State Identification of ECS Turbine Bearing Based on Fractal Dimension
According to nonlinear characteristics of vibration signals measured on the turbine used in the aircraft environment control system (ECS), the ensemble empirical mode decomposition (EEMD) together with fractal dimension analysis is investigated in the paper to extract characteristic quantities for t...
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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/10.1155/2018/4925647 |
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| _version_ | 1832560001641611264 |
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| author | Chenchen Li Qingpeng Han Rui Zhu Qingyu Zhu |
| author_facet | Chenchen Li Qingpeng Han Rui Zhu Qingyu Zhu |
| author_sort | Chenchen Li |
| collection | DOAJ |
| description | According to nonlinear characteristics of vibration signals measured on the turbine used in the aircraft environment control system (ECS), the ensemble empirical mode decomposition (EEMD) together with fractal dimension analysis is investigated in the paper to extract characteristic quantities for the goal of fault diagnosis of turbine bearings. Firstly, in order to filter noise signal vibration and advance signal-to-noise signals under different statements of bearings, including normal bearing, inner ring fault, outer ring fault, and cage fault, are decomposed by EEMD. Then correlation dimension of those signals phase is calculated, contrasted, and analyzed after space reconstruction. The experimental result shows that the correlation dimension, as nonlinear geometric invariants, can be used as the characteristic quantity of ECS turbine bearing on running state. Moreover, this method can accurately and effectively identify the running state of the bearing. |
| format | Article |
| id | doaj-art-d7d1971efd4a404f916950a0dd8ac720 |
| 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-d7d1971efd4a404f916950a0dd8ac7202025-02-03T01:28:47ZengWileyShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/49256474925647State Identification of ECS Turbine Bearing Based on Fractal DimensionChenchen Li0Qingpeng Han1Rui Zhu2Qingyu Zhu3College of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaSchool of Mechanical Engineering, Dalian University of Technology, Dalian 116024, ChinaAccording to nonlinear characteristics of vibration signals measured on the turbine used in the aircraft environment control system (ECS), the ensemble empirical mode decomposition (EEMD) together with fractal dimension analysis is investigated in the paper to extract characteristic quantities for the goal of fault diagnosis of turbine bearings. Firstly, in order to filter noise signal vibration and advance signal-to-noise signals under different statements of bearings, including normal bearing, inner ring fault, outer ring fault, and cage fault, are decomposed by EEMD. Then correlation dimension of those signals phase is calculated, contrasted, and analyzed after space reconstruction. The experimental result shows that the correlation dimension, as nonlinear geometric invariants, can be used as the characteristic quantity of ECS turbine bearing on running state. Moreover, this method can accurately and effectively identify the running state of the bearing.http://dx.doi.org/10.1155/2018/4925647 |
| spellingShingle | Chenchen Li Qingpeng Han Rui Zhu Qingyu Zhu State Identification of ECS Turbine Bearing Based on Fractal Dimension Shock and Vibration |
| title | State Identification of ECS Turbine Bearing Based on Fractal Dimension |
| title_full | State Identification of ECS Turbine Bearing Based on Fractal Dimension |
| title_fullStr | State Identification of ECS Turbine Bearing Based on Fractal Dimension |
| title_full_unstemmed | State Identification of ECS Turbine Bearing Based on Fractal Dimension |
| title_short | State Identification of ECS Turbine Bearing Based on Fractal Dimension |
| title_sort | state identification of ecs turbine bearing based on fractal dimension |
| url | http://dx.doi.org/10.1155/2018/4925647 |
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