基于机器视觉的闸坝表面位移非接触式监测方法OA北大核心CSTPCD

Aiming at the problems of conventional monitoring method such as high labor density,low monitoring frequency,and difficulty in achieving long-term stable monitoring of the surface displacement of locks and dams,a non-contact intelligent monitoring method integrating spatio-temporal features is proposed.The method adopts an artificial target as a marker,takes a camera as an acquisition device,transmits image information wirelessly,and makes use of Adaptive Gamma Correction Weighted Distribution(AGCWD)and Weighted Guided Image Filter(WGIF)with improved edge-awareness factor.WGIF with edge-awareness factor to enhance the feature expression ability of low illumination images,and the Spatio-Temporal Context(STC)algorithm based on Bayesian framework on board the computer to deeply mine the contextual spatio-temporal information of the target image,and further introduce surface fitting to obtain sub-pixel level displacement information of the target to achieve the sub-pixel displacement information of both horizontal and vertical bi-directional surface displacements of the gate and dam.Further,surface fitting is introduced to obtain subpixel-level displacement information to achieve non-pixel-level non-contact monitoring of horizontal and vertical bi-directional surface displacements of the lock and dam.The la-boratory and field test results show that the displacement monitoring data under different experimental scenarios are highly consistent with the calibration data,and the error is less than 0.05 mm;compared with the existing image optimization processing methods,the image optimization processing methods based on AGCWD and WGIF increase the Peak Signal-to-Noise Ratio(PSNR)by 2.70％,increase the information entropy by 4.91％,and reduce the standard deviation by 2.63％;compared with the established target tracking algorithms,the STC target tracking al-gorithm based on surface fitting is more effective in obtaining sub-pixel-level displacement information.Compared with the existing target tracking algorithms,the field monitoring data of the STC target tracking algorithm based on surface fitting improves the accuracy of the similar target tracking algorithms by 48％,which can provide a high-precision solution for the monitoring of the gate and dam surface displacements.