Due to the lack of image feature extraction in traditional panoramic image generation technology, the effect of 3D reconstruction of physical objects is poor. In this paper, fully digital stereoscopic 3D reconstruction technology is introduced in water conservancy surveying and mapping engineering to ensure complete panoramic image generation. Through in-depth analysis of the principle of 3D reconstruction technology and the database, the detailed water conservancy surveying and mapping engineering images are obtained, the feature vectors of the obtained panoramic images are matched, and the database is compared and positioned according to the matched position features. By using the initial position camera and calibration features, comparison and query are conducted with the image database, to remove the worthless confidence data, retain the outline of the object with reference value, obtain a fixed pose center point, and remove the overlapping area in the process of 3D reconstruction after calculating the outline of the image. Finally, the automatic generation of panoramic images is realized. Finally, the results of experimental analysis show that the panoramic image generation technology of the fully digital stereoscopic 3D reconstruction proposed in this paper has a relative accuracy of 49% compared with the traditional image generation method, and the effect of image generation is relatively good, which has a certain use value.
Aiming to study the working efficiency and stability of the loader, the hydraulic system of the loader is studied. Taking the ZL50 loader as the research carrier, the working conditions of the loader and the working principle of the hydraulic system are analysed at first. AEMSim software is used to simulate and analyse the hydraulic system, and the necessity of using the algorithm to optimize the hydraulic system is put forward. Secondly, the mathematical model of key hydraulic system optimization is deduced, and genetic algorithm and neural network algorithm are used to optimize the analysis of the objective function, and the simulation results are compared and analysed again. The results show that the parameters optimized by GA and BP algorithm are better than the original parameters. Further analysis shows that the parameters optimized by GA algorithm are better than BP algorithm in smoothness.
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