Novel condition monitoring of induction motor bearings via motor current signature analysis

The paper authors are researching the assessment of bearing conditions in induction motors. The methods developed by the authors are based on measurements and analysis of the motor supply current, which is particularly attractive in the absence of access to the engine. The article provides an overview of selected methods of induction motor bearings diagnostic based on Motor Current Signature Analysis (MCSA). However, there is no solution to date which credibility allows for industrial application. The main problem is the high ratio of disturbance components compared to the useful diagnostic components in the motor current. The author team has developed a methodology which enables introduction of various damage to bearings and also built a test stand enabling a wide range of engine tests with damaged bearings. This has provided the opportunity to compare the results of a large number of damaged bearings in a controlled manner, and also to compare different diagnostic methods. The article presents results of two new studies performed on this test stand, obtained on the basis of instantaneous power measurements and statistical method of signal analysis that have been improved by the authors. Preliminary studies confirm the advantages of these methods. The presented concept has the potential for industry implementation.

[1]  Tomasz Ciszewski,et al.  Current-based higher-order spectral covariance as a bearing diagnostic feature for induction motors , 2016 .

[2]  Wei Zhou,et al.  Incipient Bearing Fault Detection via Stator Current Noise Cancellation using Wiener Filter , 2007, 2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[3]  Leon Swędrowski,et al.  UNCERTAINTY ANALYSIS OF MEASURING SYSTEM FOR INSTANTANEOUS POWER RESEARCH , 2012 .

[4]  L. Frosini,et al.  Effect of the bearings faults on the efficiency of the induction motors , 2008, 2008 34th Annual Conference of IEEE Industrial Electronics.

[5]  J. Poshtan,et al.  An Advanced Park's Vectors Approach for Bearing Fault Detection , 2006, 2006 IEEE International Conference on Industrial Technology.

[6]  J. Rusek,et al.  Model and simulation tests of a squirrel - cage induction motor with oscillation of the air gap , 2005, 2005 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[7]  François Guillet,et al.  A New Bearing Fault Detection Method in Induction Machines Based on Instantaneous Power Factor , 2008, IEEE Transactions on Industrial Electronics.

[8]  Len Gelman,et al.  The New Second and Higher Order Spectral Technique for Damage Monitoring of Structures and Machinery , 2020 .