Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform
The vibration signals propagating in different directions from rotating machines can contain a variety of characteristic information. A novel feature extraction method based on bivariate empirical mode decomposition (BEMD) for rotor is proposed to comprehensively extract the fault features. In this...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/1639139 |
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| _version_ | 1841524430922055680 |
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| author | Chuanjin Huang Haijun Song Wenping Lei Zhanya Niu Yajun Meng |
| author_facet | Chuanjin Huang Haijun Song Wenping Lei Zhanya Niu Yajun Meng |
| author_sort | Chuanjin Huang |
| collection | DOAJ |
| description | The vibration signals propagating in different directions from rotating machines can contain a variety of characteristic information. A novel feature extraction method based on bivariate empirical mode decomposition (BEMD) for rotor is proposed to comprehensively extract the fault features. In this work, the number of signal projection directions is determined through simulation, and the energy end condition based on the energy threshold is increased using BEMD to enhance the decomposition quality. Mixed vibration signals are generated along two orthogonal directions. Then, the acquired vibration signal can be decomposed into several intrinsic mode functions (IMFs) at the rotational speed using the BEMD method. Furthermore, the instantaneous frequency and instantaneous amplitude of the real signals and the imaginary part of the IMF signals are obtained using the Hilbert transform. The fault features along two and three dimensions can be investigated, providing more comprehensive information to aid in the fault diagnosis of rotor. Experimental results on oil film oscillation, the oil whirl, the bistability of the rotor, and looseness and rotor rubbing composite fault indicate the effectiveness of the proposed method. |
| format | Article |
| id | doaj-art-0c849edad9894c0da172946dbe48a575 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-0c849edad9894c0da172946dbe48a5752025-02-03T05:53:12ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/16391391639139Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert TransformChuanjin Huang0Haijun Song1Wenping Lei2Zhanya Niu3Yajun Meng4Zhengzhou Institute of Technology, No. 18, Ying Cai Street, Hui Ji District, Zhengzhou 450044, ChinaZhengzhou Institute of Technology, No. 18, Ying Cai Street, Hui Ji District, Zhengzhou 450044, ChinaSchool of Mechanical Engineering, Zhengzhou University, Zhengzhou 450052, ChinaHenan Suda Electric Vehicles Technology Co., Ltd., Sanmenxia 472000, ChinaZhengzhou Institute of Technology, No. 18, Ying Cai Street, Hui Ji District, Zhengzhou 450044, ChinaThe vibration signals propagating in different directions from rotating machines can contain a variety of characteristic information. A novel feature extraction method based on bivariate empirical mode decomposition (BEMD) for rotor is proposed to comprehensively extract the fault features. In this work, the number of signal projection directions is determined through simulation, and the energy end condition based on the energy threshold is increased using BEMD to enhance the decomposition quality. Mixed vibration signals are generated along two orthogonal directions. Then, the acquired vibration signal can be decomposed into several intrinsic mode functions (IMFs) at the rotational speed using the BEMD method. Furthermore, the instantaneous frequency and instantaneous amplitude of the real signals and the imaginary part of the IMF signals are obtained using the Hilbert transform. The fault features along two and three dimensions can be investigated, providing more comprehensive information to aid in the fault diagnosis of rotor. Experimental results on oil film oscillation, the oil whirl, the bistability of the rotor, and looseness and rotor rubbing composite fault indicate the effectiveness of the proposed method.http://dx.doi.org/10.1155/2019/1639139 |
| spellingShingle | Chuanjin Huang Haijun Song Wenping Lei Zhanya Niu Yajun Meng Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform Shock and Vibration |
| title | Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform |
| title_full | Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform |
| title_fullStr | Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform |
| title_full_unstemmed | Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform |
| title_short | Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform |
| title_sort | instantaneous amplitude frequency feature extraction for rotor fault based on bemd and hilbert transform |
| url | http://dx.doi.org/10.1155/2019/1639139 |
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