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access icon openaccess Evaluation method of spindle performance degradation based on VMD and random forests

  • Author(s): Pangshi Wei 1, 2  and  Hongjun Wang 1, 2, 3
    • View affiliations
  • Source: Volume 2019, Issue 23, December 2019, p. 8862 – 8866
    DOI:  10.1049/joe.2018.9127 , Online ISSN 2051-3305
This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 15/10/2018, Accepted 08/01/2019, Published 25/03/2019

As one of the core components of the machine tool, the reliability of spindle is very important for improving machine tool quality. To effectively evaluate the performance degradation degree of the spindle, a method of degradation evaluation of the spindle performance based on variational mode decomposition (VMD) and random forests (RFs) was proposed. Firstly, VMD is used to process the current signal to obtain several modal components. Then, the time domain and frequency domain features of each modes component are calculated as eigenvalues. Finally, the RFs algorithm is used to classify the eigenvalues. The experimental results show that VMD can decompose the signal better and avoid the phenomenon of the modal mixture. The combination of VMD and RFs can accurately and effectively evaluate the performance degradation of the spindle.

Inspec keywords: eigenvalues and eigenfunctions; vibrations; condition monitoring; frequency-domain analysis; machine tools; time-domain analysis; machine tool spindles; mechanical engineering computing; feature extraction

Other keywords: core components; performance degradation degree; machine tool quality; modal components; spindle performance degradation; variational mode decomposition; time domain; frequency domain features; degradation evaluation; modes component; random forests; VMD; eigenvalues; RF algorithm

Subjects: Vibrations and shock waves (mechanical engineering); Statistics; Mathematical analysis; Other topics in statistics; Maintenance and reliability; Mechanical engineering applications of IT; Civil and mechanical engineering computing; Signal processing and detection; Production equipment; Machining; Mathematical analysis; Inspection and quality control; Other topics in statistics; Mathematical analysis; Digital signal processing

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