Please wait a minute...
工程设计学报
工程设计学报  2018, Vol. 25 Issue (6): 630-638,710    DOI: 10.3785/j.issn.1006-754X.2018.06.002
设计理论与方法学     
基于元动作单元的数控机床故障分级决策方法
李松涛1, 刘英1, 冉琰1, 柯磊1, 陈辉2
1. 重庆大学 机械传动国家重点实验室, 重庆 400044;
2. 四川华都核设备制造有限公司, 四川 都江堰 611800
Fault classification decision method of CNC machine tool based on meta-action unit
LI Song-tao1, LIU Ying1, RAN Yan1, KE Lei1, CHEN Hui2
1. State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China;
2. Sichuan Huadu Nuclear Equipment Manufacturing Co., Ltd., Dujiangyan 611800, China
 全文: PDF(1089 KB)   HTML
摘要：

为快速、准确地判断数控机床故障等级，避免出现花大代价处理次要故障，而关键故障却被忽略的情况，提出了一种以元动作单元为分析主体的数控机床故障分级决策方法。首先，为细化数控机床故障分析的粒度，使得分析过程更加简便，从系统功能分解的角度将数控机床按照“功能（function）-运动（motion）-动作（action）”逐层分解直至元动作层。其次，通过对分解过程进行分析，给出了元动作单元概念模型，明确了一个标准元动作单元需要包含的3类要素。然后，从动作的层面全面分析并总结元动作单元的故障模式类型。接着，定义了元动作单元故障模式的3个等级，按照评价指标对数控机床故障模式进行评价，再通过灰色聚类理论分析故障模式量化评价值，利用所得出的聚类结果建立了故障模式分级的原始决策表，随后通过粗糙集理论对原始决策表进行知识约简以使决策规则进一步简化，最终形成了一种能够快速、准确确定故障模式等级的决策方法。最后，通过对某数控机床齿条移动元动作单元的分析，验证了所提方法的合理性与有效性。实例分析结果表明使用该方法能够快速、准确地确定数控机床的故障模式等级，提高了决策效率，所得结论更加明确且具有针对性，可为后续的维修过程控制提供依据。研究结果能给相关企业确定数控机床故障等级提供有效指导，一定程度上优化企业维修资源的配置。
关键词： 元动作单元;  故障分级;  灰色聚类决策;  粗糙集;  知识约简    
Abstract:

In order to quickly and accurately determine the fault classification of CNC (computerized numerical control) machine tools, a fault classification decision method based on the meta-action unit was proposed, which could avoid costly handing of minor faults while key faults were ignored. Firstly, to refine the granularity of fault analysis of CNC machine tools, which made analysis process more convenient, according to "function-motion-action", the CNC machine tool was decomposed to the meta-action layer by layer from the point of view of system functional decomposition. Secondly, the concept model of the meta-action unit was elaborated by analyzing the decomposition process and three elements of a standard meta-action unit were defined.Thirdly, fault modes of the meta-action unit were analyzed and summarized comprehensively. Fourthly, three levels of fault modes of meta-action unit were defined. According to the evaluation index, the fault modes of CNC machine tools were evaluated, and then the grey clustering theory was applied to analyze the quantified evaluation value of the fault modes, and the original decision table of fault mode classification was established based on the clustering results obtained. After that the knowledge reduction of the original decision table made the decision rules further simplified through the rough set theory, ultimately a fast and accurate fault classification decision method was formed. Finally, the rationality and effectiveness of the proposed method was demonstrated by an example analysis of the rack movement meta-action unit in a certain CNC machine tool. The example analysis result indicated that the fault mode levels of CNC machine tools could be determined quickly and accurately so as to improve decision efficiency by this method, the obtained conclusion was more clear and pertinent, which could provide the basis for the subsequent maintenance process control. The research results can provide useful guidance for relevant enterprises to determine the fault levels of CNC machine tools, and to optimjze the allocation of enterprise maintenance resources to some extent.
Key words: meta-action unit    fault classification    grey cluster decision    rough set    knowledge reduction
收稿日期: 2018-04-03 出版日期: 2018-12-28
CLC:  TH165  
基金资助:

