Abstract
This paper is about development of an AE signal-based monitoring system for detecting defects on the bearings and rails of an LMS which is widely used in the automated production lines. It is examined whether the defects really contribute to generation of the AE signal and what frequency components of the AE signal are closely related to the defects. The cepstrum analysis is adopted to get a time interval of the purely defect-driven AE wavelets, which is compared with the theoretical interval based on the kinematic modeling of LM rail and bearing of an LMS. From the defect-driven AE wavelet picked up from a series of AE signal, the frequency features very unique to each defect of Bearing/Rail are extracted. The features are grouped three bands, that is, 100–150, 150–200, 400–450 kHz. Three-band power spectrum shows different patterns each other for normal, rail defect, small bearing defect and worse bearing defect. Through these experiments, it is verified that AE signal is useful to detect the bearing/rail defect and a couple of bands around the AE frequency features can be used as a real-time monitoring device for the status monitoring of LMS.
References
Itagaki, H., Tsutsumi, M., and Iwanaka, H., “Improvement of vibration damping of linear roller guides using grease lubrication film,” Journal of the Japan Society for Precision Engineering, Vol. 78, No. 2, pp. 168–172, 2012.
Bollas, K., Papasalouros, D., Kourousis, D., and Anastasopoulos, A., “Acoustic emission inspection of rail wheels,” Journal of Acoustic Emission, Vol. 28, pp. 215–228, 2010.
Tandon, N. and Choudhury, A., “A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings,” Tribology International, Vol. 32, No. 8, pp. 469–480, 1999.
Chen, Y., He, Z., and Yang, S., “Research on on-line automatic diagnostic technology for scratch defect of rolling element bearings,” Int. J. Precis. Eng. Manuf., Vol. 13, No. 3, pp. 357–362, 2012.
Al-Ghamd, A. M. and Mba, D., “A comparative experimental study on the use of acoustic emission and vibration analysis for bearing defect identification and estimation of defect size,” Mechanical Systems and Signal Processing, Vol. 20, No. 7, pp. 1537–1571, 2006.
Sakai, Y. and Tsutsumi, M., “Resonance frequency of carriages for linear roller guides,” Journal of Japan Society for Precision Engineering, Vol. 78, No. 7, pp. 599–604, 2012.
Brunner, A. J., Tannert, T., and Vallee, T., “Waveform analysis of acoustic emission monitoring of tensile tests on welded wood-joints,” Journal of Acoustic Emission, Vol. 28, pp. 59–67, 2010.
Ono, K., Cho, H., and Matsuo, T., “New characterization methods of AE sensors,” Journal of Acoustic Emission, Vol. 28, pp. 256–277, 2010.
Barat, V., Borodin, Y., and Kuzmin, A., “Intelligent AE signal filtering methods,” Journal of Acoustic Emission, Vol. 28, pp. 109–119, 2010.
Castro, E., Piotrkowski, R., Antolino, C., and Climent, A. B., “Discrimination of acoustic emission hits from dynamic tests of a reinforced concrete slab, Journal of Acoustic Emission, Vol. 28, pp. 120–128, 2010.
Park, C. S., Choi, Y. C., and Kim, Y. H., “Early fault detection in automotive ball bearings using the minimum variance cepstrum,” Mechanical Systems and Signal Processing, Vol. 38, No. 2, pp. 534–548, 2013.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Jian, H., Lee, HR. & Ahn, JH. Detection of bearing/rail defects for linear motion stage using acoustic emission. Int. J. Precis. Eng. Manuf. 14, 2043–2046 (2013). https://doi.org/10.1007/s12541-013-0256-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12541-013-0256-y