On the detection of distributed roughness on ball bearings via stator current energy: experimental results

• Autorzy: Curcuru G. , Cocconcelli M. , Immovilli F. , Rubini R.
• Języki publikacji: EN

Abstrakty

EN

This paper deals with the detection of distributed roughness on ball-bearings mounted on electric motors. Most of the literature techniques focus on the early detection of localized faults on bearing (e.g. on the outer ring) in order to determine the bearing life and to plan the bearing replacing. Localized faults can be detected because they have characteristic signatures which is revealed in the frequency spectrum of the vibration signal acquired by an external sensor, e.g. accelerometer. Unfortunately other faults exist which do not have a characteristic signatures and then they could not be foreseen accurately: e.g. the distributed roughness. In this paper the motor stator current energy is proposed as a fault indicator to identify the presence of the distributed roughness on the bearing. Moreover an orthogonal experiment is set to analyse, through a General Linear Model (GLM), the dependencies of the current energy to the roughness level, and two environmental conditions: the motor velocity and the loads applied externally. ANOVA investigates the statistical significance of the considered factors.

Słowa kluczowe

EN

bearing diagnostics; distributed roughness; ANOVA; GLM; induction motor

PL

łożysko; diagnostyka; ANOVA; GLM; silnik elektryczny indukcyjny

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2009
• Tom: nr 3(51)
• Strony: 17--21
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Curcuru G.

autor

Cocconcelli M.

autor

Immovilli F.

autor

Rubini R.

• DTMPIG, University of Palermo, Palermo, Italy,

Bibliografia

• [1] Jayaswal P., Wadhwani A. K., Mulchandani K. B.: Machine Fault Signature Analysis, Int. J. Rot. Mach. (2008).
• [2] Kamarainen J. I., Lindh T., Ahola J., Kalviainen H., Partanen J.: Diagnosis Tool for Motor Condition Monitoring, IEEE Trans. Ind. Appl. 41 (2005) 963-971.
• [3] Harris T. A.: Rolling Bearing Analysis, John Wiley and Sons, New York, 2001.
• [4] Stack J., Habetler G., Harley G.: Fault Classification and Fault Signature Production for Rolling Element Bearings in Electric Machines, IEEE Trans. Ind. Appl. 40 (2004) 735-739.
• [5] Stack J., Habetler G., Harley G.: Bearing Fault Detection via Autoregressive Stator Current Modelling, IEEE Trans. Ind. Appl. 40 (2004) 740-747.
• [6] Zhou W., Habetler T., Harley R. G.: Stator Current-Based Bearing Fault Detection Techniques: A General review, Proceedings of IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives SDEMPED 2007, IEEE, Cracow, Poland, 2007, pp. 7-10.
• [7] Blödt M., Raison B., Rostaing G., Granjon P.: Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring, IEEE Trans. on Ind. Electr., 55(2008) 1813-1822.
• [8] Bellini A., Franceschini G., Tassoni C.: Monitoring of induction Machines by maximum covariance method for frequency tracking, IEEE Trans. Ind. Appl. 42 (2006) 69-78.
• [9] Elfeky A., Masoud M., Arabawy I.: Fault Signature Production for Rolling Element Bearings in Induction Motor, Proceedings of Compatibility in Power Electronics CPE '07, IEEE, Gdańsk, Poland, 2007, pp. 1-5.
• [10] Bellini A., Immovilli F., Rubini R. and Tassoni C.: Diagnosis of bearing faults of induction machines by vibration or current signals: A critical comparison, Proceedings of Annual Meeting of Industry Applications Society IAS ’08, IEEE, Edmonton, Canada, 2008.
• [11] Bellini A., Cocconcelli M., Immovilli F. and Rubini R.: Diagnosis of mechanical faults by Spectral Kurtosis Energy, Proceedings of Annual Conference of Industrial Electronics Society IECON’08, IEEE, Orlando, USA, 2008.