Planetary Gearbox Fault Detection Under Speed-Varying Conditions With Angular-Domain Cyclostationary Feature Mode Decomposition

Planetary gearbox fault diagnosis under variable-speed operational conditions still presents several difficulties. To overcome this issue, this paper investigates an approach, angular domain cyclostationary feature mode decomposition (ACFMD), for fault detection in planetary gear systems using built-in encoder signals. The encoder signal is applied to capture torsional vibration characteristics and rotational phase information of the reference shaft for transient fault analysis. Firstly, the decomposition directions of the candidate modes are determined by constructing a series of different initialized filters. Then, the angular weighting indicator of second-order cyclostationary is applied as the optimization objective of the mode update. Finally, the fault impulses component can be accurately locked and extracted after iteratively performing mode update and selection processes without angular domain resampling. The effectiveness of ACFMD in accurately identifying fault signatures under time-varying speed conditions is verified through both simulation and case studies. The proposed ACFMD significantly enhances the applicability of FMD theory for fault detection under non-stationary situations.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-08-26
DOI
https://doi.org/10.1109/jsen.2025.3600841
Citations
1
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
1.21

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Planetary Gearbox Fault Detection Under Speed-Varying Conditions With Angular-Domain Cyclostationary Feature Mode Decomposition

Jiajun Zuo, Yonghao Miao, Jing Lin
1 citations
IEEE Sensors Journal
Machine Fault Diagnosis Techniques
1.21
article

Planetary Gearbox Fault Detection Under Speed-Varying Conditions With Angular-Domain Cyclostationary Feature Mode Decomposition

Jiajun Zuo, Yonghao Miao, Jing Lin
article en
1 citations

Abstract

Planetary gearbox fault diagnosis under variable-speed operational conditions still presents several difficulties. To overcome this issue, this paper investigates an approach, angular domain cyclostationary feature mode decomposition (ACFMD), for fault detection in planetary gear systems using built-in encoder signals. The encoder signal is applied to capture torsional vibration characteristics and rotational phase information of the reference shaft for transient fault analysis. Firstly, the decomposition directions of the candidate modes are determined by constructing a series of different initialized filters. Then, the angular weighting indicator of second-order cyclostationary is applied as the optimization objective of the mode update. Finally, the fault impulses component can be accurately locked and extracted after iteratively performing mode update and selection processes without angular domain resampling. The effectiveness of ACFMD in accurately identifying fault signatures under time-varying speed conditions is verified through both simulation and case studies. The proposed ACFMD significantly enhances the applicability of FMD theory for fault detection under non-stationary situations.

IEEE Sensors JournalVol. 25(19)
Beihang University (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 18%
Machine Fault Diagnosis Techniques
1.21
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Planetary Gearbox Fault Detection Under Speed-Varying Conditions With Angular-Domain Cyclostationary Feature Mode Decomposition — Jiajun Zuo, Yonghao Miao, et al. · IEEE Sensors Journal (2025) | TGRS Research Map | TGRS