Acta Mechanica Slovaca 2022, 26(4):38-43 | DOI: 10.21496/ams.2023.009

Device for Failure Detection on Production Machines

Radka Jírová1, Lubomír Pešík1, Martin Sturm2, Anett Maria Kupka1
1 Technical University of Liberec, Faculty of Mechanical Engineering, Studentska 2, 460 01 Liberec, Czech Republic
2 University of Applied Sciences Zittau/Görlitz, Faculty of Mechanical Engineering, Theodor-Korner-Allee 16, 02763 Zittau, Germany

Linear rolling systems are frequently used in industrial practice for the linear motion of machine parts or mechanical assemblies. Their reliability and prediction of possible failures are, during a production process, highly required to prevent production losses. Unfortunately, common diagnostic systems of linear rolling systems in industrial practice still fail in particular cases. Therefore, we designed an innovative solution for the diagnostic system based on a load-free part with a vibration sensor integrated into a carriage of the linear rolling system. A functional sample of diagnostics was produced, and vibrations measured on a loaded carriage and the diagnostic part in laboratory conditions were compared. Encouraging results were reached by time-domain analysis of measured data. On the diagnostic part, the damage appeared clearly, while on the loaded carriage, we did not observe any signs of damage.

Keywords: failure detection; linear rolling systems; vibrodiagnostics; wear

Received: September 21, 2022; Revised: October 11, 2022; Accepted: October 13, 2022; Published: December 15, 2022  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Jírová, R., Pešík, L., Sturm, M., & Kupka, A.M. (2022). Device for Failure Detection on Production Machines. Acta Mechanica Slovaca, 26(4), 38-43. doi: 10.21496/ams.2023.009
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. C. Mishra, A. K. Samantaray, G. Chakraborty, Rolling element bearing fault diagnosis under slow speed operation using wavelet de-noising, Measurement, vol. 103 (2017). doi: 10.1016/j.measurement.2017.02.033. Go to original source...
    2. L. Zheng, A. Ming, W. Zhang, T. Liu, F. Chum Y. Li, Fault feature extraction and enhancement of rolling element bearings based on maximum correlated kurtosis deconvolution and improved empirical wavelet transform, Applied Science, vol. 9 (2019). doi: 10.3390/app9091876. Go to original source...
    3. X. Zhang, J. Zhu, Y. Wu, D. Zhen, M. Zhang, Feature extraction for bearing fault detection using wavelet packet energy and fast kurtogram analysis, Applied Science, vol. 10 (2020). doi: 10.3390/app10217715. Go to original source...
    4. M. He, D. He, Deep learning based approach for bearing fault diagnosis, IEEE Transactions on Industry Applications, vol. 53 (2017). Go to original source...
    5. R. W. Rong, T. F. Ming, Research on rolling element bearing fault diagnosis based on genetic algorithm matching pursuit, IOP Conference Series: Materials Science and Engineering, vol. 283 (2017). doi: 10.1088/1757-899X/283/1/012009. Go to original source...
    6. THK Co. Ltd., Condition-detecting device, method, and program, and information-recording medium, granted patent EP1598569B1 (23.8.2011).
    7. THK Co. Ltd., Rolling guide device with breakage prediction function, patent application JP2012193803A (11.10.2012).
    8. HIWIN TECHNOLOGIES Corp., Linear guideway capable of detecting abnormal circulation state, granted patent US10436254B1 (8.10.2019).
    9. HIWIN TECHNOLOGIES Corp., Linear guideway, granted patent US10508691B1 (17.12.2019).
    10. H. Feng, R. Chen, Z. Wang, Feature extraction for fault diagnosis based on wavelet packet decomposition: An application on linear rolling guide, Advances in Mechanical Engineering, vol. 10. doi: 10.1177/1687814018796367. Go to original source...
    11. J. Zhong, K. Yang, Failure prediction for linear ball bearings based on wavelet transformation and self-organising map, Proceedings of 2018 IEEE 4th Information Technology and Mechatronics Engineering Conference, Chongqing, Peoples Republic China, 14-16th December 2018, p 34-38. Go to original source...
    12. THK Co. Ltd., Method for diagnosing rolling guide device status, granted patent JP6747757B2 (26.8.2020).
    13. Schaeffler Technologies Ag. & Co. Kg., Method for lubricating a linear guide, patent application DE102017113720A1 (27.12.2018).
    14. P. Chommuangpuck, T. Wanglomklang, J. Srisertpol, Fault detection and diagnosis of linear bearing in auto core adhesion mounting machines based on condition monitoring, Systems Science & Control Engineering, vol. 9(2021). doi: 10.1080/21642583.2021.1895901. Go to original source...
    15. M. S. Kim, J. P. Yun, S. Lee, P. Park, Unsupervised anomaly detection of LM guide using variational autoencoder, The XIth International Symposium on Advanced Topics in Electrical Engineering, Bucharest, Romania, 28-30th march 2019.
    16. M. S. Kim, J. P. Yun, P. Park, An explainable convolutional neural network for fault diagnosis in linear motion guide, IEEE Transactions on Industrial Informatics, vol. 17 (2021). Go to original source...
    17. D. Hong, S. Bang, B. Kim, Unsupervised condition diagnosis of linear motion guide using generative model based on images, IEEE Access, vol. 283 (2017). doi: 10.1109/ACCESS.2021.3084602. Go to original source...
    18. R. Jirova, L. Pesik, Dynamical load of linear rolling guides, MM Science Journal, vol. June (2020), pp. 3943-3949. doi: 10.17973/MMSJ.2020_06_2020014. Go to original source...
    19. Skoda Auto a. s., Linear rolling guide with integrated diagnostic equipment, granted patent CZ308232B6.

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content