Time-variant reliability analysis for industrial robot RV reducer under multiple failure modes using Kriging model

Abstract

This paper proposes a time-variant reliability method for an industrial robot rotate vector (RV) reducer with multiple failure modes using a Kriging model. Firstly, the limit state functions of the industrial robot RV reducer are built by considering time-variant load and material degradation based on the failure physic method. Secondly, a time-variant reliability analysis method for multiple failure modes is proposed based on a double-loop Kriging model. The inner loop is the extremal optimization for each limit state function based on the efficient global optimization (EGO). The outer loop is the active learning reliability analysis by combining multiple response Gaussian process model (MRGP) and the Monte Carlo simulation (MCS). Furthermore, three learning functions (U-function, EFF-function and H-function) are individually adopted to choose a new sample point until the convergence is satisfied. Case studies are finally provided to illustrate the effectiveness of the proposed method.