Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed
Monitoring the vibrations of high-speed rotating blades is significant to the security of turbomachineries. Blade tip timing (BTT) is considered as a promising technique for detecting blade vibrations without contact online. However, extracting blade vibration characteristics accurately from undersa...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/8328345 |
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| _version_ | 1832566529522139136 |
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| author | Suiyu Chen Yongmin Yang Haifeng Hu Fengjiao Guan Guoji Shen Faming Yang |
| author_facet | Suiyu Chen Yongmin Yang Haifeng Hu Fengjiao Guan Guoji Shen Faming Yang |
| author_sort | Suiyu Chen |
| collection | DOAJ |
| description | Monitoring the vibrations of high-speed rotating blades is significant to the security of turbomachineries. Blade tip timing (BTT) is considered as a promising technique for detecting blade vibrations without contact online. However, extracting blade vibration characteristics accurately from undersampled BTT signals measured at varying rotational speed (VRS) has become a big challenge. The existing two methods for this issue are restricted within the order bandwidth limitation and require prior information and precise sensor installation angles, which is often unpractical. To overcome these difficulties, a compressed sensing-based order analysis (CSOA) method was proposed. Its feasibility comes from the sparsity of BTT vibration signals in the order domain. The mathematical model for the proposed method was built, and the optimizing principles for sensor number and sensor arrangement were given. Simulated and experimental results verified the feasibility and advantages of the proposed method that it could extract order spectrum accurately from BTT vibration signals measured at VRS without the drawbacks in the existing two methods. |
| format | Article |
| id | doaj-art-286f5c366b5148ebb6ddee59690c8c29 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-286f5c366b5148ebb6ddee59690c8c292025-02-03T01:03:56ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/83283458328345Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational SpeedSuiyu Chen0Yongmin Yang1Haifeng Hu2Fengjiao Guan3Guoji Shen4Faming Yang5Laboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, ChinaLaboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, ChinaLaboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, ChinaLaboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, ChinaLaboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, ChinaLaboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, ChinaMonitoring the vibrations of high-speed rotating blades is significant to the security of turbomachineries. Blade tip timing (BTT) is considered as a promising technique for detecting blade vibrations without contact online. However, extracting blade vibration characteristics accurately from undersampled BTT signals measured at varying rotational speed (VRS) has become a big challenge. The existing two methods for this issue are restricted within the order bandwidth limitation and require prior information and precise sensor installation angles, which is often unpractical. To overcome these difficulties, a compressed sensing-based order analysis (CSOA) method was proposed. Its feasibility comes from the sparsity of BTT vibration signals in the order domain. The mathematical model for the proposed method was built, and the optimizing principles for sensor number and sensor arrangement were given. Simulated and experimental results verified the feasibility and advantages of the proposed method that it could extract order spectrum accurately from BTT vibration signals measured at VRS without the drawbacks in the existing two methods.http://dx.doi.org/10.1155/2020/8328345 |
| spellingShingle | Suiyu Chen Yongmin Yang Haifeng Hu Fengjiao Guan Guoji Shen Faming Yang Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed Shock and Vibration |
| title | Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed |
| title_full | Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed |
| title_fullStr | Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed |
| title_full_unstemmed | Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed |
| title_short | Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed |
| title_sort | compressed sensing based order analysis for blade tip timing signals measured at varying rotational speed |
| url | http://dx.doi.org/10.1155/2020/8328345 |
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