国家自然科学基金资助项目（51705048）；国家科技重大专项资金资助项目（2015ZX04003-003，2016ZX04004-005）
通讯作者: 冉琰(1989-),女,重庆潼南人,讲师,博士,从事可靠性技术、现代质量工程技术研究,E-mail:ranyan@cqu.edu.cn     E-mail: ranyan@cqu.edu.cn
作者简介: 李松涛(1994-),男,重庆涪陵人,硕士生,从事可靠性技术研究,E-mail:lisongtao94@163.com,https://orcid.org/0000-0002-5251-0673
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　
李松涛
刘英
冉琰
柯磊
陈辉

引用本文:

李松涛, 刘英, 冉琰, 柯磊, 陈辉. 基于元动作单元的数控机床故障分级决策方法[J]. 工程设计学报, 2018, 25(6): 630-638,710.

LI Song-tao, LIU Ying, RAN Yan, KE Lei, CHEN Hui. Fault classification decision method of CNC machine tool based on meta-action unit[J]. Chinese Journal of Engineering Design, 2018, 25(6): 630-638,710.

链接本文:

https://www.zjujournals.com/gcsjxb/CN/10.3785/j.issn.1006-754X.2018.06.002    或    https://www.zjujournals.com/gcsjxb/CN/Y2018/V25/I6/630

