Abstract
The bearing fault will firstly generate torque fluctuation, then magnetic field in motor is affected, lastly partial bearing fault feature is transferred into stator current. Because of the bearing fault feature is more obvious in magnetic field than those in stator current, the magnetic field frequency feature of the bearing fault is researched. The magnetic field characteristic frequency expression is deduced considering a multiple modulation between torque fluctuation frequency, power supply harmonics, and slot harmonics. The above expression is verified by finite element analysis. Using four search coils which are inserted inside the stator slot to research the magnetic field frequency feature at the actually bearing fault condition, and results verify that the proposed method based on magnetic field frequency feature is feasible and effective.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bouchikhi EHE, Choqueuse V, Benbouzid MEH et al (2013) Current frequency spectral subtraction and its contribution to induction machines’ bearings condition monitoring. IEEE Trans Energy Convers 28(1):135–144
Immovilli F, Bellini A, Rubini R et al (2010) Diagnosis of bearing faults in induction machines by vibration or current signals: a critical comparison. IEEE Trans Ind Appl 46(4):1350–1359
Salles G, Filippetti F, Tassoni C et al (2000) Monitoring of induction motor load by neural network techniques. IEEE Trans Power Electron 15(3):762–768
Esfahani ET, Wang S, Sundararajan V (2014) Multisensor wireless system for eccentricity and bearing fault detection in induction motors. IEEE/ASME Trans Mechatron 19(3):819
Frosini L, Bassi E (2010) Stator current and motor efficiency as indicators for different types of bearing faults in induction motors. IEEE Trans Ind Electron 57(1):244–251
Zhou W, Lu B, Habetler TG et al (2009) Incipient bearing fault detection via motor stator current noise cancellation using wiener filter. IEEE Trans Ind Appl 45(4):1309–1317
Frosini L, Harlisca C, Szabó L et al (2015) Induction machine bearing fault detection by means of statistical processing of the stray flux measurement. IEEE Trans Ind Electron 62(3):1846–1854
Ceban A, Pusca R, Romary R (2012) Study of rotor faults in induction motors using external magnetic field analysis. IEEE Trans Ind Electron 59(5):2083–2093
Blodt M, Granjon P, Raison B et al (2008) Models for bearing damage detection in induction motors using stator current monitoring. IEEE Trans Ind Electron 55(4):1813–1822
Acknowledgments
The research work was supported by National Natural Science Foundation of China under Grant No. 51279020. The support is greatly appreciated.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Geng, T., Qiu, C., Xu, C., Ma, J. (2016). Research on Magnetic Field Frequency Feature for Motor Bearing Fault. In: Jia, L., Liu, Z., Qin, Y., Ding, R., Diao, L. (eds) Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation. Lecture Notes in Electrical Engineering, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49367-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-662-49367-0_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-49365-6
Online ISBN: 978-3-662-49367-0
eBook Packages: EnergyEnergy (R0)