RELIABILITY ALLOCATION OF INDUSTRIAL ROBOT SYSTEMS BASED ON BP NEURAL NETWORK AND PYTHAGOREAN FUZZY NUMBERS

XU Minjun; DONG Qiuxian; LIU Ruliang; LIU Jun; XIA Chenguang; FANG Xiaojie

doi:10.16579/j.issn.1001.9669.2025.08.016

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RELIABILITY ALLOCATION OF INDUSTRIAL ROBOT SYSTEMS BASED ON BP NEURAL NETWORK AND PYTHAGOREAN FUZZY NUMBERS

·Optimization·Reliability· | 更新时间：2025-08-18

- RELIABILITY ALLOCATION OF INDUSTRIAL ROBOT SYSTEMS BASED ON BP NEURAL NETWORK AND PYTHAGOREAN FUZZY NUMBERS
- Journal of Mechanical Strength Vol. 47, Issue 8, Pages: 131-140(2025)
- 作者机构：
  
  南昌大学数学与计算机学院，南昌 330031
- 作者简介：
  
  DONG Qiuxian, E-mail: dongqiuxian@163.com
- 基金信息：
  
  National Natural Science Foundation of China(72071099)
- DOI：10.16579/j.issn.1001.9669.2025.08.016
  CLC： TB114
- Received：05 November 2023，
  
  Revised：08 January 2024，
  
  Published：15 August 2025
- 稿件说明：
移动端阅览
徐闽军，董秋仙，刘汝良，等. 结合BP神经网络和毕达哥拉斯模糊数的工业机器人系统的可靠性分配［J］. 机械强度，2025，47（8）：131-140.

XU Minjun，DONG Qiuxian，LIU Ruliang，et al. Reliability allocation of industrial robot systems based on BP neural network and Pythagorean fuzzy numbers［J］. Journal of Mechanical Strength，2025，47（8）：131-140.
徐闽军，董秋仙，刘汝良，等. 结合BP神经网络和毕达哥拉斯模糊数的工业机器人系统的可靠性分配［J］. 机械强度，2025，47（8）：131-140. DOI： 10.16579/j.issn.1001.9669.2025.08.016.

XU Minjun，DONG Qiuxian，LIU Ruliang，et al. Reliability allocation of industrial robot systems based on BP neural network and Pythagorean fuzzy numbers［J］. Journal of Mechanical Strength，2025，47（8）：131-140. DOI： 10.16579/j.issn.1001.9669.2025.08.016.

摘要

为确保工业机器人实现可靠性目标，可靠性分配是其制造设计阶段需要完成的任务。根据工业机器人结构复杂、不确定度高、样品少且组成零件间具有失效相关性的特点，提出了一种基于反向传播（Back Propagation

BP）神经网络和毕达哥拉斯模糊数（Pythagorean Fuzzy Number

PFN）的工业机器人系统的可靠性分配方法，使用Copula函数建立系统可靠性模型，将工业机器人的故障分为系统级、子系统级和部件级3个层次，通过使用BP神经网络，将系统可靠性、子系统结构重要度和子系统复杂度作为输入变量，完成系统级到子系统级的可靠性分配；引入PFN对重要程度、环境条件、技术水平、可维修性、费用灵敏度、复杂性6个影响因素进行评分，从而构造分配权重，完成子系统级到部件级的可靠性分配。结果表明，该方法可以实现可靠性目标，并保证了可靠性的增长。

Abstract

In order to ensure the industrial robot realizes the reliability goal

reliability allocation is a task to be accomplished in its manufacturing design stage. According to the characteristics of industrial robots

such as complex structure

high uncertainty

few samples

and failure correlation between component parts

a reliability allocation method for industrial robot systems based on BP neural network and Pythagorean fuzzy numbers was proposed. Using Copula function to establish a system reliability model

the failures of industrial robots were classified into three levels

the system level

the subsystem level

and the component level. By using the back propagation (BP) neural network

the system reliability

subsystem structure importance and subsystem complexity were taken as the input variables to complete the system-to-subsystem reliability allocation. The Pythagoras fuzzy number was introduced to score the influence factors of importance

environmental condition

technical level

maintainability

cost sensitivity and complexity

complete the reliability allocation from the subsystem level to the component level.The results show that the methodology achieves reliability goals and ensures reliability growth.

关键词

Keywords

references

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