• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2025, Vol. 61 ›› Issue (3): 77-90.doi: 10.3901/JME.2025.03.077

• 特邀专栏:人机联合认知赋能的高端装备设计、制造与运维 • 上一篇    

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人机协作的掘进机截割部故障率稳健性容差设计

崔凯越1, 洪兆溪1,2, 娄山河3, 闫炜煜1, 冯毅雄1,4, 谭建荣1   

  1. 1. 浙江大学流体动力基础件与机电系统全国重点实验室 杭州 310027;
    2. 浙江大学宁波科创中心 宁波 315100;
    3. 南洋理工大学机械与宇航工程学院 新加坡 637460 新加坡;
    4. 贵州大学省部共建公共大数据国家重点实验室 贵阳 550025
  • 收稿日期:2024-03-01 修回日期:2024-09-14 发布日期:2025-03-12
  • 作者简介:崔凯越,女,1998年出生,博士研究生。主要研究方向为复杂产品优化设计。E-mail:cuikaiyue@zju.edu.cn;洪兆溪(通信作者),女,1990年出生,博士,助理研究员。主要研究方向为智能设计与不确定性优化决策。E-mail:hzhx@zju.edu.cn;娄山河,男,1993年出生,博士后。主要研究方向为产品创新设计理论、设计认知。E-mail:loushanhe@zju.edu.cn;闫炜煜,男,1998年出生,博士研究生。主要研究方向为复杂产品结构设计。E-mail:12025056@zju.edu.cn;冯毅雄,男,1975年出生,博士,教授,博士研究生导师。主要研究方向为现代产品设计理论与方法。E-mail:fyxtv@zju.edu.cn;谭建荣,男,1954年出生,博士,教授,博士研究生导师,中国工程院院士。主要研究方向为CAX方法学、工程图学、企业信息化。E-mail:egi@zju.edu.cn
  • 基金资助:
    国家重点研发计划(2022YFB3402000)和国家自然科学基金(52130501,52105281)资助项目。

Robust Tolerance Design for Failure Rate of Roadheader Cutting Unit Based on Human-machine Collaboration

CUI Kaiyue1, HONG Zhaoxi1,2, LOU Shanhe3, YAN Weiyu1, FENG Yixiong1,4, TAN Jianrong1   

  1. 1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027;
    2. Ningbo Innovation Center, Zhejiang University, Ningbo 315100;
    3. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 637460 Singapore;
    4. State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025
  • Received:2024-03-01 Revised:2024-09-14 Published:2025-03-12

摘要: 掘进机截割部的稳健运行是掘进工作能够按时保质完成的必要条件,对截割部故障率进行稳健性容差设计是满足系统稳健运行的同时降低制造成本的有效措施。针对截割部故障率稳健性容差设计过程中故障数据样本量大、缺少相关稳健性优化数学模型、目标函数高维求解困难等问题,提出人机协作的截割部故障率稳健性容差设计方法。该方法以计算机的强大算力为支撑,首先利用人的区间模糊推理知识和最大似然估计方法对大量故障数据进行参数拟合,近似估计零部件故障率。其次基于数学目标规划知识和n重黎曼定积分设计了稳健性度量函数,构建高维高次稳健性优化数学模型。然后使用人群搜索算法和算法参数分析知识进行求解,获得了故障率容差的相对最优解。最后设计基于积分的多维波动模拟策略,得到整个截割部系统故障率的波动曲线。对比试验结果表明,所提出的人机协作的截割部故障率稳健性容差设计方法可以有效获得零部件故障率的扩展区间,并使截割部系统的稳健性能保持在较高水平。在人认知能力和计算机计算智能的联合推动下,该稳健性容差设计方法可经过适应性调整,进一步应用于其他可微的复杂系统。

关键词: 截割部故障率, 稳健性容差设计, 人机协作, 最大似然估计, 黎曼定积分, 人群搜索算法

Abstract: The robust operation of the roadheader cutting unit is a necessary condition for the timely and high-quality completion of excavation work. Robust tolerance design for failure rate of cutting unit is an effective measure to meet the robust operation while reducing manufacturing costs. Aiming at the problems of large sample size of fault data, lack of relevant robustness optimization mathematical models, and difficulty in solving high-dimensional objective functions, a robust tolerance method for failure rate of cutting unit based on human-machine collaboration is proposed. This method is supported by the strong computing power of computers. Firstly, the human interval fuzzy reasoning knowledge and maximum likelihood estimation method are employed to fit a significant number of failure data and obtain an approximate estimation of components' failure rates. Secondly, a robustness metric function is designed based on the mathematical goal programming knowledge and n-fold Riemannian integrals, and a high-dimensional and high-order robustness optimization mathematical model is constructed. Then, the seeker optimization algorithm and algorithm parameter analysis knowledge are utilized to solve the problem, and a relatively optimal solution of the failure rate tolerance is obtained. Finally, a multi-dimensional fluctuation simulation strategy based on integration is designed to obtain the fluctuation curve of the cutting unit’s failure rate. The comparison results show that the proposed robust tolerance design method for failure rate of cutting unit based on human-machine collaboration is capable of obtaining the extended ranges of components’ failure rates, and the cutting unit’s robust performance is maintained at a high level. With the combined advancements of human cognitive ability and computer computing intelligence, the proposed robust tolerance design method can be further applied to other complex systems through adaptive adjustments.

Key words: failure rate of cutting unit, robust tolerance design, human-machine collaboration, maximum likelihood estimation, Riemann integral, seeker optimization algorithm

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