Vol. 3 Issue 1
Year:2015
Issue:Nov-Jan
Title:Diagnosis of Air-Gap Eccentricity Fault for Inverter Driven Induction Motor Drives in the Transient Condition
Author Name:Khadim Moin Siddiqui, Kuldeep Sahay and V.K. Giri
Synopsis:
In the present time, the inverter-driven induction motors drives are being widely employed in the industries for variable speed applications. These drives are replacing D.C. motors and thyrister bridges day to day in the industries. In the past, the Fast Fourier Transform (FFT) algorithm had been successfully implemented for the diagnosis of air-gap fault in the induction motor. This algorithm was used to diagnose various induction motor faults in the steady state conditions for constant load. However, the FFT algorithm is unable to detect induction motor faults in the transient condition. Therefore, early fault detection is not possible by this algorithm. Generally, the variable speed induction motors include large data size and FFT method is also not able to diagnose many faults for large data size. This research paper proposes a new technique for early air-gap fault diagnosis purpose. By using this technique, the air-gap fault may be diagnosed in the transient condition and fault may be averted before it becomes more catastrophic. As a result, industries may save large revenues and unexpected failure condition. In this research paper, an inverter driven induction motor model has been proposed and diagnosed for air-gap eccentricity fault in the transient condition by time-domain and time-frequency domain techniques.
Year:2015
Issue:Nov-Jan
Title:Diagnosis of Air-Gap Eccentricity Fault for Inverter Driven Induction Motor Drives in the Transient Condition
Author Name:Khadim Moin Siddiqui, Kuldeep Sahay and V.K. Giri
Synopsis:
In the present time, the inverter-driven induction motors drives are being widely employed in the industries for variable speed applications. These drives are replacing D.C. motors and thyrister bridges day to day in the industries. In the past, the Fast Fourier Transform (FFT) algorithm had been successfully implemented for the diagnosis of air-gap fault in the induction motor. This algorithm was used to diagnose various induction motor faults in the steady state conditions for constant load. However, the FFT algorithm is unable to detect induction motor faults in the transient condition. Therefore, early fault detection is not possible by this algorithm. Generally, the variable speed induction motors include large data size and FFT method is also not able to diagnose many faults for large data size. This research paper proposes a new technique for early air-gap fault diagnosis purpose. By using this technique, the air-gap fault may be diagnosed in the transient condition and fault may be averted before it becomes more catastrophic. As a result, industries may save large revenues and unexpected failure condition. In this research paper, an inverter driven induction motor model has been proposed and diagnosed for air-gap eccentricity fault in the transient condition by time-domain and time-frequency domain techniques.
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