DETECCIÓN DE FALLA DE RODAMIENTO EN UNA CADENA CINEMÁTICA VÍA EMISIÓN ACÚSTICA
Resumen
Resumen
Las cadenas cinemáticas son componentes esenciales en la mayoría industrias, compuestas principalmente por motores de inducción, cajas de engranes, etc.., las fallas de estás provocan grandes pérdidas monetarias. Para evitarlos se utilizan sistemas automatizados de monitorización. Existen diferentes técnicas de monitoreo con diferentes metodologías, la emisión acústica (EA) es uno de los métodos de monitoreo no invasivo para la detección de fallas en estos sistemas. En este trabajo se presenta el desarrollo de un sistema de adquisición de señales de EA y una metodología basada en el análisis de estas señales para la detección de falla de rodamiento en un banco de pruebas de una cadena cinemática, la identificación de los componentes relacionados con la falla para el análisis es respaldado por su modelo teórico. Los resultados obtenidos muestran la detección de falla en rodamiento en altas frecuencias y la metodología para el análisis de la EA.
Palabras Claves: Detección de fallas, emisión acústica, FFT, rodamientos.
DETECTION OF BEARING FAILURE IN A CINEMATIC CHAIN VIA ACOUSTIC EMISSION
Abstract
Kinematics Chains are essential components in most industries, composed mainly of induction motors, gearboxes, etc.., failures within them cause great monetary losses. To avoid this, automated monitoring systems are used. There are different monitoring techniques with different methodologies, the acoustic emission (AE) is one of the methods of noninvasive monitoring for the detection of failures in these systems. This work presents the development of an AE signal acquisition system and a methodology based on the analysis of these signals for the detection of bearing failure in a test bench of a kinematic chain. The identification of the components related to the fault for the analysis is supported by its theoretical model. The obtained results show the detection of failure in rolling in high frequencies and the methodology for the analysis of the AE.
Keywords: Acoustic emission, bearings, faults detection, FFT.
Texto completo:
1392-1406 PDFReferencias
Amini, A., Entezami, M., Huang, Z., Rowshandel, H., & Papaelias, M., Wayside detection of faults in railway axle bearings using time spectral kurtosis analysis on high-frequency acoustic emission signals. Advances in Mechanical Engineering, 8(11), 1687814016676000, 2016.
Caesarendra, W., Kosasih, B., Tieu, A. K., Zhu, H., Moodie, C. A., & Zhu, Q., Acoustic emission-based condition monitoring methods: Review and application for low speed slew bearing. Mechanical Systems and Signal Processing, 72, pp. 134-159, 2016.
Delgado-Arredondo, P. A., Garcia-Perez, A., Morinigo-Sotelo, D., Osornio-Rios, R. A., Avina-Cervantes, J. G., Rostro-Gonzalez, H., & Romero-Troncoso, R. D. J., Comparative study of time-frequency decomposition techniques for fault detection in induction motors using vibration analysis during startup transient. Shock and Vibration, 2015.
Gohar, R., & Akturk, N., Vibrations Associated With Ball Bearings. In Conference on Multi body Dynamics, Proc. I. Mech. Engrs, pp. 43-63, 1998.
Hao, R. J., Lu, W. X., & Chu, F. L., Review of diagnosis of rolling element bearings defaults by means of acoustic emission technique. Journal of Vibration and Shock, 27(3), pp. 75-79, 2008.
Henriquez P., Alonso, J. B., Ferrer, M. A., & Travieso, C. M., Review of automatic fault diagnosis systems using audio and vibration signals. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(5), pp. 642-652, 2014.
James Li C, Li S, Acoustic emission analysis for bearing condition monitoring, Wear 185(1), pp. 67–74, 1995.
Kral, C., & Habetler, T. G., Condition monitoring and fault detection of electric drives. INTECH Open Access Publisher, 2010.
Mba D, Acoustic emissions and monitoring bearing health. Tribol Trans 46(3), pp. 447–451, 2003.
McFadden P, Smith J., Acoustic emission transducers for the vibration monitoring of bearings at low speeds. Proc Inst Mech Eng Part C J Mech Eng Sci 198, pp. 127–130, 1984.
Morales Velazquez, L., de Jesus Romero Troncoso, R., Osornio-Rios, R. A., Herrera-Ruiz, G., & Cabal-Yepez, E., Open-architecture system based on a reconfigurable hardware–software multi-agent platform for CNC machines. Journal of Systems Architecture, 56(9), pp. 407-418, 2010.
Niknam, S. A., Songmene, V., & Au, Y. J., The use of acoustic emission information to distinguish between dry and lubricated rolling element bearings in low-speed rotating machines. The International Journal of Advanced Manufacturing Technology, 69(9-12), pp. 2679-2689, 2013.
Pao, Y. H., Gajewski, R. R., & Ceranoglu, A. N., Acoustic emission and transient waves in an elastic plate. The Journal of the Acoustical Society of America, 65(1), pp. 96-105, 1979.
Pollock, A. A., Acoustic emission-2: acoustic emission amplitudes. Non-destructive testing, 6(5), pp. 264-269, 1973.
Saucedo-Dorantes, J. J., Delgado-Prieto, M., Ortega-Redondo, J. A., Osornio-Rios, R. A., & Romero-Troncoso, R. D. J., Multiple-fault detection methodology based on vibration and current analysis applied to bearings in induction motors and gearboxes on the kinematic chain. Shock and Vibration, 2016.
Saxena, A., & Saad, A., Genetic algorithms for artificial neural net-based condition monitoring system design for rotating mechanical systems. In Applied Soft Computing Technologies: The Challenge of Complexity, Springer Berlin Heidelberg, pp. 135-149, 2006.
Tandon N, Nakra B., Comparison of vibration and acoustic measurement techniques for the condition monitoring of Rolling element bearings. Tribol Int 25(3), pp. 205–212, 1992.
Tandon, N., & Nakra, B. C., Vibration and acoustic monitoring techniques for the detection of defects in rolling element bearings―a review. The shock and vibration digest, 24(3), pp. 3-11, 1992.
Tandon, N., & Choudhury, A., A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology international, 32(8), pp. 469-480, 1999.
V.Mien, K. Hee-Jun, and S. Kyoo-Sik, Rolling element bearing fault diagnosis based on non-local means de-noising and empiricalmode decomposition, IET Science, Measurement and Technology, vol. 8, no. 6, pp. 571–578, 2014.
URL de la licencia: https://creativecommons.org/licenses/by/3.0/deed.es
Pistas Educativas está bajo la Licencia Creative Commons Atribución 3.0 No portada.
TECNOLÓGICO NACIONAL DE MÉXICO / INSTITUTO TECNOLÓGICO DE CELAYA
Antonio García Cubas Pte #600 esq. Av. Tecnológico, Celaya, Gto. México
Tel. 461 61 17575 Ext 5450 y 5146
pistaseducativas@itcelaya.edu.mx