The current loaded tooth contact analysis of cycloid drives based on the assumption of theoretical positions of ring pins ignores the deviations caused by manufacturing errors and elastic deformations, which are not in agreement with reality. To fill this gap, an improved load distribution model of the mismatched cycloid-pin gear pair with ring pin position deviations is presented for a component-level analysis. Firstly, with the cycloid gear tooth profile geometry defined, the unloaded tooth contact analysis is applied as a pre-processor to determine the potential contact points, the gear backlash, and the rotation angle of the cycloid gear. Secondly, due to the statically indeterminate structure of the multi-tooth contact, a varying nonlinear contact stiffness is introduced to establish the relation between force and deformation. Then, the force and moment equilibrium equations with compatibility conditions are solved by using an iterative approach. With this, detailed parametric case studies are presented to verify the correctness of the proposed model by comparing it with those predicted by the current model and to demonstrate the influences of ring pin position deviations on the distributed load, contact stress, loaded transmission error, and instantaneous gear ratio of the mismatched cycloid-pin gear pair. This study provides a deeper investigation into the load distribution characteristics of the cycloid drive and therefore can be employed to assist in gear design.

Due to their advantages of compact size, high reduction ratio, large stiffness and high load capacity, RV reducers have been widely used in industrial robots. The dynamic characteristics of RV reducers in terms of vibratory response and dynamic transmission error have a significant influence on positioning accuracy and service life. However, the current dynamic studies on RV reducers are not extensive and require deeper study. To bridge this gap, a more effective and realistic lumped parameter dynamic model for RV reducers is developed, considering the tooth profile modification of cycloid gears and system errors. Firstly, for an efficient solution, the equivalent pressure angle and equivalent mesh stiffness of the cycloid–pin gear pair are introduced in the dynamic model based on the loaded tooth contact analysis. Secondly, the differential equations of the system are derived by analyzing the relative displacement relationships between each component, which are solved using the Runge–Kutta method. With this, the effects of errors such as machining errors, assembly errors and bearing clearances on the dynamic behaviors and transmission precision are investigated by comparison to quantify or qualify their influence. This research is helpful in characterizing the multi-tooth mesh and dynamic behavior, and revealing the underlying physics of the RV reducer.

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In the field of intelligent driving of freight trains, determining the track line ahead of the train is an important function in the autopilot technology of such trains. Combining the characteristics of freight railway tracks, we conduct an in-depth analysis of the shortcomings of object detection technology in extracting track lines and propose an improved Zhang–Suen (ZS) thinning theory for a railway track line recognition algorithm. Through image preprocessing and single pixel thinning steps, a continuous track line is obtained and then processed by a denoising algorithm to obtain a complete track line. Experimental results show that the track extracted by our method has good continuity and less noise. It can simultaneously perform track detection on straight roads, curves and turnouts, and is suitable for changing weather conditions such as sunny daytime, mild rainy daytime, cloudy daytime, night with lamp lighting and night without lamp lighting conditions.