Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application
Instantaneous rotating frequency extraction is one of the key technologies for mechanical health monitoring and fault diagnosis. As the instantaneous rotating frequency presents fast-varying property under high-speed fluctuation, this paper uses a coarse-to-fine strategy to propose a tacholess fast-...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-09-01
|
| Series: | Journal of Low Frequency Noise, Vibration and Active Control |
| Online Access: | https://doi.org/10.1177/14613484251320211 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849233722734280704 |
|---|---|
| author | Lu Yan Tian Zhong Lan Shi Li Yang Qin Xiao Chen Jin Wei Bie |
| author_facet | Lu Yan Tian Zhong Lan Shi Li Yang Qin Xiao Chen Jin Wei Bie |
| author_sort | Lu Yan |
| collection | DOAJ |
| description | Instantaneous rotating frequency extraction is one of the key technologies for mechanical health monitoring and fault diagnosis. As the instantaneous rotating frequency presents fast-varying property under high-speed fluctuation, this paper uses a coarse-to-fine strategy to propose a tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform (NLSTFT) combination with adaptive chirp mode decomposition (ACMD). By self-adaptive matching and decomposing the vibration signal based on its time-frequency distribution, it increases the energy aggregation of time-frequency representation, which not only improves computational efficiency but also avoids the spectral ambiguity problem. As a result, the proposed model is very suitable for extracting instantaneous rotating frequency under severe speed fluctuation; simulation signal and rolling bearing fault vibration signal also validate this conclusion. Furthermore, by integrating with signal decomposition technology, various order components of fault vibration signal can also be self-adaptive extracted. |
| format | Article |
| id | doaj-art-3d173b10cfdd4508ae993edc36aaacee |
| institution | Kabale University |
| issn | 1461-3484 2048-4046 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of Low Frequency Noise, Vibration and Active Control |
| spelling | doaj-art-3d173b10cfdd4508ae993edc36aaacee2025-08-20T04:03:26ZengSAGE PublishingJournal of Low Frequency Noise, Vibration and Active Control1461-34842048-40462025-09-014410.1177/14613484251320211Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its applicationLu YanTian Zhong LanShi Li YangQin Xiao ChenJin Wei BieInstantaneous rotating frequency extraction is one of the key technologies for mechanical health monitoring and fault diagnosis. As the instantaneous rotating frequency presents fast-varying property under high-speed fluctuation, this paper uses a coarse-to-fine strategy to propose a tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform (NLSTFT) combination with adaptive chirp mode decomposition (ACMD). By self-adaptive matching and decomposing the vibration signal based on its time-frequency distribution, it increases the energy aggregation of time-frequency representation, which not only improves computational efficiency but also avoids the spectral ambiguity problem. As a result, the proposed model is very suitable for extracting instantaneous rotating frequency under severe speed fluctuation; simulation signal and rolling bearing fault vibration signal also validate this conclusion. Furthermore, by integrating with signal decomposition technology, various order components of fault vibration signal can also be self-adaptive extracted.https://doi.org/10.1177/14613484251320211 |
| spellingShingle | Lu Yan Tian Zhong Lan Shi Li Yang Qin Xiao Chen Jin Wei Bie Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application Journal of Low Frequency Noise, Vibration and Active Control |
| title | Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application |
| title_full | Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application |
| title_fullStr | Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application |
| title_full_unstemmed | Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application |
| title_short | Research on tacholess fast-varying instantaneous rotating frequency estimation model based on nonlinear short-time Fourier transform combination with adaptive chirp mode decomposition and its application |
| title_sort | research on tacholess fast varying instantaneous rotating frequency estimation model based on nonlinear short time fourier transform combination with adaptive chirp mode decomposition and its application |
| url | https://doi.org/10.1177/14613484251320211 |
| work_keys_str_mv | AT luyan researchontacholessfastvaryinginstantaneousrotatingfrequencyestimationmodelbasedonnonlinearshorttimefouriertransformcombinationwithadaptivechirpmodedecompositionanditsapplication AT tianzhonglan researchontacholessfastvaryinginstantaneousrotatingfrequencyestimationmodelbasedonnonlinearshorttimefouriertransformcombinationwithadaptivechirpmodedecompositionanditsapplication AT shiliyang researchontacholessfastvaryinginstantaneousrotatingfrequencyestimationmodelbasedonnonlinearshorttimefouriertransformcombinationwithadaptivechirpmodedecompositionanditsapplication AT qinxiaochen researchontacholessfastvaryinginstantaneousrotatingfrequencyestimationmodelbasedonnonlinearshorttimefouriertransformcombinationwithadaptivechirpmodedecompositionanditsapplication AT jinweibie researchontacholessfastvaryinginstantaneousrotatingfrequencyestimationmodelbasedonnonlinearshorttimefouriertransformcombinationwithadaptivechirpmodedecompositionanditsapplication |