Bearing Fault Detection Using Gaussian Filter Bank

被引:0
作者
Kandale, Neha S. [1 ]
Gaikwad, J. A. [1 ]
Kulkarni, J. V. [1 ]
机构
[1] Vishwakarma Inst Technol, Dept Instrumentat, Pune, Maharashtra, India
来源
2017 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION, CONTROL AND AUTOMATION (ICCUBEA) | 2017年
关键词
Gaussian function; Convolution; FFT; Bearing; Fault diagnosis; Vibration analysis;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
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页数:6
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