skip to main content
10.1145/3305275.3305299acmotherconferencesArticle/Chapter ViewAbstractPublication PagesisbdaiConference Proceedingsconference-collections
short-paper

Design method of rolling force sensor based on object orientation

Published: 29 December 2018 Publication History

Abstract

The object oriented method is used to design the rolling force sensor, which can be combined with the advantages of object oriented method for targeted and efficient design of the detection object. The steps of sensor design are abstracted as: object analysis, sensor design, measurement circuit design, packaging structure design and so on. This method can be reasonably designed in simulation. In this paper, through the design of rolling force sensor of continuous injection and continuous rolling equipment, it can greatly reduce redundant operation, save design time, rationally and efficiently use resources, and meet the actual demand of rolling force detection, which proves that it is better than traditional design methods.

References

[1]
Zhang E, Jiang Fan, Li Xiaoyuan. Classification Tree-Function Table Method and Its Application in Object-Oriented Mechanical Parts Design {J}.Mechanical Science and Technology, 1999 (6): 897--899.
[2]
Haixiang Tao, Shang Zhang, Cifa Chen (2018). A Design of Wsn Based Locking System. Acta Informatica Malaysia, 2(1): 04--06
[3]
Lin Ling. Application and Comparison of Structural Method and Object-Oriented Method in Modeling {J}.Electromechanical Technology, 2011, 34 (5): 26--30.
[4]
Xu Zhongxin, Wang Xiankui, Lei Tianyu, et al. Research and application of object-oriented knowledge representation in mechanical design expert system {J}.Journal of Zhengzhou Institute of Technology, 1996 (2): 1--6.
[5]
Chen Jiabin. Object oriented optimization design software {D}. Fujian Agriculture And Forestry University, 2006.
[6]
Luo Xu (2018). Study on PC Continuous Girder mechanical properties Based on Tendon Tensioning Pattern. Acta Mechanica Malaysia, 1(1): 08--11.
[7]
Hu Liangming, Xu Cheng, Wang Yongjuan, et al. {J}.Journal of Nanjing University of Science and Technology (Natural Science Edition), 2009, 33 (1): 104--107.
[8]
Cao Ji, Yuan Yong. Progress in object oriented finite element method {J}. mechanics quarterly, 2002, 23 (2): 241--248.

Index Terms

  1. Design method of rolling force sensor based on object orientation

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ISBDAI '18: Proceedings of the International Symposium on Big Data and Artificial Intelligence
    December 2018
    365 pages
    ISBN:9781450365703
    DOI:10.1145/3305275
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 December 2018

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Object oriented
    2. Process parameters
    3. Sensor design

    Qualifiers

    • Short-paper
    • Research
    • Refereed limited

    Conference

    ISBDAI '18

    Acceptance Rates

    ISBDAI '18 Paper Acceptance Rate 70 of 340 submissions, 21%;
    Overall Acceptance Rate 70 of 340 submissions, 21%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 33
      Total Downloads
    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 20 Jan 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media