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Road quality information detect system is an important component in architecture quality detect system, also is the basement of successfully working of other related project for the whole country. The study of detecting the road crack is the key to insure the security of accurately detect the road quality in transportation system. In this paper, we come up with a fixed way of road undersized rift image detection by using cellular neural networks. By image processing, building rift networks and details networks and adding the model of similarity undersized rift networks. It can avoid the problem that can not accurately detect undersized crack by only taking the crack feature value. The experiment proved that fixed crack detect computing is easy to do, more accurate to detect the undersized cracks on the road and can reach the standard level of current detect technique.

According to structure feature and principle of relying on relative rotation among hubs to realize elastic deformation of elastic spoke and varying diameter of a novel variable diameter walking wheel, finite element model was created based on the theory of continuous collision and the nonlinear contact between the wheel’s caster and ground was defined through introducing mobile marker in SIMPACK software. Dynamics simulation analysis was carried out respectively under two varying diameter strategies of the wheel and get the dynamic response in the mode of changing the diameter in situ and the minimum size of torque needing for varying diameter. The suitable for working condition and varying mode was pointed out via comparative analysis of the simulation’s results, and can provide theoretical basis for further rational design and study.

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