联合MRGP和PSO的工业机器人驱动器可靠性分析

doi:10.12305/j.issn.1001-506X.2023.08.40

系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (8): 2643-2650.doi: 10.12305/j.issn.1001-506X.2023.08.40

• 可靠性 • 上一篇

联合MRGP和PSO的工业机器人驱动器可靠性分析

曾颖¹^,², 李彦锋¹^,²^,*, 王弘毅¹^,², 钱华明²^,³, 黄洪钟¹^,²

1. 电子科技大学机械与电气工程学院, 四川成都 611731
2. 电子科技大学系统可靠性与安全性研究中心, 四川成都 611731
3. 重庆大学机械传动国家重点实验室, 重庆 400044

收稿日期:2023-02-15 出版日期:2023-07-25 发布日期:2023-08-03
通讯作者: 李彦锋
作者简介:曾颖(1994—), 男, 博士研究生, 主要研究方向为电子产品可靠性建模、剩余寿命预测
李彦锋(1981—), 男, 教授, 博士研究生导师, 博士, 主要研究方向为系统可靠性建模
王弘毅(1995—), 男, 硕士, 主要研究方向为时变可靠性分析、结构可靠性优化
钱华明(1992—), 男, 讲师, 博士, 主要研究方向为时变可靠性分析、结构可靠性优化
黄洪钟(1963—), 男, 教授, 博士研究生导师, 博士, 主要研究方向为系统可靠性与安全性、剩余寿命预测
基金资助:
国家重点研发计划项目(2017YFB1301302)

Reliability analysis of industrial robot driver combining MRGP and PSO

Ying ZENG¹^,², Yanfeng LI¹^,²^,*, Hongyi WANG¹^,², Huaming QIAN²^,³, Hongzhong HUANG¹^,²

1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2. Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China
3. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China

Received:2023-02-15 Online:2023-07-25 Published:2023-08-03
Contact: Yanfeng LI

摘要/Abstract

摘要：

作为工业机器人的核心部件之一, 驱动器失效频发, 失效模式多样且具有一定相关性, 给工业机器人的正常工作带来了严峻挑战。同时, 工业机器人驱动器各失效模式的极限状态方程复杂, 甚至一些为隐函数, 这也造成了工业机器人驱动器可靠性建模的困难。为此, 本文引入多维响应高斯过程(multiple response Gaussian process, MRGP)模型来刻画驱动器内各失效模式间的相关性及其极限状态方程, 同时引入粒子群优化(particle swarm optimization, PSO)算法优化MRGP模型中的超参数, 结合主动学习策略, 对MRGP模型进行更新迭代, 直至其满足一定精度条件, 形成基于MRGP-PSO的工业机器人驱动器可靠性分析方法。最后开展相关算例分析, 验证了所提方法的有效性。

关键词: 工业机器人, 驱动器, 多维响应高斯过程, 粒子群优化算法, 可靠性分析

Abstract:

As one of the core components of the industrial robot, the failure of the driver is frequent, and the failure modes are various and have certain correlation, which brings severe challenges to the reliable operation of the industrial robot. Simultaneously, the limit state function of each failure mode in the industrial robot driver is very complex and even implicit, which further makes the reliability modeling of the industrial robot driver difficult. To solve this problem, multiple response Gaussian process (MRGP) model is introduced to describe the correlation and limit state function of each failure mode in the driver. Further, particle swarm optimization (PSO) algorithm is introduced to optimize the hyperparameters in the MRGP model. Besides, combined with the active learning strategy, the MRGP model is updated and iterated until it met certain accuracy conditions, and a reliability analysis method of industrial robot driver based on MRGP-PSO is proposed. Finally, relevant case studies are conducted, and the validity of the method is also verified.

Key words: industrial robot, driver, multiple response Gaussian process (MRGP), particle swarm optimization (PSO) algorithm, reliability analysis

中图分类号:

TP242.2

曾颖, 李彦锋, 王弘毅, 钱华明, 黄洪钟. 联合MRGP和PSO的工业机器人驱动器可靠性分析[J]. 系统工程与电子技术, 2023, 45(8): 2643-2650.

Ying ZENG, Yanfeng LI, Hongyi WANG, Huaming QIAN, Hongzhong HUANG. Reliability analysis of industrial robot driver combining MRGP and PSO[J]. Systems Engineering and Electronics, 2023, 45(8): 2643-2650.

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元器件失效		电路连接失效
失效部件	失效模式	失效部件	失效模式
电容	击穿(短路)、开路、漏液、电参数超差等	焊点	疲劳、断裂
电阻	开路、参数漂移等	引脚	断裂
电感	短路、开路	镀瞳孔	疲劳、断裂
二极管	短路、开路、阈值电阻老化	PCB电路板	断裂
IGBT	键合线断裂脱落、疲劳、芯片破坏	-	-

可靠性算法		设计点数量(初始点+g₁+g₂+g₃)	P_f (误差, 变异系数)
不同算法	学习函数	设计点数量(初始点+g₁+g₂+g₃)	P_f (误差, 变异系数)
MRGP-PSO	EFF	(8+24)×3	1.191×10^－3 (0%, 2.90%)
	U	(8+24)×3	1.191×10^－3 (0%, 2.90%)
	H	(8+23)×3	1.193×10^－3 (0.168%, 2.89%)
AK-SYS	EFF	8×3+15+17+0	1.190×10^－3 (0.084%, 2.90%)
	U	8×3+10+20+0	1.200×10^－3 (0.756%, 2.89%)
	H	8×3+5+12+0	1.785×10^－3 (49.87%, 2.36%)
原始MRGP	EFF	(8+32)×3	1.191×10^－3 (0%, 2.90%)
	U	(8+33)×3	1.191×10^－3 (0%, 2.90%)
	H	(8+31)×3	1.192×10^－3 (0.084%, 2.89%)
AK-MCS	EFF	(8+371)×3	1.190×10^－3 (0.084%, 2.90%)
	U	(8+329)×3	1.186×10^－3 (0.420%, 2.90%)
	H	(8+18)×3	8.26×10^－4 (30.6%, 3.48%)
MCS	-	3×10⁵	1.191×10^－3 (‘truth’, 2.90%)

随机变量	均值, 标准差
电容器容量/μF	10, 0.1
电压/V	24, 1
相对湿度	0.6, 0.1
纹波电流/mA	55, 4
电容表面积/cm²	5.2, 0.16
键合点高度/m	4.2×10^－4, 1×10^－8
键合点长度/m	4.5×10^－2, 1×10^－3
温度/K	100, 1
PCB厚度/m	2×10^－3, 5×10^－5
PTH孔半径/m	2.25×10^－4, 1×10^－6
PTH厚度/m	25×10^－6, 7×10^－8
PCB作用半径/m	1.025×10^－3, 1×10^－6

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联合MRGP和PSO的工业机器人驱动器可靠性分析

Reliability analysis of industrial robot driver combining MRGP and PSO

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