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A Comparison of Methods on Building Empirical Model of Milling Working Status Based on Vibration

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Advances in Engineering Research and Application (ICERA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 366))

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Abstract

This research presents different approaches of data analyzing and modelling to detect the milling status (i.e., milling/idling) based on the vibration of 3 axes. Data harvested during experiments, which represented in time domain, was transformed into frequency domain by Fast Fourier Transform (FFT) method in order to get more useful information and reduce noise. Neural network (NN) and Support Vector Machine (SVM) were two supervised machine learning and classification models which were used to train the data. The structure of the two models were selected by using Genetic Algorithm (GA) and Non-Dominated Sorting Genetic Algorithm – II (NSGA-II). A preferable recognition rate of 99.6% was achieved by Neural network with Genetic algorithm implemented.

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Acknowledgement

This research is funded by Thai Nguyen University of Technology, Viet Nam under grant number T2020-B39.

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Authors and Affiliations

  1. Thai Nguyen University of Technology, No. 666, 3/2 Street, Tich Luong Ward, Thai Nguyen City, Thai Nguyen Province, 25000, Vietnam

    Thanh-Dat Phan & The-Vinh Do

Authors
  1. Thanh-Dat Phan
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  2. The-Vinh Do
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Corresponding author

Correspondence to Thanh-Dat Phan .

Editor information

Editors and Affiliations

  1. Faculty of Electronic Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Duy Cuong Nguyen

  2. Faculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Ngoc Pi Vu

  3. Vietnam Association for Science Editing, Hanoi University of Science and Technology, Hanoi, Vietnam

    Banh Tien Long

  4. Institute for Automation and Systems Engineering, Ilmenau University of Technology (IUT), Ilmenau, Germany

    Horst Puta

  5. Department of Computer Science and Automation, Ilmenau University of Technology (IUT), Ilmenau, Germany

    Kai-Uwe Sattler

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Phan, TD., Do, TV. (2022). A Comparison of Methods on Building Empirical Model of Milling Working Status Based on Vibration. In: Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H., Sattler, KU. (eds) Advances in Engineering Research and Application. ICERA 2021. Lecture Notes in Networks and Systems, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-030-92574-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-92574-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92573-4

  • Online ISBN: 978-3-030-92574-1

  • eBook Packages: EngineeringEngineering (R0)

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