Nueva metodología para la detección de fallas en rodamientos en motores de inducción trifásicos

A new methodology for detection of bearings faults in three-phase induction motor

Contenido principal del artículo

Carlos Cáceres-Amaya
Resumen

Este estudio expone una metodología para la detección, clasificación y ubicación de fallas en rodamientos de bola, en la jaula y la pista exterior. Para este estudio se utilizó un motor de inducción trifásico, en el que se midieron las señales de tensión y corriente del estator. Calculando la distorsión armónica total y utilizando la Transformada de Stockwell, se obtuvieron diferentes características en las señales eléctricas que permitieron definir las condiciones de falla en el rodamiento, la clasificación del tipo de falla y la ubicación del rodamiento defectuoso (lado ventilador o lado carga). Calculando la diferencia entre la distorsión armónica total de la señal de corriente y voltaje, es posible identificar un valor de umbral de 0.004 que separa una condición de operación normal y una condición de falla. El uso de la Transformada de Stockwell y el algoritmo de puntuación de Fisher nos permite clasificar las condiciones de falla con una precisión promedio del 92.5%. La ubicación de un rodamiento con defectos en el lado de carga genera una mayor amplitud en la señal, en comparación con los ubicados en el lado del ventilador. Este comportamiento permite establecer un valor umbral de 1.6 para fallas de bola y 0.001 para fallas en la jaula y en la pista exterior. Por los resultados obtenidos, el algoritmo propuesto en el estudio se considera una herramienta con un alto grado de confiabilidad para el diagnóstico de rodamientos en motores de inducción.

Palabras clave

Descargas

Los datos de descargas todavía no están disponibles.

Detalles del artículo

Biografía del autor/a (VER)

Carlos Cáceres-Amaya, Universidad Francisco de Paula Santander

Ingeniero de Sistemas

Jorge Duarte-Forero, Universidad del Atlántico

Doctor en Ingeniería Mecánica

Guillermo Valencia-Ochoa, Universidad del Atlántico

Doctor en Ingeniería

Referencias

S. O. Gulhane and M. R. Salodkar, Review of Detection of Faults in Induction Motor, 2016.

H. Arabaci and O. Bilgin, Effects of rotor faults in squirrel-cage induction motors on the torque-speed curve, in The XIX International Conference on Electrical Machines - ICEM 2010, pp. 1–5, 2010.

D. V. Spyropoulos and E. D. Mitronikas, A Review on the Faults of Electric Machines Used in Electric Ships, Advances in Power Electronics, vol. 2013, pp. 1–8, 2013.

M. A. Alsaedi, Fault Diagnosis of Three-Phase Induction Motor: A Review, Optics, vol. 4, no. 1, p. 1, 2015.

T. Aroui, Y. Koubaa, and A. Toumi, Magnetic coupled circuits modeling of induction machines oriented to diagnostics, Leonardo Journal of Sciences, vol. 7, no. 13, pp. 103–121, 2008.

R. Moreno-Chuquen and O. Florez-Cediel, Online Dynamic Assessment of System Stability in Power Systems Using the Unscented Kalman Filter, International Review of Electrical Engineering (IREE), vol. 14, no. 6, pp. 465–472, 2019.

A. M. S. Yunus, M. Saini, M. R. Djalal, A. Abu-Siada, and M. A. S. Masoum, Impact of Superconducting Magnetic Energy Storage Unit on Doubly Fed Induction Generator Performance During Various Levels of Grid Faults, International Review of Electrical Engineering (IREE), vol. 14, no. 4, pp. 246–255, 2019.

P. Thongprasri, Investigation of a Switched Reluctance Generator Using the Voltage Pulse Width Modulation Method, International Review of Electrical Engineering (IREE), vol. 13, no. 2, pp. 89–97, 2018.

M. Widyan, Operational Performance of Synchronous Generator Hybrid-Excited by PMDC and PV Generators, International Review of Electrical Engineering (IREE), vol. 9, no. 4, pp. 863–872, 2014.

M. S. Sepeeh, S. A. Zulkifli, S. Y. Sim, and E. Pathan, A Comprehensive Review of Field-Oriented Control in Sensorless Control Techniques for Electric Vehicle, International Review of Electrical Engineering (IREE), vol. 13, no. 6, pp. 461–475, 2018.

