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• W2891768995 abstract "Preventative maintenance is a growing trend in industrial operations. One critical area of preventative maintenance includes vibration monitoring. The most critical area for analysis is directed at the bearings. The performance of the machine depends upon health of bearing. So, Condition monitoring become vital to detect the faults. Vibration analysis is one of the important condition monitoring technique. This paper proposes the method of vibration analysis using signal processing tools such as Gaussian function, Convolution, Fast Fourier transform. In MATLAB, Gaussian function plots for different values of sigma (standard deviation) are obtained. These plots are convoluted with acquired vibration signal. After this harmonic analysis is done using Fast Fourier Transform to detect the fault. The proposed method is easy and provides accurate results." @default.
• W2891768995 created "2018-09-27" @default.
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• W2891768995 date "2017-08-01" @default.
• W2891768995 modified "2023-09-25" @default.
• W2891768995 title "Bearing Fault Detection Using Gaussian Filter Bank" @default.
• W2891768995 doi "https://doi.org/10.1109/iccubea.2017.8463979" @default.
• W2891768995 hasPublicationYear "2017" @default.
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