Du Chuanyao, Ma Shuqing, Yang Ling, et al. Dual optical path visibility system measuring method and experiment. J Appl Meteor Sci, 2014, 25(5): 610-617.
Citation:
Du Chuanyao, Ma Shuqing, Yang Ling, et al. Dual optical path visibility system measuring method and experiment. J Appl Meteor Sci, 2014, 25(5): 610-617.
Du Chuanyao, Ma Shuqing, Yang Ling, et al. Dual optical path visibility system measuring method and experiment. J Appl Meteor Sci, 2014, 25(5): 610-617.
Citation:
Du Chuanyao, Ma Shuqing, Yang Ling, et al. Dual optical path visibility system measuring method and experiment. J Appl Meteor Sci, 2014, 25(5): 610-617.
Dual optical path visibility system is a visibility measuring system based on a charge coupled device (CCD) digital camera and a light attenuation theory in atmosphere. Photovoltaic conversion process is realized by using the CCD to measure the light attenuation in the atmosphere. Two target reflection and background devices at different fixed distances are installed in the dual optical path visibility system and have identical characteristics except for distances. During measurement, a light source and the CCD are arranged at the same place, light signal sent by the light source is transmitted to the target reflector and reflected back, two beams of light reflected back are received by the CCD, the CCD converted reflected beams of light to corresponding facula images, and the whole photovoltaic conversion process is completed. Compared with the traditional digital camera method in which the same distance between a CCD and a target device is set, the light path distance of the dual optical path visibility system is doubled because of light reflection. The facula images captured by the CCD are transmitted to a computer and the attenuation information and background grey information of target facula images are acquired by digital image processing. The center of gravity method is used to dynamically extract the attenuation information of the target facula images, random noise is eliminated by averaging a plurality of extracted facula images, and the attenuation information is used for visibility back calculating. A back calculation formula is derived based on the classical optical attenuation theory, the formula is improved by combining an actual experimental platform, and finally, visibility is calculated. Through contrast experiments and correlation coefficients, the basic trend of visibility data of the dual optical path visibility system is consistent with that of the traditional transmission visibility meter and the traditional forward scatter visibility meter, especially when the visibility is low, and with the visibility increasing, the trend consistency declines to some extent. According to the mean deviation and mean relative deviation, visibility data of the dual optical path visibility system are more close to the traditional transmission visibility meter because of a similar working principle, as the dual optical path visibility system and the traditional transmission visibility measure attenuation of a whole light path while the forward scatter visibility meter only measures atmospheric scattering. With the visibility increasing, the visibility data deviation of the dual optical path visibility system and the traditional transmission visibility meter become larger mainly because of more fluctuation. In addition, optical axis alignment of the traditional transmission visibility meter is required and the camera lens of the traditional transmission visibility meter is sensitive to contaminant. Through visibility data comparison of day and night, it is observed that sunlight influences on the visibility data are basically eliminated.
Fig.
3
Visibility comparison by different measuring methods
(a) low visibility comparison diagram on 8 June 2013, (b) medium daytime visibility comparison diagram on 13 June 2013, (c) high visibility comparison diagram on 13 June 2013
Liaw J J, Lian S B, Huang Y F, et al.Atmospheric Visibility Monitoring Using Digital Image Analysis Techniques.13th International Conference on Computer Analysis of Images and Patterns (CAIP 2009), 2009:1204-1211.