The cycloid gear wear of RV reducers leads to the degradation of the industrial robots’ transmission accuracy, but the degradation law with respect to the wear volume is still unclear. In this paper, a method for determining transmission error (TE) through a combination of numerical and simulation analysis is proposed. The wear model of cycloid gear was ascertained based on the theory of Archard. Then, the full rigid body and rigid–flexible coupling model of RV reducers were established using the multibody dynamics theory. Finally, the static transmission error (STE) and dynamic transmission error (DTE) were investigated. The results show that as working hours increase, the cycloid gear wear volume increases, and transmission accuracy deteriorates, but the rate tends to slow down.

In this paper, the application scope of the average flow model is extended to grease lubrication considering the non-Newtonian characteristics. First, flow factor expressions applicable to both Newtonian fluids and non-Newtonian fluids are derived. Then, a model problem is established by coupling the Reynolds governing equation, film thickness function, and boundary conditions and solved for the flow factor. Fit the result into empirical relations for conveniently using in the grease lubrication analysis. Finally, the influence of several parameters on the flow factor is studied. The results demonstrate that the film thickness ratio, rheological index, and surface elastic deformation have a significant effect on the flow factor, and the influence law is affected by the orientation of the surface roughness.

The rotation speed directly influences the vibration and lubrication behaviors of gear pairs, but studying the effects of time-varying rotation speeds during their operation poses substantial challenges. The present work proposed an approach to analyzing the dynamic response and lubrication performance of spur gear pairs under time-varying rotation speeds. A single-degree-of-freedom torsional dynamics model was established to capture the vibration responses and meshing forces of a gear pair, with the meshing stiffness modulated by the time-varying rotation speed. Additionally, a transient elastohydrodynamic lubrication model of the gear system was proposed to obtain the pressure pro-file and film shape, incorporating the effects of time-varying rotation speeds. Three types of time-varying rotation speeds were investigated: acceleration, deceleration, and oscillation. The results reveal that the time-varying rotation speed induces chaotic motion of the gear system, resulting in significant changes in the dynamic meshing force, entrainment velocity, and curvature radius of the gear pair compared to those in constant-speed scenarios. The lubrication performance under time-varying rotation speeds also shows diverse dynamic characteristics, highlighting significant differences from that observed under a constant rotation speed. These insights contribute to a more comprehensive understanding of gear dynamics under realistic operating conditions, enhancing gears’ performance and reliability in practical applications.

Wear is one of the most common failure forms of gear transmission system. In this paper, a dynamic wear reliability evaluation method for gear system, which subjects to stochastic external load, is proposed on the basis of the Markov diffusive process. The stochastic load is considered as the combination of constant load and random noise. The failure is defined as the wear depth of the maximum wear point of gear under the constant load that exceeds a specific threshold. The maximum wear point and relative sliding velocity are obtained by deterministic wear analysis. The stochastic noise is assumed as Gaussian white noise; hence, the wear depth can be described as Markov diffusive process, and the transition probability is governed by Fokker–Planck–Kolmogorov (FPK) equation. With the transition probability function, the wear life and dynamic reliability of gear systems with different noise spectral densities are predicted. The results reveal that the wear depth obeys normal distribution and becomes more and more scattered with noise spectral density increases. The wear life does not obey normal distribution, and the effect of noise spectral density on mean life is neglectable while on a standard deviation of life is considerable.

To address the challenge of predicting lubrication states and reliability caused by the uncertainty of gear materials and structural parameters, a lubrication reliability analysis method considering the randomness of gear parameters is proposed. Firstly, a nonlinear dynamic model of a gear pair is established to derive the dynamic meshing force. The geometric and kinematic analyses are then performed to determine time-varying equivalent curvature radius and entrainment velocity. The minimum film thickness during meshing is further calculated. Considering gear parameters as random variables, a gear lubrication reliability model is formulated. Monte Carlo Simulation method is employed to accurately analyze the dynamic response, dynamic meshing force, equivalent curvature radius, entrainment velocity, probability distribution of minimum film thickness, and gear lubrication failure probability. Additionally, a specialized wear test device is designed to investigate the evolution of tooth surface roughness with wear and to forecast trends in gear lubrication failure probability as wear progresses. The results indicate that the uncertainty in gear parameters have minimal impact on the equivalent curvature radius and entrainment velocity, but significantly affect the dynamic meshing force. The gear speed and root mean square roughness are critical factors affecting lubrication reliability, and the early wear of the teeth enhances the lubrication reliability. The present work provides valuable insights for the design, maintenance, and optimization of high-performance gear systems in practical engineering applications.

We propose a wind spectrum–response surface dual-domain coupling method to study the reliability optimization of tall structures under the action of unsteady wind fields. Unlike traditional research, the dual-domain coupling analysis can quickly and accurately capture structural response defects and optimize size. The first parametric modeling technology establishes a high-precision finite element model of the movable boom structure by establishing a dual-domain coupling framework of pulsating wind and structural optimization. Using MATLAB (instructional R2024b version), the pulsating wind is simulated with uncertainty. The pulsating wind speeds at different heights are converted into wind loads acting on the net-sealed movable boom structure. Secondly, the boom structure’s dynamic response analysis and response surface optimization design were carried out. The final results show that the maximum value of displacement of the optimized net sealer boom is reduced by about 8.06%, the maximum value of stress is reduced by about 11.04%, and the stiffness is improved through the stress monitoring of the existing structure. It showed that the wind-resistant capability of the boom studied by this method is enhanced, improving the study’s efficiency.