Application of adaptive network based fuzzy inference system for model reconstruction in reverse engineering

被引:0
|
作者
Ma Zi [1 ]
Xu Huipu [1 ]
机构
[1] Dalian Maritime Univ, Automat Res Ctr, Dalian 116026, Peoples R China
来源
PROCEEDINGS OF THE 24TH CHINESE CONTROL CONFERENCE, VOLS 1 AND 2 | 2005年
关键词
adaptive network; Fuzzy Inference System; reverse engineering;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Combining the both of technologies, fuzzy neural network and laser Surface data measurement., a novel model reconstruction methodology is presented. This model reconstruction scheme includes two main parts, One is Surface data measurement system, and the other one is model reconstruction algorithm. The surface data measurement system consists of a vision system with a smart laser camera and a PC computer, the system is developed to measure data for freeform Surface with complex shape. Using an Adaptive Network based Fuzzy Inference System (ANFIS), the model reconstruction algorithm is designed. For demonstrating the effectiveness of the presented scheme, the surface data of ail existing part are measured, the point cloud data with good accuracy are used to train the ANFIS so that the network model is obtained. From comparing the output of network model data with the sample data, it can be found that the trained network model can match the real surface very well.
引用
收藏
页码:1077 / 1081
页数:5
相关论文
共 50 条
  • [21] Image Interpolation Based on Adaptive Neuro-Fuzzy Inference System
    Maleki, Shiva Aghapour
    Tinati, Mohammad Ali
    Tazehkand, Behzad Mozaffari
    2019 3RD INTERNATIONAL CONFERENCE ON IMAGING, SIGNAL PROCESSING AND COMMUNICATION (ICISPC), 2019, : 78 - 84
  • [22] Research on Model reconstruction and NC machining for Blade based on reverse engineering
    Zhou, Yu Qing
    MANUFACTURING ENGINEERING AND AUTOMATION II, PTS 1-3, 2012, 591-593 : 670 - 673
  • [23] Adaptive-network-based fuzzy inference system models for input resistance computation of circular microstrip antennas
    Guney, K.
    Sarikaya, N.
    MICROWAVE AND OPTICAL TECHNOLOGY LETTERS, 2008, 50 (05) : 1253 - 1261
  • [24] Interpretation of a model footing response through an adaptive neural fuzzy inference system
    Provenzano, P
    Ferlisi, S
    Musso, A
    COMPUTERS AND GEOTECHNICS, 2004, 31 (03) : 251 - 266
  • [25] A Neural Network Approach to Edge Detection using Adaptive Neuro - Fuzzy Inference System
    Anwar, Shamama
    Raj, Sugandh
    2014 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2014, : 2432 - 2435
  • [26] Adaptive Neuro Fuzzy Inference System Based Obstacle Avoidance System for Autonomous Vehicle
    Karthikeyan, M.
    Sathiamoorthy, S.
    Vasudevan, M.
    INNOVATIVE DATA COMMUNICATION TECHNOLOGIES AND APPLICATION, 2020, 46 : 118 - 126
  • [27] An Application Study of Transition Surface Reconstruction in Reverse Engineering
    LU Jing-ping
    College of Mechanical Engineering
    ComputerAidedDrafting,DesignandManufacturing, 2004, DesignandManufacturing.2004 (01) : 24 - 29
  • [28] AN ONLINE ENGINEERING EDUCATION FRAMEWORK BASED ON THE PREDICTORS OF ADAPTABILITY AND FUZZY INFERENCE SYSTEM
    Corpuz, Ralph Sherwin A.
    INTERNATIONAL JOURNAL ON INFORMATION TECHNOLOGIES AND SECURITY, 2024, 16 (04): : 49 - 60
  • [29] Comparative evaluation of adaptive fuzzy inference system and adaptive neuro-fuzzy inference system for mandatory lane changing decisions on freeways
    Vechione, Matthew
    Cheu, Ruey Long
    JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 26 (06) : 746 - 760
  • [30] CAD Software Tools Employed in a Reverse Engineering Application: a Fan Propeller Model Reconstruction
    Falheiro, Mizael S.
    Diniz, Laurivan S.
    Lima Jr, Jose C.
    Najafabadi, Hossein R.
    Goto, Tiago G.
    Tsuzuki, Marcos S. G.
    2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON), 2021, : 672 - 678