Development of chatter vibration detection utilizing disturbance observer (2nd report) - An assorted chatter detection combining moving variance and moving fourier transform algorithms

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Chatter vibration deteriorates the machining accuracy and shortens the tool life. Thus, In-process monitoring methods have been proposed by using additional sensors such as dynamometers and acceleration sensors. However, introducing additional sensors leads to high cost and reduction of machine-tool stiffness. To solve these problems, a sensor-less monitoring method applying the disturbance observer theory was proposed in our previous research which has experimentally shown that chatter vibration can be detected only from the servo information in milling. For further demand, because chatter vibration can be classified into self-excited vibration and forced vibration, an assorted detection method is required. In this study, we propose a novel frequency analysis method combining moving variance and moving Fourier transform algorithms, which can obtain the power spectrum density of each chatter vibration type separately with small computational load. The validity of the proposed method is evaluated through milling tests with different rotational speeds.

Original languageEnglish
Pages (from-to)692-698
Number of pages7
JournalSeimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering
Volume81
Issue number7
DOIs
Publication statusPublished - 2015 Jul 1

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Fourier transforms
Sensors
Dynamometers
Process monitoring
Power spectrum
Machine tools
Machining
Stiffness
Monitoring
Costs

Keywords

  • Chatter
  • Disturbance observer
  • Milling
  • Process monitoring
  • Sliding fourier transform

ASJC Scopus subject areas

  • Mechanical Engineering

Cite this

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title = "Development of chatter vibration detection utilizing disturbance observer (2nd report) - An assorted chatter detection combining moving variance and moving fourier transform algorithms",
abstract = "Chatter vibration deteriorates the machining accuracy and shortens the tool life. Thus, In-process monitoring methods have been proposed by using additional sensors such as dynamometers and acceleration sensors. However, introducing additional sensors leads to high cost and reduction of machine-tool stiffness. To solve these problems, a sensor-less monitoring method applying the disturbance observer theory was proposed in our previous research which has experimentally shown that chatter vibration can be detected only from the servo information in milling. For further demand, because chatter vibration can be classified into self-excited vibration and forced vibration, an assorted detection method is required. In this study, we propose a novel frequency analysis method combining moving variance and moving Fourier transform algorithms, which can obtain the power spectrum density of each chatter vibration type separately with small computational load. The validity of the proposed method is evaluated through milling tests with different rotational speeds.",
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author = "Ryo Koike and Yasuhiro Kakinuma and Tojiro Aoyama and Kouhei Ohnishi",
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AU - Ohnishi, Kouhei

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