Online Condition Monitoring to Diagnose Bearing Faults of Induction Motor
Neelam Mehala
Neelam Mehala, Department of Electronics Engineering, YMCA University of Science and Technology, Faridabad, INDIA.
Manuscript received on August 11, 2013. | Revised Manuscript received on August 15, 2013. | Manuscript published on August 25, 2013. | PP: 69-73 | Volume-1, Issue-10, August 2013. | Retrieval Number: J04390811013/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With advances in digital technology over the last years, adequate data processing capabilities is now available on cost effective hardware platforms, to monitor motors for variety of abnormalities on a real time basis. For this reasons, this paper is devoted to investigate the application of advanced signal processing techniques for detection of bearing fault of induction motor. In this study, bearing faults are successfully diagnosed by monitoring the stator current of motor. The experiments were conducted 0.5 hp, 415V induction motor. Virtual instrument was developed with help of programming in software ‘LabVIEW’. This instrument was used to obtain the current spectrum of stator current. The different spectrums of healthy motor and faulty motor were than compared to diagnose the bearing faults. The experimental results show that FFT based spectral analysis may be adequate to indicate the presence of bearing faults of induction motors. This may be achieved at a relatively low cost, eliminating need for expensive spectrum analyzers.
Keywords: Fault detection, signal processing, motor current signature analysis.