It is a difficult task to measure the optical uniformity of an optical coating with very large aperture. Here an automatic near-UV/VIS/NIR spectrophotometer has been developed for spectrum analysis of optical coatings on very large aperture optical elements. It can give two-dimensional scanning result of a sample with substrate surface size of 600mm*350mm and 70mm thickness. The testing beam can be s- or p-polarized, at an incident angle from 0° to 70°. The equipment is composed of optical system, mechanical structure, photo-translating module and computer control system. Because of the light deflection after passing through the very thick sample, an integrating sphere and a sphere moving structure was involved. The measuring beam is guided in a quartz fiber with a special interface that can improve coupling efficiency from the monochromator to fiber. The two-dimensional scanning work platform has the position accuracy about 0.05mm and a reproducibility of 0.01mm. The beam incident angle accuracy is controlled within 0.1°. The measurement results show that in the near-UV/VIS/NIR region, the overall photometric accuracy can get 0.1% and 0.2% for transmittance and reflectance, respectively. The wavelength scale is accurate to be within 0.4nm with a reproducibility of 0.05nm.
An auto-focusing and auto-alignment system based on digital image processing and the computer control technology was developed for 3-LCD projector manufacture. We analyzed the imaging characteristic of the optical system, and developed a mathematical model to realize the accurate focusing of each LCD panel and accurate alignment among three LCD panels. Based on the model, the experimental facility was set up, which is compose of five CCD detectors that are placed on the screen at different filed of view to capture images and regulating mechanism of LCD’s six-dimensional degree of freedom droved by stepper motors. Appropriate defocusing evaluation function and alignment algorithm were also presented in this paper. The images captured by CCDs are processed to get the defocusing amount of every panel by the variance function and displacement amount of the three LCD panels by the gravity model approach. Then commands are sent to regulating mechanism to control the movement of each panel. After several turns of auto-correction, all the panels are in the proper position. Experiment results show that with the proper algorithm, the system can provide high accuracy and good performance in projector manufacture. The whole focusing and alignment process can be finished within ten minutes which is far superior to that made by man more than half an hour. With this system, completely automatic product lines can be established, which can provide 3-panel LCD projector light engines with considerable focusing and alignment accuracy.
The optical recognition system is based on the optical characteristic extractor. In this report, a kind of new theory of the characteristic recognition system with artificial neural network is introduced. The optical compound eye system, lateral inhibition network and back propagation network (BP) are adopted to form a parallel neural network, recognition system. The field of view is divided into mosaic pixels by the plane compound eye lens, which is convenient to use single photoelectric detector. The information received by the detector is extracted characteristic through the lateral inhibition network. It is a parallel neural network made up of resistor network and it has the advantage of high speed, simple structure, etc. BP network is used for pattern recognition. Its weights are anew distributed during network learning processing. Once the studied object is detected again, the system will quickly response its pattern. In this paper, several experimental data of simple patters are given, and the precessions of the network recognition are analyzed. Finally, it is pointed out that the characteristic recognition system is feasible in applying to industrial detection and Chinese character recognition, etc.
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