+高级检索
首页 > 过刊浏览>2016年第39卷第6期 >111-117. DOI:10.11835/j.issn.1000-582X.2016.06.014
PDF HTML阅读 XML下载 导出引用 引用提醒
Petri网逆网在主轴故障诊断中的应用
作者:
基金项目:

教育部“春晖计划”（Z2014140）；吉林省科技发展计划项目（20140520126JH）；吉林省教育厅十二五科学技术研究项目资助（2015-80）。


Inverse Petri net and its application to spindle fault diagnosis
Author:
  • 摘要
    • | |
  • 访问统计
    • |
  • 参考文献 [16]
    • |
  • 相似文献 [20]
    • | | |
  • 文章评论
    摘要:

    为了能够快速寻找主轴故障原因，采用Petri网逆网对数控机床主轴进行故障诊断。建立petri网逆网模型构建数控机床主轴关联故障可达图，深入系统分析主轴故障的各个子系统、故障模式和故障根本原因，并对故障模式和故障原因进行关联性分析；分析状态转移可达集，掌握主轴关联故障的传递过程，寻找导致主轴故障的根本原因；并以数控机床主轴噪声大为例描述数控机床主轴Petri网逆网故障诊断过程。主轴关联故障的Petri网逆网研究，有助于迅速进行主轴故障诊断与维修，缩短修复时间，进一步提高主轴的可用度。

    Abstract:

    In order to quickly find the cause of the spindle failure, inverse Petri net was adopted to diagnose the fault of CNC(computerized numerical control) machine tool spindle. An inverse Petri net model of related failure for CNC machine tool spindle was established to obtain the inverse Petri net reachability graph of the spindle. And the failure of subsystems, failure modes and failure causes can be thorough analyzed. In addition, the relevance of fault modes and fault causes can be analyzed by the reachability graph. By analyzing state transferring reachable set, we can grasp the transmission process of spindle related failure and get the root cause of failure. By taking the loud noise of spindle as an example, its fault diagnosis process with inverse Petri net was described. Studying inverse Petri net of spindle related failure can help to diagnosis and repair the spindle quickly, shorten the repair time and improve the availability of the spindle.

    参考文献
    [1] 邓三鹏,徐小力,张建新,等.基于噪声小波包络谱的数控机床主轴故障诊断研究[J].机床与液压,2009,37(12):219-221. DENG Sanpeng, XU Xiaoli, ZHANG Jianxin, et al. Spindle fault diagnosis based on wavelet and envelope anal-ysis[J]. Machine Tool & Hydraulics,2009,37(12):219-221.(in Chinese)
    [2] 于捷,贾亚洲.数控车床故障模式影响与致命性分析[J].哈尔滨工业大学学报,2005,37(12):1725-1727. YU Jie, JIA Yazhou. Failure mode effect and criticality analysis on certain serial CNC lathes[J]. Journal of Harbin Institute of Technology,2005,37(12):1725-1727.(in Chinese)
    [3] Wang Y, Deng C, Wu J, et al. A corrective maintenance scheme for engineering equipment[J]. Engineering Failure Analysis,2014,36:269-283.
    [4] Purba J H, Tjahyani D T S, Ekariansyah A S, et al. Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty[J].Annals of Nuclear Energy,2015,85:1189-1199.
    [5] Liu P, Yang L, Gao Z, et al. Fault tree analysis combined with quantitative analysis for high-speed railway accid-ents[J]. Safety Science,2015, 79:344-357.
    [6] 董立立,朱煜,黄道,等. 灰关联分析及其在装备故障诊断中的应用[J]. 华东理工大学学报(自然科学版),2008,38(4):563-597. DONG Lili, ZHU Yu, HUANG Dao, et al. Grey relevancy analysis and its application to equipment fault diagnosis[J]. Journal of East China University of Science and Technology(Natural Science Edition),2008,38(4):563-597.(in Chinese)
    [7] 刘晨曦,陈南,杨佳宁.基于多态故障树的伺服刀架可靠性分析[J].东南大学学报(自然科学版),2014,44(3):538-543. LIU Chenxi, CHEN Nan, YANG Jianing. Reliability analysis of servo turret based on multi-state fault tree[J]. Journal of Southeast University (Natural Science Edition),2014,44(3):538-543.(in Chinese)
    [8] Whiteley M, Dunnett S, Jackson L. Failure mode and effect analysis, and fault tree analysis of polymer electrolyte membrane fuel cells[J].International Journal of Hydrogen Energy. 2016,41(2):1187-1202.
    [9] Renganathan K, Bhaska V. Modeling, analysis and performance evaluation for fault diagnosis and Fault Tolerant Control in bottle-filling plant modeled using Hybrid Petri nets[J]. Applied Mathematical Modelling,2013,37:4842-4859.
    [10] 王志琼.电主轴故障分析及可靠性增长技术研究[D]. 长春:吉林大学,2012. WANG ZhiQiong. The fault analysis and reliability growth technique study for electro-spindle[D]. Changchun:Jilin University,2012.(in Chinese)
    [11] Cheng H, He Z, Wang Q, et al. Fault diagnosis method based on Petri nets considering service feature of information source devices[J]. Computers and Electrical Engineering,2015,46:1-13.
    [12] Huea G S, Atwwod J W. The use of Petri nets to analyze coherent fault trees[J].IEEE Transaction on Reliability,1988,37(5):469-474.
    [13] Renganathan K, Bhaskar V C. An observer based approach for achieving fault diagnosis and fault tolerant control of systems modeled as hybrid Petri nets[J]. ISA Transactions,2011,50:443-453.
    [14] Liu H C, Lin Q L, Ren M L, et al. Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets[J]. Computers & Industrial Engineering,2013,66(4):899-908.
    [15] 汪惠芬,梁光夏,刘庭煜,等.基于改进模糊故障Petri网的复杂系统故障诊断与状态评价[J]. 计算机集成制造系统,2012,19(12):3049-3061. WANG Huifen, LIANG Guangxia, LIU Tingyu, et al. Machinery failure diagnosis and condition evaluation for complex system based on improved fuzzy fault Petri net[J]. Computer Integrated Manufacturing Systems,2012,19(12):3049-3061.(in Chinese)
    [16] 熊国江,石东源.容错Petri网电网故障诊断改进模型[J]. 华中科技大学学报(自然科学版),2013,41(1):11-15. XIONG Guojiang, SHI Dongyuan. Improved fault-tolerant petri nets for fault-diagnosis power grids[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition),2013,41(1):11-15.(in Chinese)
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

谷东伟,张学文,王志琼,申桂香,张英芝. Petri网逆网在主轴故障诊断中的应用[J].重庆大学学报,2016,39(6):111-117.

复制
分享
文章指标
  • 点击次数:966
  • 下载次数: 976
  • HTML阅读次数: 600
  • 引用次数: 0
历史
  • 收稿日期:2016-08-13
  • 在线发布日期: 2016-12-12
文章二维码
您是第11883390 位访问者
主管单位：中华人民共和国教育部
主办单位：重庆大学
地址：重庆市沙坪坝正街174号
电话：
重庆大学学报 ® 2025 版权所有