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Functional Series TARMA Models for Non-stationary Tool Vibration Signals Representation and Wear Estimation

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Structural Health Monitoring, Damage Detection & Mechatronics, Volume 7

Abstract

This article addresses the problem of tool wear estimation using vibration signals. Time dependent time series models are suitable for extraction of time varying dynamics embedded in the non-stationary signals. A version of non-stationary time series known as Functional Series Time dependent AutoRegressive Moving Average (FS-TARMA) is employed for estimation of tool vibration signals and identification of the dynamics of tool/holder system. The obtained models associated with different levels of tool wear are compared by using characteristic quantities calculated based on model parameters. In this method, called model parameter-based method wear is estimated using a feature that is a function of model parameter vector obtained from FS-TARMA models. The advantage of this method over the ARMA metric employed in a previous study is that it does not violate the non-stationarity assumption of signals. The results of this study demonstrate that the FS-TARMA models with model parameter-based method provides higher accuracy in wear estimation compared with ARMA counterpart and also FS-TARMA with ARMA metric.

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Acknowledgement

Authors would like to gratefully acknowledge the support provided by the TUBITAK (The Scientific and Technological Research Council of Turkey), Grant no: 2216 – Research Scholarship Program for International Researchers.

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Authors and Affiliations

  1. Mechanical Engineering Department, Middle East Technical University, 06800, Ankara, Turkey

    Behrang Hosseini Aghdam & Ender Cigeroglu

Authors
  1. Behrang Hosseini Aghdam
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  2. Ender Cigeroglu
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Correspondence to Ender Cigeroglu .

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Editors and Affiliations

  1. & State University, Virginia Polytechnic Institute, Blacksburg, Virginia, USA

    Alfred Wicks

  2. Department Mechanical Engineering, University of Massachusetts Lowell, Lowell, Massachusetts, USA

    Christopher Niezrecki

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Aghdam, B.H., Cigeroglu, E. (2016). Functional Series TARMA Models for Non-stationary Tool Vibration Signals Representation and Wear Estimation. In: Wicks, A., Niezrecki, C. (eds) Structural Health Monitoring, Damage Detection & Mechatronics, Volume 7. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29956-3_16

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  • DOI: https://doi.org/10.1007/978-3-319-29956-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29955-6

  • Online ISBN: 978-3-319-29956-3

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