Diagnosis of bearing with mechanical vibrations and virtual instruments

  • Vıctor Manuel Gomez Ramırez
  • Juan Carlos Serna Bedoya
  • Luisa Velez Lopez
Palabras clave: Mechanical vibration analysis, Power spectral density, Virtual instrument, Bearings (es_ES)

Resumen (es_ES)

The mechanical vibration analysis has great importance in the condition based maintenance; in this sense, the bearings are elements that affect more stops rotating machinery. Therefore, this paper describes the hardware and software architecture of a vibration analyzer developed in LabVIEW oriented to study bearings extracting its parameters or descriptors through the power spectral density (PSD) and the RMS and DC signal values in time. Shows the advantages of working with such solutions: cost and the possibility of increasing benefits as needed.


La descarga de datos todavía no está disponible.


Moreno S´anchez R., Pintado Sanju´an P., Alonso S´anchez F.J., Chicharro Higuera J.M., Morales, Robredo A.L., Nieto Quijorna A.J.”Evaluaci´on y comparaci´on de modelos de diagn´ostico de fallos en engranajes utilizando las se˜nales de vibraciones mec´anicas”, 8o congreso iberoamericano de ingenier´ıa mec´anica, Cusco, 23 al 25 de Octubre de 2007.

Cornelius Scheffer, Paresh Girdhard, “Practical Machinery

Vibration Analysis and Predictive Maintenance”, Oxford: Jordan Hill, 2004

C.Castej´on,O, Lara,J.C.Garc´ıa-Prada, “Automated diagnosis of rolling bearings using MRA and neuralnetworks”, Mechanical Systems and Signal Processing, Vol 24 No 1 pp. 289-299, 27June 2009.

J. Lee, R. Abujamra, A.K.S. Jardine, D. Lin, D. Banjevic,

“An integrated platform for diagnostics, prognostics and maintenance optimization”, in: The IMS ’2004 International Conference on Advances in Maintenance and in Modeling, Simulation and Intelligent Monitoring of Degradations, Arles, France, 2004.

Andrew K.S. Jardine, Daming Lin, Dragan Banjevic, “A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mechanical Systems and Signal Processing” (2006) pp.1483–1510.

S. Goldman. “Vibration Spectrum Analysis”. Industrial

Press Inc. 2nd edition. New York, USA, pp. 83-85, 113-122. 1999

J. Mitchell. “Introduction to Machinery Analysis and Monitoring”. Pennwell Books. 2nd edition. Oklahoma, USA, pp. 134-160. 1993.

National Instruments, Febrero 2008. [En l´ınea]. Disponible en: www.ni.com.

T. Butcher. “10 Questions to ask when selecting your sound and vibration measurement system”. Enero 2006. [En l´ınea]. Disponible en: http://www.ni.com/academic/instructor/meche dy

namics vibration.htm

SKF Group “The Power of Knowledge Engineering”

Julio 2014 [En l´ınea]. Disponible en: www.skf.com

Case Western Reserve University, Julio 2014 [En l´ınea]. Disponible en: http://www.eecs.cwru.edu/laboratory/bearing.

Cómo citar
Gomez Ramırez, V. M., Serna Bedoya, J. C., & Velez Lopez, L. (2014). Diagnosis of bearing with mechanical vibrations and virtual instruments. Visión electrónica, 8(2), 107-113. https://doi.org/10.14483/22484728.9881
Publicado: 2014-12-28
Visión de Caso