A utilization method of big sensor data to detect tool anomaly in machining process

Yasuo Kondo, Sho Mizunoya, Satoshi Sakamoto, Kenji Yamaguchi, Tsuyoshi Fujita, Mitsugu Yamaguchi

    抄録

    The essential features and scale of sensor data was discussed to monitor the tool anomaly in the machining process from the pattern variation of large scale sensor data such as vibration and effective power. The cycle data, the time series sensor data collected with an acceleration or power sensor in one periodical machining of the given groove shape, had been measured periodically. In this study, the graphic pattern formed by overwriting the time series cycle data on a specific coordinate system was treated as the "big sensor data". The big data from the effective power sensor can stably respond to the cutting power changes and showed a strong possibility as a detecting device for tool anomaly such as abrasive wear and chipping. While the big data from the acceleration sensor only responded to a big event like the chattering vibration. The number of cycle data needed to generate the big sensor data also affected on the detection sensitivity for tool anomaly. It had been required a family of time series sensor data enough to represent the cutting power change as a visual graphic pattern.

    本文言語英語
    代表出版物のタイトルAdvanced Materials Research and Technologies
    出版者Trans Tech Publications Ltd
    ページ122-126
    ページ数5
    719
    ISBN(印刷物)9783035710052
    DOI
    ジャーナル掲載日出版済み - 2017
    イベントInternational Conference on Advanced Materials Research and Manufacturing Technologies, AMRMT 2016 - Singapore, シンガポール

    出版物シリーズ

    名前Key Engineering Materials
    719
    ISSN(印刷物)10139826

    その他

    その他International Conference on Advanced Materials Research and Manufacturing Technologies, AMRMT 2016
    シンガポール
    Singapore
    期間16/8/1816/8/20

    Fingerprint

    Sensors
    Time series
    Machining
    Big data
    Abrasion

    Keywords

      ASJC Scopus subject areas

      • Materials Science(all)
      • Mechanics of Materials
      • Mechanical Engineering

      これを引用

      Kondo, Y., Mizunoya, S., Sakamoto, S., Yamaguchi, K., Fujita, T., & Yamaguchi, M. (2017). A utilization method of big sensor data to detect tool anomaly in machining process. : Advanced Materials Research and Technologies. (巻 719, pp. 122-126). (Key Engineering Materials; 巻数 719). Trans Tech Publications Ltd. DOI: 10.4028/www.scientific.net/KEM.719.122

      A utilization method of big sensor data to detect tool anomaly in machining process. / Kondo, Yasuo; Mizunoya, Sho; Sakamoto, Satoshi; Yamaguchi, Kenji; Fujita, Tsuyoshi; Yamaguchi, Mitsugu.

      Advanced Materials Research and Technologies. 巻 719 Trans Tech Publications Ltd, 2017. p. 122-126 (Key Engineering Materials; 巻数 719).

      研究成果: 著書の章/レポート/会議のプロシーディングス会議での発言

      Kondo, Y, Mizunoya, S, Sakamoto, S, Yamaguchi, K, Fujita, T & Yamaguchi, M 2017, A utilization method of big sensor data to detect tool anomaly in machining process. : Advanced Materials Research and Technologies. 巻. 719, Key Engineering Materials, 巻. 719, Trans Tech Publications Ltd, pp. 122-126, International Conference on Advanced Materials Research and Manufacturing Technologies, AMRMT 2016, Singapore, シンガポール, 18-20 8月. DOI: 10.4028/www.scientific.net/KEM.719.122
      Kondo Y, Mizunoya S, Sakamoto S, Yamaguchi K, Fujita T, Yamaguchi M. A utilization method of big sensor data to detect tool anomaly in machining process. : Advanced Materials Research and Technologies. 巻 719. Trans Tech Publications Ltd. 2017. p. 122-126. (Key Engineering Materials). 利用可能場所, DOI: 10.4028/www.scientific.net/KEM.719.122

      Kondo, Yasuo; Mizunoya, Sho; Sakamoto, Satoshi; Yamaguchi, Kenji; Fujita, Tsuyoshi; Yamaguchi, Mitsugu / A utilization method of big sensor data to detect tool anomaly in machining process.

      Advanced Materials Research and Technologies. 巻 719 Trans Tech Publications Ltd, 2017. p. 122-126 (Key Engineering Materials; 巻数 719).

      研究成果: 著書の章/レポート/会議のプロシーディングス会議での発言

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      AU - Yamaguchi,Mitsugu

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