An Adaptive Spectral Kurtosis Method Based on Optimal Filter
As a useful tool to detect protrusion buried in signals, kurtosis has a wide application in engineering, for example, in bearing fault diagnosis. Spectral kurtosis (SK) can further indicate the presence of a series of transients and their locations in the frequency domain. The factors influencing ku...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2017/6987250 |
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| _version_ | 1832548136614100992 |
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| author | Yanli Yang Ting Yu |
| author_facet | Yanli Yang Ting Yu |
| author_sort | Yanli Yang |
| collection | DOAJ |
| description | As a useful tool to detect protrusion buried in signals, kurtosis has a wide application in engineering, for example, in bearing fault diagnosis. Spectral kurtosis (SK) can further indicate the presence of a series of transients and their locations in the frequency domain. The factors influencing kurtosis values are first analyzed, leading to the conclusion that amplitude, not the frequency of signals, and noise make major contribution to kurtosis values. It is helpful to detect impulsive components if the components with big amplitude are removed from composite signals. Based on this cognition, an adaptive SK algorithm is proposed in this paper. The core steps of the proposed SK algorithm are to find maxima, add window around maxima, merge windows in the frequency domain, and then filter signals according to the merged window in the time domain. The parameters of the proposed SK algorithm are varying adaptively with signals. Some experimental results are presented to demonstrate the effectiveness of the proposed algorithm. |
| format | Article |
| id | doaj-art-9ff25dab330f4c48a611f52013ac650b |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-9ff25dab330f4c48a611f52013ac650b2025-02-03T06:42:08ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/69872506987250An Adaptive Spectral Kurtosis Method Based on Optimal FilterYanli Yang0Ting Yu1Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin Polytechnic University, Tianjin 300387, ChinaTianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin Polytechnic University, Tianjin 300387, ChinaAs a useful tool to detect protrusion buried in signals, kurtosis has a wide application in engineering, for example, in bearing fault diagnosis. Spectral kurtosis (SK) can further indicate the presence of a series of transients and their locations in the frequency domain. The factors influencing kurtosis values are first analyzed, leading to the conclusion that amplitude, not the frequency of signals, and noise make major contribution to kurtosis values. It is helpful to detect impulsive components if the components with big amplitude are removed from composite signals. Based on this cognition, an adaptive SK algorithm is proposed in this paper. The core steps of the proposed SK algorithm are to find maxima, add window around maxima, merge windows in the frequency domain, and then filter signals according to the merged window in the time domain. The parameters of the proposed SK algorithm are varying adaptively with signals. Some experimental results are presented to demonstrate the effectiveness of the proposed algorithm.http://dx.doi.org/10.1155/2017/6987250 |
| spellingShingle | Yanli Yang Ting Yu An Adaptive Spectral Kurtosis Method Based on Optimal Filter Shock and Vibration |
| title | An Adaptive Spectral Kurtosis Method Based on Optimal Filter |
| title_full | An Adaptive Spectral Kurtosis Method Based on Optimal Filter |
| title_fullStr | An Adaptive Spectral Kurtosis Method Based on Optimal Filter |
| title_full_unstemmed | An Adaptive Spectral Kurtosis Method Based on Optimal Filter |
| title_short | An Adaptive Spectral Kurtosis Method Based on Optimal Filter |
| title_sort | adaptive spectral kurtosis method based on optimal filter |
| url | http://dx.doi.org/10.1155/2017/6987250 |
| work_keys_str_mv | AT yanliyang anadaptivespectralkurtosismethodbasedonoptimalfilter AT tingyu anadaptivespectralkurtosismethodbasedonoptimalfilter AT yanliyang adaptivespectralkurtosismethodbasedonoptimalfilter AT tingyu adaptivespectralkurtosismethodbasedonoptimalfilter |