K. C. Lakshmiah and T. A. Raghavendiran, A New Modified H-Bridge Multilevel Inverter with Multi Carrier PWM Technique for Speed Control of Induction Motor, International Review of Electrical Engineering (IREE), vol. 13, no. 5, pp. 365–372, 2018.

Ç. Acar, O. C. Soygenc, and L. T. Ergene, Increasing the Efficiency to IE4 Class for 5.5 kW Induction Motor Used in Industrial Applications, International Review of Electrical Engineering (IREE), vol. 14, no. 1, pp. 67–78, 2019.

F. S. El-Faouri, O. Mohamed, and W. A. Elhaija, Model-Based Field-Oriented Control of a Three-Phase Induction Motor with Consideration of Rotor Resistance Variation, International Review of Electrical Engineering (IREE), vol. 14, no. 3, pp. 173–181, 2019.

M. A. Mossa and A. A. Z. Diab, Effective Model Predictive Control Approach for a Faulty Induction Motor Drive, International Review of Electrical Engineering (IREE), vol. 14, no. 5, pp. 314–327, 2019.

H. H. Hanafy, T. M. Abdo, and A. A. Adly, 2D finite element analysis and force calculations for induction motors with broken bars, Ain Shams Engineering Journal, vol. 5, no. 2, pp. 421–431, 2014.

M. Akar and I. Cankaya, Broken rotor bar fault detection in inverter-fed squirrel cage induction motors using stator current analysis and fuzzy logic, Turkish Journal of Electrical Engineering and Computer Sciences, vol. 20, pp. 1077–1089, 2012.

M. A. Juneghani, B. K. Boroujeni, and M. Abdollahi, Determination of number of broken rotor bars in squirrel-cage induction motors using adaptive neuro-fuzzy interface system, Research Journal of Applied Sciences, Engineering and Technology, vol. 4, pp. 3399–3405, 2012.

T. C. Anil Kumar, G. Singh, and V. N. A. Naikan, Effectiveness of vibration monitoring in the health assessment of induction motor, International Journal of Prognostics and Health Management, vol. 6, pp. 1–9, 2015.

Y. Liu and A. M. Bazzi, A review and comparison of fault detection and diagnosis methods for squirrel-cage induction motors: State of the art, ISA Transactions, vol. 70, pp. 400–409, 2017.

İ. Y. önel, K. Burak Dalci, and İ. Senol, Detection of outer raceway bearing defects in small induction motors using stator current analysis, Sadhana, vol. 30, no. 6, pp. 713–722, 2005.

S. E. Pandarakone, Y. Mizuno, and H. Nakamura, Distinct Fault Analysis of Induction Motor Bearing Using Frequency Spectrum Determination and Support Vector Machine, IEEE Transactions on Industry Applications, vol. 53, no. 3, pp. 3049–3056, 2017.

R. H. C. Palácios, I. N. da Silva, A. Goedtel, and W. F. Godoy, A novel multi-agent approach to identify faults in line connected three-phase induction motors, Applied Soft Computing, vol. 45, pp. 1–10, 2016.

A. Rai and S. H. Upadhyay, A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings, Tribology International, vol. 96, pp. 289–306, 2016.

E. Elbouchikhi, V. Choqueuse, Y. Amirat, M. E. H. Benbouzid, and S. Turri, An Efficient Hilbert–Huang Transform-Based Bearing Faults Detection in Induction Machines, IEEE Transactions on Energy Conversion, vol. 32, no. 2, pp. 401–413, 2017.

M. Lopez-Ramirez et al., Detection and diagnosis of lubrication and faults in bearing on induction motors through STFT, in 2016 International Conference on Electronics, Communications and Computers (CONIELECOMP), 2016, pp. 13–18.

O. P. Mahela and A. G. Shaik, Recognition of power quality disturbances using S-transform based ruled decision tree and fuzzy C-means clustering classifiers, Applied Soft Computing, vol. 59, pp. 243–257, 2017.

O. P. Mahela and A. G. Shaik, Power quality recognition in distribution system with solar energy penetration using S -transform and Fuzzy C-means clustering, Renewable Energy, vol. 106, pp. 37–51, 2017.

M. Singh and A. G. Shaik, Application of stockwell transform in bearing fault diagnosis of induction motor, in 2016 IEEE 7th Power India International Conference (PIICON), 2016, pp. 1–6.

Sistema OJS - Metabiblioteca |