subsurface Defects Of Polished Optics With Multisensor Image Fusion

Sun

Wang

et al. 2022

Preprint

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Surface defects (SDs) and subsurface defects (SSDs) are the key factors decreasing the laser damage threshold of optics. Due to the spatially stacked structure, accurately detecting and distinguishing them has become a major challenge. Herein a detection method for SDs and SSDs with multisensor image fusion is proposed. The optics is illuminated by a laser under dark field condition, and the defects are excited to generate scattering and fluorescence lights, which are received by two image sensors in a wide-field microscope. With the modified algorithms of image registration and feature-level fusion, different types of defects are identified and extracted from the scattering and fluorescence images. Experiments show that two imaging modes can be realized simultaneously by multisensor image fusion, and HF etching verifies that SDs and SSDs of polished optics can be accurately distinguished. This method provides a more targeted reference for the evaluation and control of the defects of optics, and exhibits potential in the application of material surface research.

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Sub surface damage measurements based on short coherent interferometry

Cited by 19 publications

References 3 publications

Methods for Detection of Subsurface Damage: A Review

Methods for Detection of Subsurface Damage: A Review

3D microscopy in industrial measurements

Detection Of Surface Defects And Subsurface Defects Of Polished Optics With Multisensor Image Fusion

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