Document Type
Article
Language
eng
Format of Original
9 p.
Publication Date
7-2003
Publisher
Institute of Electrical and Electronics Engineers
Source Publication
IEEE Transactions on Industry Applications
Source ISSN
0093-9994
Original Item ID
doi: 10.1109/TIA.2003.814582
Abstract
This paper develops the foundations of a technique for detection and categorization of dynamic/static eccentricities and bar/end-ring connector breakages in squirrel-cage induction motors that is not based on the traditional Fourier transform frequency-domain spectral analysis concepts. Hence, this approach can distinguish between the "fault signatures" of each of the following faults: eccentricities, broken bars, and broken end-ring connectors in such induction motors. Furthermore, the techniques presented here can extensively and economically predict and characterize faults from the induction machine adjustable-speed drive design data without the need to have had actual fault data from field experience. This is done through the development of dual-track studies of fault simulations and, hence, simulated fault signature data. These studies are performed using our proven time-stepping coupled finite-element-state-space method to generate fault case performance data, which contain phase current waveforms and time-domain torque profiles. Then, from this data, the fault cases are classified by their inherent characteristics, so-called "signatures" or "fingerprints." These fault signatures are extracted or "mined" here from the fault case data using our novel time-series data mining technique. The dual track of generating fault data and mining fault signatures was tested here on dynamic and static eccentricities of 10% and 30% of air-gap height as well as cases of one, three, six, and nine broken bars and three, six, and nine broken end-ring connectors. These cases were studied for proof of principle in a 208 V 60 Hz four-pole 1.2 hp squirrel-cage three-phase induction motor. The paper presents faulty and healthy performance characteristics and their corresponding so-called phase space diagnoses that show distinct fault signatures of each of the above-mentioned motor faults.
Recommended Citation
Bangura, John F.; Povinelli, Richard J.; Demerdash, Nabeel; and Brown, Ronald H., "Diagnostics of Eccentricities and Bar/End-Ring Connector Breakages in Polyphase Induction Motors through a Combination of Time-Series Data Mining and Time-Stepping Coupled FE-State Space Techniques" (2003). Electrical and Computer Engineering Faculty Research and Publications. 101.
https://epublications.marquette.edu/electric_fac/101
ADA Accessible Version
Comments
Accepted version. IEEE Transactions on Industry Applications, Vol. 39, No. 4 (July/August 2003): 1005-1013. DOI. © 2003 Institute of Electrical and Electronic Engineers (IEEE). Used with permission.