[1] 陈政平,付桂翠,赵幼虎.改进的风险优先数(RPN)分析方法[J].北京航空航天大学学报,2011,37(11):1395-1399. CHEN Zheng-ping, FU Gui-cui, ZHAO You-hu. Improved analysis method of risk priority number[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(11):1395-1399.
[2] 王志琼,申桂香,张英芝,等.基于数据包络的松拉刀机构故障模式风险分析[J].华南理工大学学报(自然科学版),2015,43(7):142-146. WANG Zhi-qiong, SHEN Gui-xiang, ZHANG Ying-zhi, et al. Risk analysis of failure mode of clamping and releasing tool based on data envelopment analysis[J]. Journal of South China University of Technology (Natural Science Edition), 2015, 43(7):142-146.
[3] SHI Jun-li, WANG Ya-jun, JIN Hai-hua, et al. A modified method for risk evaluation in failure mode and effects analysis[J]. Journal of Applied Science and Engineering, 2016, 19:177-186.
[4] 王浩伦,徐翔斌,甘卫华.基于三角模糊软集的FMEA风险评估方法[J].计算机集成制造系统,2015,21(11):3054-3062. WANG Hao-lun, XU Xiang-bin, GAN Wei-hua. Risk evaluation method in FMEA based on triangular fuzzy soft set[J]. Computer Integrated Manufacturing Systems, 2015, 21(11):3054-3062.
[5] 耿秀丽,张永政.基于犹豫模糊集的改进FMEA风险评估方法[J].计算机集成制造系统,2017,23(2):340-348. GENG Xiu-li, ZHANG Yong-zheng. Improved FMEA approach for risk evaluation based on hesitant fuzzy set[J]. Computer Integrated Manufacturing Systems, 2017, 23(2):340-348.
[6] ZHOU Q, THAI V V. Fuzzy andgrey theories in failure mode and effect analysis for tanker equipment failure prediction[J]. Safety Science, 2016, 83:74-79.
[7] KUTLU A C, EKMEKÇIO LU M. Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP[J]. Expert Systems with Applications, 2012, 39(1):61-67.
[8] CERTA A, HOPPS F, INGHILLERI R, et al. A Dempster-Shafer theory-based approach to the Failure Mode, Effects and Criticality Analysis (FMECA) under epistemic uncertainty:application to the propulsion system of a fishing vessel[J]. Reliability Engineering and System Safety, 2017, 159:69-79.
[9] BOZDAG E, ASAN U, SOYER A, et al. Risk prioritization in failure mode and effects analysis using interval type-2 fuzzy stes[J]. Expert Systems with Applications, 2015, 42(8):4000-4015.
[10] 王锦妮,火建卫.定量危害性矩阵分析方法研究[J].航空工程进展,2016,7(1):70-77. WANG Jin-ni, HUO Jian-wei. Research on quantitative criticality matrix analysis method[J]. Advances in Aeronautical Science and Engineering, 2016, 7(1):70-77.
[11] 王波,唐晓青,耿如军.机械产品装配关系建模[J].北京航空航天大学学报,2010,36(1):71-76. WANG Bo, TANG Xiao-qing, GENG Ru-jun. Modeling for assembly structure in mechanical product[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(1):71-76.
[12] 陈循,陶俊勇,张春华.可靠性强化试验与加速寿命试验综述[J].国防科技大学学报,2002,24(4):29-32. CHEN Xun, TAO Jun-yong, ZHANG Chun-hua. Reliability enhancement testing and accelerated life testing:an introductory review[J]. Journal of National University of Defense Technology, 2002, 24(4):29-32.
[13] 张根保,孙恒,范秀君.数控机床基于FMA的功能分解与可靠性分析[J].机械科学与技术,2012,31(4):528-533. ZHANG Gen-bao, SUN Heng, FAN Xiu-jun. Function decomposition and reliability analysis of CNC machine using function-motion-action[J]. Mechanical Science and Technology for Aerospace Engineering, 2012, 31(4):528-533.
[14] RAN Yan, ZHANG Gen-bao, ZHANG Lian. Quality characteristic association analysis of computer numerical control machine tool based on meta-action assembly unit[J]. Advances in Mechanical Engineering, 2016, 8(1):1-10.
[15] 周庆法.基于元动作单元的核换料机可靠性分析与控制技术研究[D].重庆:重庆大学机械工程学院,2017:27-28. ZHOU Qing-fa. Research on reliability analysis and control technology of nuclear refueling machine based on meta-action unit[D]. Chongqing:Chongqing University, College of Mechanical Engineering, 2017:27-28.
[16] 邓聚龙.灰色系统基本方法[M].武汉:华中科技大学出版社,2005:2-4. DENG Ju-long. The primary methods of grey system theory[M]. Wuhan:Huazhong University of Science and Technology Press, 2005:2-4.
[17] 徐泽水.部分权重信息下多目标决策方法研究[J].系统工程理论与实践,2002,22(1):43-47. XU Ze-shui. On method for multi-objective decision-making with partial weight information[J]. Systems Engineering Theory and Practice, 2002, 22(1):43-47.
[18] 吕宏辉,钟珞,夏红霞.灰色系统与神经网络融合技术探索[J].微机发展,2000(3):3-5. LÜ Hong-hui, ZHONG Luo, XIA Hong-xia. Exploring in fusion technology of grey system and neural networks[J]. Microcomputer Development, 2000(3):3-5.
[1] 魏巍, 林载盛. 基于RIR-MOO的定制产品优化设计方法研究[J]. 工程设计学报, 2020, 27(5): 592-599.
[2] 司光耀, 王凯, 李文强, 李彦, 牟亮. 基于大数据和粗糙集的产品需求分析方法研究[J]. 工程设计学报, 2016, 23(6): 521-529.
[3] 陈建宏, 周汉陵, 邬书良, 杨珊, 于凤玲. 优势变精度粗糙集构建采矿方案评价体系的研究[J]. 工程设计学报, 2013, 20(6): 453-458.
[4] 张 莉. 缝制设备协同开发过程中冲突消解方法的研究[J]. 工程设计学报, 2010, 17(2): 98-101.