Spatial phase retrieval of vortex beam using convolutional neural network

Vortex beam (VB) possessing spatially helical phase–front has attracted widespread attention in free-space optical communication, etc. However, the spiral phase of VB is susceptible to atmospheric turbulence, and effective retrieval of the distorted conjugate phase is crucial for its practical applications. Herein, a convolutional neural network (CNN) approach to retrieve the phase distribution of VB is experimentally demonstrated. We adopt a spherical wave to interfere with VB for converting its phase information into intensity changes, and construct a CNN model with excellent image processing capabilities to directly extract phase–front features from the interferogram. Since the interference intensity is correlated with the phase–front, the CNN model can effectively reconstruct the wavefront of conjugate VB carrying different initial phases from a single interferogram. The results show that the CNN-based phase retrieval method has a loss of 0.1418 in the simulation and a loss of 0.2344 for the experimental data, and remains robust even in turbulence environments. This approach can improve the information acquisition capability for recovering the distorted wavefront and reducing the reliance on traditional inverse retrieval algorithms, which may provide a promising tool to retrieve the spatial phase distributions of VBs.

Dynamic Wind Turbine Blade Inspection Using Micro-Polarisation Spatial Phase Shift Digital Shearography

Shearography, as a novel non-destructive evaluation technique, has shown notable ability in the detection of composite materials. However, in current shearography practices, the phase shifting and loading methods applied are mainly static. For instance, vacuum hood or force loading facilities are often used in phase-shifting shearography, and these are hard to realise with robotic control, especially for on-board inspection. In this study, a dynamic process for detecting defects in the subsurface of a wind turbine blade (WTB) using spatial phase shift with dynamic thermal loading was proposed. The WTB sample underwent a dynamic thermal loading operation, and its status is captured by a Michelson interferometric-based spatial phase shift digital shearography system using a pixelated micro-polarisation array sensor. The captured images were analysed in a 2D frequency domain and low-pass filtered for phase map acquisition. The initial phase maps underwent a window Fourier filtering process and were integrated to produce a video sequence for realisation of visualising the first derivative of the displacement in the process of thermal loading. The approach was tested in experimental settings and the results obtained were presented and discussed. A comparative assessment of the approach with shearography fringe pattern analysis and temporal phase shift technique is also presented and discussed.

Wavefront detection method for orbital angular momentum modes based on conformal mapping-spatial phase shifting interferometry

The orbital angular momentum (OAM) of light has garnered significant interest in recent years owing to its various applications, and extensive creative research has been conducted to generate OAM. However, the particular helical phase structure of an optical vortex leads to non-smooth and discontinuous phase profiles and hinders the accurate recovery of the phase distribution of the vortex beam. Significantly, the existence of a wavefront dislocation leads to the failure of the traditional phase unwrapping algorithm. At the same time, it is essential to detect the wavefront of OAM modes in real-time for free-space optical communication and optical precision measurement. Therefore, we designed conformal mapping-spatial phase-shifting interferometry and achieved rapid and high-precision wavefront measurements for the OAM modes. The wavefront of the OAM modes with a topological charge of 1,2,4 and 6 were measured, respectively. The results were significantly consistent with the anticipated results based on simulations. This study revealed the mathematical mechanism behind the forked fringe patterns and presented a method for demodulating the helical wavefront from the forked fringe patterns.