An Application of Simulated Annealing in Compensation of Nonlinearity of Scanners

Rayyan Manwar,Mohsin Zafar,Adrian Podoleanu,Mohammad Avanaki

doi:10.3390/app9081655

Rayyan Manwar, Mohsin Zafar + Show 2 more

Open Access

https://doi.org/10.3390/app9081655

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Journal: Applied Sciences	Publication Date: Apr 22, 2019
Citations: 7	License type: CC BY 4.0

Affiliation: Wayne State University, University of Kent

Abstract

Galvo scanners are popular devices for fast transversal scanning. A triangular signal is usually employed to drive galvo scanners at scanning rates close to the inverse of their response time where scanning deflection becomes a nonlinear function of applied voltage. To address this, the triangular signal is synthesized from several short ramps with different slopes. An optimization algorithm similar to a simulated annealing algorithm is used for finding the optimal signal shape to drive the galvo scanners. As a result, a significant reduction in the nonlinearity of the galvo scanning is obtained.

Highlights

Two orthogonal scanners are generally required in the implementation of any optical system based on flying spot for transversal scanning [1,2,3]
Our aim is to alter the shape of each ramp in the triangular signal, using an optimization algorithm [22,28,29,30,31,32,33,34], until the photodetected signal presented maximum regularity in the succession of peaks corresponding to the beam being scanned over regularly placed empty spaces, to produce equidistant spikes, and narrow the fast Fourier transform (FFT) peak
The optimization algorithm was implemented in LabVIEW on a quad core computer with 16 GB

Summary

Introduction

Two orthogonal scanners are generally required in the implementation of any optical system based on flying spot for transversal scanning [1,2,3]. One common problem with galvo-scanners, when driven at high rates, is that they are not able to follow the shape of the input signal perfectly. They do not perform as expected (see Figure 1), and create artefacts in the acquired signal [14,15,16,17,18]. Several procedures are known to correct for such nonlinearities, the most popular one being to alter the image depending on the position signal This requires a specialized frame grabber, complex software, and expensive galvo-scanners, equipped with position. Ramp, it becomes possible to reduce the artefacts [19]

A Triangular

Results

Discussion and Conclusions