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There are a large number of uncertainties in engineering design, and the accumulated uncertainties will enlarge the overall failure probability of the structure system. Therefore, structural design considering uncertainties has good guiding significance for improving the reliability of engineering structures. To address this issue, the dynamic-static structural topology optimization is established and reliability-based topology optimization with decoupling format is conducted in this study. The design point which satisfying the constraint of the target reliability indicator is obtained according to the reliability indicators of the first-order reliability method, and the uncertain design variables are modified into a deterministic variable according to the sensitivity information.

The mechanical claw is an important functional part of intelligent sanitation vehicles. Its performance significantly influences the functional reliability and structural safety of intelligent sanitation vehicles. The load of the trash changes extensively during the work of the mechanical claw. Hence, a comprehensive consideration of structural uncertainty during designing is needed to meet performance requirements. Uncertainty optimization design should be applied to reduce the sensitivity of structural performance to uncertain factors and ensure the robust performance of the mechanical paw structure. In this study, a numerical model of the mechanical claw of novel intelligent sanitation vehicles is established first in SolidWorks, and a finite element model is built by Optistruct. Based on the analysis of uncertain load factors of the mechanical claw, a robust mathematical model of uncertain factors is established by the Gauss-Chebyshev and Smolyak algorithm.

In order to avoid the influence of the change of the camera pitch angle and the variation of the height of the ground on the ranging accuracy, improve the real-time performance of the algorithm by substituting the current widely-used monocular vision ranging algorithm which builds the optical model based on the shadow of the vehicle floor and the lane line, as well as avoid the classification of vehicle detection, a vehicle distance measurement algorithm based on monocular vision and license plate width is established. Firstly, the target image acquisition and preprocessing are studied. Then the paper studies the license plate image location segmentation method based on accelerated template matching. On this basis, the algorithm for obtaining the ratio of license plate width to image width is studied, and the function of vehicle distance and license plate ratio width is established.