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Application of Principal Component Analysis and Decision Trees in Diagnostics of Cylindrical Plunge Grinding Process

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Advances in Manufacturing

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

In the grinding process, information about the process state may be derived from many measurement signals. As a result of these signals preprocessing, it is possible to obtain a high number of features of which only a part is related to the monitored process. This paper deals with the feature selection problem and modeling of relationships of selected features with grinding process states and grinding results. Firstly, time–frequency signal processing techniques are analyzed. Using the Hilbert-Huang transform, force, vibration, and acoustic emission signals are decomposed into separate intrinsic mode functions, and then the statistical features are extracted from these functions. Next, principal component analysis is used to select the most relevant features and to remove redundant data. Finally, decision trees are applied to additionally decrease the number of features and to model the grinding process. Using the proposed approach, it is possible to automate the feature selection process and to effectively diagnose the process state and predict final part quality parameters.

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Author information

Authors and Affiliations

  1. Institute of Machine Tools and Production Engineering, Technical University of Lodz, Lodz, Poland

    Pawel Lajmert, Malgorzata Sikora, Bogdan Kruszynski & Dariusz Ostrowski

Authors
  1. Pawel Lajmert
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  2. Malgorzata Sikora
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  3. Bogdan Kruszynski
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  4. Dariusz Ostrowski
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Corresponding author

Correspondence to Pawel Lajmert .

Editor information

Editors and Affiliations

  1. Poznan University of Technology, Poznań, Poland

    Adam Hamrol

  2. Poznan University of Technology, Poznań, Poland

    Olaf Ciszak

  3. Poznan University of Technology, Poznań, Poland

    Stanisław Legutko

  4. Poznan University of Technology, Poznań, Poland

    Mieczysław Jurczyk

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Lajmert, P., Sikora, M., Kruszynski, B., Ostrowski, D. (2018). Application of Principal Component Analysis and Decision Trees in Diagnostics of Cylindrical Plunge Grinding Process. In: Hamrol, A., Ciszak, O., Legutko, S., Jurczyk, M. (eds) Advances in Manufacturing. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-68619-6_68

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  • DOI: https://doi.org/10.1007/978-3-319-68619-6_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68618-9

  • Online ISBN: 978-3-319-68619-6

  • eBook Packages: EngineeringEngineering (R0)

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