Shearography is a full-field speckle interferometric technique used to determine surface displacement derivatives. For an interferometric technique, shearography is particularly resilient to environmental disturbances and has hence become an invaluable measurement tool outside of the optics laboratory. Furthermore, the inclusion of additional measurement channels has turned shearography from a qualitative inspection tool into a system suitable for quantitative surface strain measurement. In this review article we present a comprehensive overview of the technique, describing the principle of operation, optical configurations, image processing algorithms and applications, with a focus on more recent technological advances.

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Shearography technology and applications: a review

Digital shearography has demonstrated great potential in direct strain measurement and, thus, has become an industrial tool for nondestructive testing (NDT), especially for NDT of delaminations and detection of impact damage in composite materials such as carbon fiber reinforced plastics and honeycomb structures. The increasing demand for high measurement sensitivity has led to the need for real-time monitoring of a digital shearographic phase map. Phase maps can be generated by applying a temporal, or spatial, phase shift technique. The temporal phase shift technique is simpler and more reliable for industry applications and, thus, has widely been utilized in practical shearographic inspection systems. This paper presents a review of the temporal phase shift digital shearography method with different algorithms and the possibility for real-time monitoring of phase maps for NDT. Quantitative and real-time monitoring of full-field strain information, using different algorithms, is presented. The potentials and limitations for each algorithm are discussed and demonstrated through examples of shearographic testing.

https://www.spiedigitallibrary.org/journals/optical-engineering/volume-52/issue-10/101902/Real-time-monitoring-of-phase-maps-of-digital-shearography/10.1117/1.OE.52.10.101902.pdf

Real-time monitoring of phase maps of digital shearography

The increasing usage of composite materials has called for more effective techniques for inspecting the integrity of composite structures, as composite materials generally have higher likelihood of having material imperfections. This chapter reviews shearography and its applications in non-destructive testing. Shearography is an interferometric technique for full-field, non-contacting measurement of surface deformation (displacement or strain). It was developed to overcome several limitations of holography by eliminating the reference beam. Consequently, it is less sensitive to environmental disturbances and is a practical tool that can be used in field/factory settings. In non-destructive testing, shearography reveals defects in an object by identifying defect-induced deformation anomalies. Shearography has already received considerable industrial acceptance, in particular, for nondestructive testing of tires and aerospace structures. Other applications of shearography include strain measurement, material characterization, residual stress evaluation, leak detection, hermetic seal evaluation, vibration studies and 3D shape measurement. This chapter focuses on its application in non-destructive testing with an emphasis on composite materials.

Non-destructive evaluation (NDE) of composites: digital shearography

Phase unwrapping is a necessary step in fringe-projection profilometry that produces accurate depth maps. However, the original wrapped phase is often corrupted by errors, and thus conventional spatial unwrapping suffers from error propagation, such as scanline-based unwrapping, and high complexity, such as quality-guided methods. In this paper, we propose a fast and robust spatial unwrapping method called multi-anchor scanline unwrapping (MASU). Different from previous work, when unwrapping each pixel, MASU refers to multiple anchors in the scanline, where each anchor has a threshold adapting to its location. In such a manner, a set of fringe order candidates are predicted by the anchors according to phase smoothness assumption, and the one with the highest number of votes is chosen. After that, with the obtained fringe order, the absolute phase and depth are computed. Simulation and experiments have shown that even corrupted by severe phase errors, the proposed MASU can still produce robust unwrapped results. In addition, MASU is thousands of times faster than quality-guided unwrapping with comparative or even superior depth accuracy.

Multi-anchor spatial phase unwrapping for fringe projection profilometry.

Digital holography can provide quantitative phase images related to the morphology and content of biological samples. After the numerical image reconstruction, the phase values are limited between −π and π; thus, discontinuity may occur due to the modulo 2π operation. We propose a new deep learning model that can automatically reconstruct unwrapped focused-phase images by combining digital holography and a Pix2Pix generative adversarial network (GAN) for image-to-image translation. Compared with numerical phase unwrapping methods, the proposed GAN model overcomes the difficulty of accurate phase unwrapping due to abrupt phase changes and can perform phase unwrapping at a twice faster rate. We show that the proposed model can generalize well to different types of cell images and has high performance compared to recent U-net models. The proposed method can be useful in observing the morphology and movement of biological cells in real-time applications.

Automated phase unwrapping in digital holography with deep learning

In optical measurement techniques, such as holographic and shearographic interferometry, digital speckle pattern interferometry, and 3-D computer vision, phase is used as a carrier for different physical quantities. For example, phase could stand for information concerning shape and deformation. The useful information is coded and wrapped into the range of −π to +π rad in a phase map. Phase unwrapping is the basic technique to resolve 2π ambiguities and recover expected physical quantities. We describe a novel method for unwrapping phase in a noise-disturbed phase map, which is characterized by broken fringes induced by different sources, such as a poor coherence length, high light or weak reflection on the sample surface, too dense fringes due to stress concentration, etc. In our method, broken fringes are detected and estimated. The phase map is segmented into different regions based on the quality of phase. Regions are ranked and arranged to construct a systematic unwrapping sequence. Unwrapping errors brought by broken fringes are minimized by the proposed unwrapping scheme. Several applications are presented to validate the new method.

Sheng Liu

Papers

Regional phase unwrapping method based on fringe estimation and phase map segmentation