A low cost adaptive optical system for improving solid-state laser beam quality has been set up. This
system consists of a deformable mirror, a high voltage amplifier, a set of solid-state laser system, a
CCD camera, a control software and corresponding optimization algorithm. This adaptive optical
system doesn't employ a wave-front sensor to detect the phase information, but optimize the light
intensity within a fixed aperture in the focal plane by a 19-element piezoelectricity deformable mirror.
In order to find the optimum surface profile of the deformable mirror, which is applied to correct the
phase aberrations in a solid-state laser system, a global genetic algorithm is introduced. The far-field
light intensity signal, which is measured by a CCD camera, is used as a fitness function of the genetic
algorithm. In this paper, the performance and efficiency of this wave-front sensor-less adaptive optical
system based on the genetic algorithm are presented. Both the simulation results and the experimental
results are given and discussed.
With the fast-speed real-time wavefront processor in 37-element adaptive optical (AO) system as example, the
limitation of conventional wavefront processor is analyzed, a novel wavefront processor is proposed based on ARM-based
embedded system. The method will enable the whole 37-element AO system compacter, smarter and more
effective. The merit of this processor will make the AO system be suitable for more especial situation. The hardware
configuration and the method of software based on Linux operating system are both exposited in detail.
KEYWORDS: Wavefronts, Solid state lasers, Laser systems engineering, Control systems, Reconstruction algorithms, CCD image sensors, Digital signal processing, Human-machine interfaces, Charge-coupled devices, Data acquisition
A high speed real-time wavefront processing system for a solid-state laser beam cleanup system has been built. This
system consists of a core2 Industrial PC (IPC) using Linux and real-time Linux (RT-Linux) operation system (OS), a
PCI image grabber, a D/A card. More often than not, the phase aberrations of the output beam from solid-state lasers
vary fast with intracavity thermal effects and environmental influence. To compensate the phase aberrations of solid-state
lasers successfully, a high speed real-time wavefront processing system is presented. Compared to former systems,
this system can improve the speed efficiently. In the new system, the acquisition of image data, the output of control
voltage data and the implementation of reconstructor control algorithm are treated as real-time tasks in kernel-space, the
display of wavefront information and man-machine conversation are treated as non real-time tasks in user-space. The
parallel processing of real-time tasks in Symmetric Multi Processors (SMP) mode is the main strategy of improving the
speed. In this paper, the performance and efficiency of this wavefront processing system are analyzed. The opened-loop
experimental results show that the sampling frequency of this system is up to 3300Hz, and this system can well deal with
phase aberrations from solid-state lasers.
A conventional adaptive optical system (AOS) often measures the wavefront slope or curvature straightly by a wavefront sensor. However, another alternative approach allows the design of an AOS without an independent wavefront sensor. This technique detect the image quality affected by phase aberration in laser wavefront rather than measuring the phase aberration itself, and then the image quality is taken as a sharpness metric. When wavefront phase aberration is corrected, the sharpness metric reaches its maximum value. In this paper, a wavefront sensorless adaptive optical system (AOS) has been set up. This system mainly consists of a 19-element piezoelectricity deformable mirror (DM), a high voltage amplifier, a set of 650nm laser, a CCD camera and an industrial computer. The CCD camera is used to measure the light intensity within an aperture of the focus plane, and then this intensity is regarded as the sharpness metric to optimize. A Modified Hill Climbing Algorithm (MHC) and a Genetic Algorithm (GA) are used to control the DM to correct the phase aberrations in this system. Experimental results show that both of these two algorithms can be used successfully in this indirect wavefront measurement AOS. However, the GA can obtain better performance than the MHC. After phase aberrations are corrected, the βfactor are reduced from 5.5 to 1.5 and 1.9, from 30 to 1.2 and 1.4 respectively.
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