Abstract
Because of its benefits, an induction machine is used in a variety of applications. The machine’s robustness is one of its benefits. Generally, mechanical faults cause torque oscillations, eccentricity, and vibration, which affect the stator current value and magnetic field distribution. As a result, early warning of mechanical failures helps to prevent damage to the induction system or sudden stopping. In this sense, the accuracy of techniques in detecting rolling bearing failure is investigated in this article. The first method focused on stator current analysis and the second on stray flux signature analysis. The aim of this research is to compare the success of the stray flux technique and the stator current analysis in detecting inner raceway faults. In addition, this research suggests a novel method for determining the relationship between two signals based on a transfer function estimate and magnitude-squared coherence between current and flux. Experimental tests were realized in a laboratory to artificially create the bearing damage. After that, the analysis focused on characteristic harmonics related to the different harmonics.
Highlights
Induction motors (IMs) are commonly used in a variety of industrial uses
Like all rotating electrical machines (REMs), they are vulnerable to a variety of faults
The use of motor current signature analysis (MCSA)-fast Fourier transform (FFT) and Stray Flux Signature Analysis (SFSA)-FFT to detect rolling element bearing faults in an IM is compared in this paper
Summary
Induction motors (IMs) are commonly used in a variety of industrial uses. like all rotating electrical machines (REMs), they are vulnerable to a variety of faults. 5. Transfer Function Estimate Analysis (TFEA) The proposed method for system identification using a frequency analysis approach is briefly described below, followed by a detailed presentation of the theory. Transfer Function Estimate Analysis (TFEA) The proposed method for system identification using a frequency analysis approach is briefly described below, followed by a detailed presentation of the theory The proposed method for system identification using a frequency analysis appr6ooaf c1h0 is briefly described below, followed by a detailed presentation of the theory This method starts by finding a rough estimate of the relationship between signals (transfer function). This information is considered as a new data which can exploit it for another analysis
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