Fuzzy evaluation of weld quality based on Matlab

被引：0
|
作者：
机构：
[1] Yao, Ping
[2] Xue, Jiaxiang
[3] Wang, Leilei
[4] Zhu, Qiang
来源：
Yao, P. (ypsunny@163.com) | 1600年 / 23期
关键词：
Evaluation results - Fuzzy evaluation - Fuzzy inference systems - Shape defect - Subjective evaluations - Three categories - Weld defects - Weld quality;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Based on standards and the expertise, 10 indicators such as crack, reinforcement and splash, etc. are selected for welds quality description. The indicators are classified into three categories: appearance defects, shape defects and weld defects, and corresponding fuzzy evaluation sets are designed. Membership functions of each indicator are determined with fuzzy inference system (FIS) editor in Matlab based on the actual welding experience. A two-stage fuzzy evaluation model for weld quality is established in Simulink. Finally, the model is tested through evaluating 7 different types of welds. The results show that fuzzy evaluation calculation can be simplified by combining Simulink with Matlab-FIS, and the evaluation results are more accurate and objective compared with the experts' subjective evaluation. Copyright: © 2014 Editorial Board of CHINA WELDING.
引用
收藏
相关论文
共 50 条
  • [1] Weld fatigue life assessment based on fuzzy quality evaluation model
    Li, Xiangwei
    Zhao, Wenzhong
    Zheng, Chengde
    Hanjie Xuebao/Transactions of the China Welding Institution, 2010, 31 (08): : 49 - 52
  • [2] Evaluation of Water Quality Using Fuzzy Neural Network Based on Matlab Software
    Wang, Qi
    Li, Jun
    Fu, Qingqing
    2011 3RD WORLD CONGRESS IN APPLIED COMPUTING, COMPUTER SCIENCE, AND COMPUTER ENGINEERING (ACC 2011), VOL 1, 2011, 1 : 334 - 337
  • [3] Fuzzy evaluation of railway environmental noise based on MATLAB
    Yan, Dongsong
    Huang, Yuanliang
    Zhongguo Tiedao Kexue/China Railway Science, 2011, 32 (03): : 126 - 130
  • [4] A vision-based weld quality evaluation system
    Barnett, RJ
    Cook, GE
    Strauss, AM
    Andersen, K
    Springfield, JF
    TRENDS IN WELDING RESEARCH, 1996, : 689 - 694
  • [5] A fuzzy pattern recognition based system for monitoring laser weld quality
    Park, H
    Rhee, S
    Kim, D
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2001, 12 (08) : 1318 - 1324
  • [6] Application of fuzzy control to the improvement of weld quality
    Xibei Gongye Daxue Xuebao, 2 (213-216):
  • [7] Robotic Welding Parameter Optimization Based on Weld Quality Evaluation
    Sterling, Tyler
    Chen, Heping
    2016 IEEE INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 2016, : 216 - 221
  • [8] Clustering quality evaluation based on fuzzy FCA
    Sassi Hidri, Minyar
    Touzi, Amel Grissa
    Ounelli, Habib
    DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2007, 4653 : 639 - +
  • [9] ULTRASONIC EVALUATION OF SPOT WELD QUALITY
    ROKHLIN, SI
    ADLER, L
    WELDING JOURNAL, 1985, 64 (07) : S191 - S200
  • [10] Study on the Evaluation and Operation Efficiency of Elevator Service Quality Based on MATLAB
    Fan, Sheng-Li
    PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON ECONOMIC MANAGEMENT AND TRADE COOPERATION, 2014, 107 : 141 - 145
12345