Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform
The problems of the synchroextracting transform method being unable to handle FM signals and being prone to time–frequency feature discontinuity in a strong noise environment are addressed by the construction of a novel rotation synchroextracting chirplet transform under the framework of the synchro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/24/12972 |
| _version_ | 1797461542315229184 |
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| author | Zhifeng Hu Zhinong Li Liying Ge Qinghua Mao Xuhui Zhang |
| author_facet | Zhifeng Hu Zhinong Li Liying Ge Qinghua Mao Xuhui Zhang |
| author_sort | Zhifeng Hu |
| collection | DOAJ |
| description | The problems of the synchroextracting transform method being unable to handle FM signals and being prone to time–frequency feature discontinuity in a strong noise environment are addressed by the construction of a novel rotation synchroextracting chirplet transform under the framework of the synchroextracting transform. The method retains the advantage of the generalized linear chirplet transform that can fit the time–frequency characteristics of the original signal and retains the high precision time–frequency analysis ability of the synchroextracting transform. The simulation results show that the proposed method is obviously superior to the generalized chirplet transform and synchroextracting transform method. The method can obtain the time–frequency energy located at the time–frequency ridges of FM-AM signals and multicomponent signals with crossed-frequency components, and has high time–frequency analysis ability and anti-interference ability. Finally, the proposed method is applied to diagnose mechanical faults. The experimental results further verify the effectiveness of the proposed method, which can effectively extract the characteristic freque.ncy of fault signal. |
| first_indexed | 2024-03-09T17:20:53Z |
| format | Article |
| id | doaj.art-2f047f4f274141a5a498daecb7322765 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T17:20:53Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2f047f4f274141a5a498daecb73227652023-11-24T13:07:57ZengMDPI AGApplied Sciences2076-34172022-12-0112241297210.3390/app122412972Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet TransformZhifeng Hu0Zhinong Li1Liying Ge2Qinghua Mao3Xuhui Zhang4Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang 330063, ChinaKey Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang 330063, ChinaKey Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang 330063, ChinaShaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring, Xi’an University of Science and Technology, Xi’an 710054, ChinaShaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring, Xi’an University of Science and Technology, Xi’an 710054, ChinaThe problems of the synchroextracting transform method being unable to handle FM signals and being prone to time–frequency feature discontinuity in a strong noise environment are addressed by the construction of a novel rotation synchroextracting chirplet transform under the framework of the synchroextracting transform. The method retains the advantage of the generalized linear chirplet transform that can fit the time–frequency characteristics of the original signal and retains the high precision time–frequency analysis ability of the synchroextracting transform. The simulation results show that the proposed method is obviously superior to the generalized chirplet transform and synchroextracting transform method. The method can obtain the time–frequency energy located at the time–frequency ridges of FM-AM signals and multicomponent signals with crossed-frequency components, and has high time–frequency analysis ability and anti-interference ability. Finally, the proposed method is applied to diagnose mechanical faults. The experimental results further verify the effectiveness of the proposed method, which can effectively extract the characteristic freque.ncy of fault signal.https://www.mdpi.com/2076-3417/12/24/12972rotation synchroextracting chirplet transformsynchroextracting transformfault diagnosisgeneralized linear chirplet transform |
| spellingShingle | Zhifeng Hu Zhinong Li Liying Ge Qinghua Mao Xuhui Zhang Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform Applied Sciences rotation synchroextracting chirplet transform synchroextracting transform fault diagnosis generalized linear chirplet transform |
| title | Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform |
| title_full | Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform |
| title_fullStr | Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform |
| title_full_unstemmed | Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform |
| title_short | Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform |
| title_sort | diagnosis method for mechanical faults based on rotation synchroextracting chirplet transform |
| topic | rotation synchroextracting chirplet transform synchroextracting transform fault diagnosis generalized linear chirplet transform |
| url | https://www.mdpi.com/2076-3417/12/24/12972 |
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