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Realization of a force inspection system with skilled inspector-like sensing ability

Research Project

Project/Area Number 12650246
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent mechanics/Mechanical systems
Research InstitutionFukui University

Principal Investigator

YAMADA Yasuhiro  FUKUI UNIVERSITY DEPT. OF MECHANICAL ENGINEERING, ASSOCIATE PROF., 工学部, 助教授 (40220412)

Co-Investigator(Kenkyū-buntansha) MASUDA Masanobu  INDUSTRIAL TECHNOLOGY CENTER OF FUKUI PREFECTURE, RESEARCHER, 機械電子部, 主任研究員
KOMURA Yoshiaki  Fukui University DEPT. OF MECHANICAL ENGINEERING, PROF., 工学部, 教授 (00020214)
Project Period (FY) 2000 – 2001
Project Status Completed (Fiscal Year 2001)
Budget Amount *help
¥2,600,000 (Direct Cost: ¥2,600,000)
Fiscal Year 2001: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2000: ¥1,500,000 (Direct Cost: ¥1,500,000)
KeywordsInspection / Neural Network / Wavelet Transform / Regression analysis / Reaction Force / 計算機援用検査 / 統計手法 / 力覚検査 / ニューラルネット / ウェーブレット
Research Abstract

This paper looks at a system for inspection of the quality ofa probe's reaction force characteristics. This system, until now considered difficult to realize, automates the inspection method utilizing the touching of an inspector's finger.
1. Wavelet transformation and a neural network (NN) approach is applied to the system for probes to learn an inspector's finger judgment. We provide an input layer of a NN with thirty-three nodes corresponding to a time series of reaction forces of a probe and an output layer with one node corresponding to ajudgment ; being one of non-defective, defective, or unable to judge. From experimental results, the effectiveness of the system has been clarified. The inspection results of skilled inspectors were learned by the proposed wavelet-neural network system.
2. Regression analysis and a NN approach is applied to the system for probes to learn an inspector's finger judgment. We provide an input layer of a NN with forty-three nodes corresponding to a time series difference between reaction forces of the test probe and the best quality probe, and an output layer with three nodes corresponding to a judgment. From experimental results, the effectiveness of the system has been clarified. The inspection results of skilled inspectors were learned by the proposed regression analysis -neural network system.
3. A graphical presentation system is proposed. All performances of the regression analysis-neural network system are displayed in the graphical presentation system. The graphical presentation syste*m supports unskilled inspector' s training in inspection skills.
In time better trained neural networks will further improve the speed and accuracy of probe inspections, thereby reducing inspection costs.

Report

(3 results)
  • 2001 Annual Research Report   Final Research Report Summary
  • 2000 Annual Research Report
  • Research Products

    (6 results)

All Other

All Publications (6 results)

  • [Publications] 山田泰弘, 古村義彰, 宮西俊二, 大久保雄一: "ニューラルネットワークによる力覚検査に関する研究"日本設計工学会北陸支部平成12年度研究発表論文集. 53-56 (2000)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2001 Final Research Report Summary
  • [Publications] Yasuhiro Yamada, Yoshiaki Komura, Masanobu Masuda, Yuuichi Ookubo: "Reaction Force Inspection System Using Wavelet Transforms and Neural Networks"Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington D.C... May 2002 (in press). (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2001 Final Research Report Summary
  • [Publications] Yasuhiro Yamada, Yoshiaki Komura, Syunji Miyanishi, Yuuichi Ookubo: "Force Sense Inspection* System Using Neural Network"Praeedings of the JSDE Hokuriku-division. 53-56 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2001 Final Research Report Summary
  • [Publications] Yasuhiro Yairiada, Yoshiaki Komura, Masanobu Masuda, Yuuichi Ookubo: "Reaction Force Inspection System Using Wavelet Transforms and Neural Networks"Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Wihington D.C.. (in press). (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2001 Final Research Report Summary
  • [Publications] Yasuhiro Yamada, Yoshiaki Komura, Masanobu Masuda, Yuuichi Ookubo: "Reaction Force Inspection System Using Wavelet Transforms and Neural Networks"Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington D. C., May 2002. (to appear). (2002)

    • Related Report
      2001 Annual Research Report
  • [Publications] 山田泰弘: "ニューラルネットワークによる力覚検査に関する研究"日本設計工学会北陸支部平成12年度研究発表論文集. 53-56 (2000)

    • Related Report
      2000 Annual Research Report

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Published: 2000-04-01   Modified: 2016-04-21  

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