A Multi-Fidelity Integration Method for Reliability Analysis of Industrial Robots

忠诚 计算机科学 高斯求积 可靠性(半导体) 数值积分 正交(天文学) 算法 高斯分布 概率密度函数 数据集成 数学 数据挖掘 尼氏法 统计 工程类 数学分析 电信 功率(物理) 物理 量子力学 电气工程 积分方程
作者
Jinhui Wu,Pengpeng Tian,Shunyu Wang,Yourui Tao
出处
期刊:Journal of Mechanical Design [American Society of Mechanical Engineers]
卷期号:146 (1) 被引量:2
标识
DOI:10.1115/1.4063404
摘要

Abstract A multi-fidelity integration method is proposed to analyze the reliability of multiple performance indicators (MPI) for industrial robots. In order to high-fidelity mapping the performance of industrial robots, a unified multi-domain model (UMDM) is first established. The contribution-degree analysis is then used to classify the input random variables into interacting and non-interacting ones. Thus, the high-dimensional integration of reliability analysis is separated into a low-dimensional integration and multiple one-dimensional integrations in an additive form. Here, the low-dimensional integration consisting of the interacting variables is calculated using the high-precision mixed-degree cubature formula (MDCF), and the computational results are treated as high-fidelity data. The one-dimensional integration consisting of non-interacting variables is then computed by the highly efficient five-point Gaussian Hermite quadrature (FGHQ), and the computational results are named low-fidelity data. A multi-fidelity integration method is constructed by fusing the high-fidelity data and the low-fidelity data to obtain the statistical moments of the MPI. Subsequently, the probability density function and the failure probability of the MPI are estimated using the saddlepoint approximation method. Finally, some representative methods are performed to verify the superiority of the proposed method.
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