Due to the limited joint position space and the consideration of reducing the moment of inertia and vibration for industrial robot, the design optimization for rotate vector (RV) reducer is becoming a new and urgent problem in industry. Currently, the existing researches focus on deterministic design optimization, which may cause unreliable designs without considering uncertainties. Therefore, the study focuses on the implementation of reliability-based design optimization (RBDO) to the RV reducer. The aim is to make the RV reducer smaller in size while ensuring a higher reliability. Firstly, a modified advanced mean value (MAMV) method is proposed to improve efficiency and robustness of the advanced mean value method, which encounters inefficiency and numerical instability for the concave or highly nonlinear performance measure functions. Secondly, a mathematical model of RBDO for the RV reducer is established. Thirdly, the proposed MAMV method is integrated into double-loop method to optimize the established mathematical model of RBDO with different target reliability. The results show that the proposed MAMV method is efficient compared with other methods. In addition, the volume of the RV reducer is correspondingly reduced by 9.44%, 7.89%, and 5.66% compared with that before optimization when the target reliabilities are 99.38%, 99.87%, and 99.98%.

由于关节位置空间有限，并且考虑到减小工业机器人的惯性矩和振动，旋转矢量（RV）减速器的设计优化正成为工业中的新问题和紧迫问题。当前，现有的研究集中在确定性设计优化上，这可能导致不可靠的设计而不考虑不确定性。因此，本研究着重于对RV减速器实施基于可靠性的设计优化（RBDO）。目的是使RV减速器尺寸更小，同时确保更高的可靠性。首先，提出了一种改进的高级均值（MAMV）方法，以提高高级均值方法的效率和鲁棒性，而对于凹或高度非线性的性能度量函数，该方法遇到效率低下和数值不稳定的问题。其次，建立了RV减速器的RBDO数学模型。第三，将提出的MAMV方法集成到双环方法中，以优化已建立的具有不同目标可靠性的RBDO数学模型。结果表明，与其他方法相比，该方法是有效的。另外，当目标可靠性为99.38％，99.87％和99.98％时，与优化前相比，RV减速器的体积分别减少了9.44％，7.89％和5.66％。