A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions
Under frequently time-varying operating conditions, equipment with dual rotors like gas turbines is influenced by two rotors with different rotating speeds. Alarm methods of fixed threshold are unable to consider the influences of time-varying operating conditions. Hence, those methods are not suita...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2018/5382398 |
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| _version_ | 1832568053788835840 |
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| author | Zhinong Jiang Minghui Hu Kun Feng Hao Wang |
| author_facet | Zhinong Jiang Minghui Hu Kun Feng Hao Wang |
| author_sort | Zhinong Jiang |
| collection | DOAJ |
| description | Under frequently time-varying operating conditions, equipment with dual rotors like gas turbines is influenced by two rotors with different rotating speeds. Alarm methods of fixed threshold are unable to consider the influences of time-varying operating conditions. Hence, those methods are not suitable for monitoring dual-rotor equipment. An early warning method for dual-rotor equipment under time-varying operating conditions is proposed in this paper. The influences of time-varying rotating speeds of dual rotors on alarm thresholds have been considered. Firstly, the operating conditions are divided into several limited intervals according to rotating speeds of dual rotors. Secondly, the train data within each interval is processed by SVDD and the allowable ranges (i.e., the alarm threshold) of the vibration are determined. The alarm threshold of each interval of operating conditions is obtained. The alarm threshold can be expressed as a sphere, whose controlling parameters are the coordinate of the center and the radius. Then, the cluster center of the test data, whose alarm state is to be judged, can be extracted through K-means. Finally, the alarm state can be obtained by comparing the cluster center with the corresponding sphere. Experiments are conducted to validate the proposed method. |
| format | Article |
| id | doaj-art-12e6a6dd96a94026aeffcf5f897db3e3 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-12e6a6dd96a94026aeffcf5f897db3e32025-02-03T00:59:48ZengWileyShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/53823985382398A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating ConditionsZhinong Jiang0Minghui Hu1Kun Feng2Hao Wang3College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, ChinaCollege of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, ChinaCollege of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, ChinaCollege of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, ChinaUnder frequently time-varying operating conditions, equipment with dual rotors like gas turbines is influenced by two rotors with different rotating speeds. Alarm methods of fixed threshold are unable to consider the influences of time-varying operating conditions. Hence, those methods are not suitable for monitoring dual-rotor equipment. An early warning method for dual-rotor equipment under time-varying operating conditions is proposed in this paper. The influences of time-varying rotating speeds of dual rotors on alarm thresholds have been considered. Firstly, the operating conditions are divided into several limited intervals according to rotating speeds of dual rotors. Secondly, the train data within each interval is processed by SVDD and the allowable ranges (i.e., the alarm threshold) of the vibration are determined. The alarm threshold of each interval of operating conditions is obtained. The alarm threshold can be expressed as a sphere, whose controlling parameters are the coordinate of the center and the radius. Then, the cluster center of the test data, whose alarm state is to be judged, can be extracted through K-means. Finally, the alarm state can be obtained by comparing the cluster center with the corresponding sphere. Experiments are conducted to validate the proposed method.http://dx.doi.org/10.1155/2018/5382398 |
| spellingShingle | Zhinong Jiang Minghui Hu Kun Feng Hao Wang A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions Shock and Vibration |
| title | A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions |
| title_full | A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions |
| title_fullStr | A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions |
| title_full_unstemmed | A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions |
| title_short | A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions |
| title_sort | svdd and k means based early warning method for dual rotor equipment under time varying operating conditions |
| url | http://dx.doi.org/10.1155/2018/5382398 |
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