勤益科大機構典藏:Item 987654321/7037
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 2928/5721 (51%)
Visitors : 387181      Online Users : 156
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/7037


    Title: Application of the Extension Neural Network-Type 3 to Defect Recognition of Car Engine
    Authors: 王孟輝
    Contributors: 電機工程(學)系
    Date: 2012-01
    Issue Date: 2018-01-07 09:35:55 (UTC+8)
    Abstract: The recognized hidden defects in a car engine is the most important work for a maintain engineer, so they can regulate the engines to be safe and improve the reliability of automobile systems. In this paper, we will present a novel defect recognized method based on the extension neural network type-3 (ENN-3) and apply this method in the defect fault recognition of a practical car engine. The proposed recognized method has been tested on the practical tested records of the Nissan CEFIRO 2.0 engine and also compared with other traditional classified methods. Experimental results are of great interest for the hidden defect recognition of car engines.
    Relation: ICIC Express Letters
    Appears in Collections:[Department of Electrical Engineering] 【電機工程系所】期刊論文

    Files in This Item:

    There are no files associated with this item.



    All items in NCUTIR are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback