A novel tacholess order tracking method for planetary gearbox fault detection under variable rotational speed conditions

Abstract Planetary gearboxes generally operate under variable speed conditions in response to actual industrial production requirements, which is prone to cause single or compound faults. The planetary gearbox fault signal exhibits time-varying, weak and complex characteristics under varying conditions, and common diagnostic approaches are difficult to effectively extract and reveal fault-related features. In addition, the computed order tracking requires a speed signal as an auxiliary calculation. Unfortunately, due to economic and installation space limitations, encoders and tachometers are not always available, which poses a huge challenge for extracting variable speed planetary gearbox faults. To tackle these challenges, a novel tacholess order tracking method based on improved adaptive chirp mode decomposition (IACMD) and adaptive maximum second-order cyclostationarity blind deconvolution (CYCBD) is proposed in this contribution for diagnosing planetary gearbox single and composite faults. First, the IACMD algorithm is utilized to adaptively decompose the fault signal, which constructs a composite index (CI)-based signal mode selection and recombination scheme to perform optimal modal decomposition. Second, the instantaneous dominant meshing multiply trend line with obvious amplitude advantage is extracted from the time–frequency representation of the original fault signal, and then converted to the reference shaft rotation frequency to perform angle domain resampling on the sensitive model with the highest CI value. Third, the adaptive CYCBD is adopted to deconvolute the angular domain sensitive modal to heighten the weak fault signatures. Finally, the envelope spectrum of the improved signal is utilized to identify prominent fault characteristic orders and ascertain failure types. Both numerical simulations and practical engineering data for different planetary gearbox failure cases have been thoroughly examined to demonstrate the correctness and feasibility of the proposed approach. Moreover, comparison with some existing technologies demonstrates the superiority of the proposed approach.

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Publication Details

Journal
Measurement Science and Technology
Published
2025-02-26
DOI
https://doi.org/10.1088/1361-6501/adba7c
Citations
1
Primary Topic
Gear and Bearing Dynamics Analysis
Type
article
Field-Weighted Citation Impact
0.71

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article

A novel tacholess order tracking method for planetary gearbox fault detection under variable rotational speed conditions

Yuanyuan Huang, Hongkun Li, Wang Li-jun, Chaoge Wang et al.
1 citations
Measurement Science and Technology
Gear and Bearing Dynamics Analysis
0.71
article

A novel tacholess order tracking method for planetary gearbox fault detection under variable rotational speed conditions

Yuanyuan Huang, Hongkun Li, Wang Li-jun, Chaoge Wang, Ran Wang
article en
1 citations

Abstract

Abstract Planetary gearboxes generally operate under variable speed conditions in response to actual industrial production requirements, which is prone to cause single or compound faults. The planetary gearbox fault signal exhibits time-varying, weak and complex characteristics under varying conditions, and common diagnostic approaches are difficult to effectively extract and reveal fault-related features. In addition, the computed order tracking requires a speed signal as an auxiliary calculation. Unfortunately, due to economic and installation space limitations, encoders and tachometers are not always available, which poses a huge challenge for extracting variable speed planetary gearbox faults. To tackle these challenges, a novel tacholess order tracking method based on improved adaptive chirp mode decomposition (IACMD) and adaptive maximum second-order cyclostationarity blind deconvolution (CYCBD) is proposed in this contribution for diagnosing planetary gearbox single and composite faults. First, the IACMD algorithm is utilized to adaptively decompose the fault signal, which constructs a composite index (CI)-based signal mode selection and recombination scheme to perform optimal modal decomposition. Second, the instantaneous dominant meshing multiply trend line with obvious amplitude advantage is extracted from the time–frequency representation of the original fault signal, and then converted to the reference shaft rotation frequency to perform angle domain resampling on the sensitive model with the highest CI value. Third, the adaptive CYCBD is adopted to deconvolute the angular domain sensitive modal to heighten the weak fault signatures. Finally, the envelope spectrum of the improved signal is utilized to identify prominent fault characteristic orders and ascertain failure types. Both numerical simulations and practical engineering data for different planetary gearbox failure cases have been thoroughly examined to demonstrate the correctness and feasibility of the proposed approach. Moreover, comparison with some existing technologies demonstrates the superiority of the proposed approach.

Measurement Science and TechnologyVol. 36(3)
North China University of Water Resources and Electric Power (CN), Dalian University of Technology (CN), China General Nuclear Power Corporation (China) (CN), Institute of Nuclear Power Operations (US), Shanghai Maritime University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 36%
Gear and Bearing Dynamics Analysis
0.71
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