Vibration signal AM-FM models and spectral characteristics for rotate vector reducer fault diagnosis: an insight into multiple modulations and fault feature analysis

Rotate vector (RV) reducers need to undertake cyclic heavy load, and therefore are prone to faults. However, they feature highly intricate kinematics, due to their complex structure, simultaneous multiple point contacts and coupled spin–revolution of cycloidal and planetary gear stages. This leads to high vibration complexity, and poses a great challenge to vibration based fault diagnosis. To address the above issue, we derive the fault characteristic frequency equations for the main components in both cycloidal and planetary gear stages, including the sun, planets, cycloids and pinwheel. Considering the multiple modulation effects on meshing vibration (including the amplitude modulation and frequency modulation effects due to localized fault, and the extra amplitude modulation effects caused by time-varying measurement angle and vibration transfer path), we establish analytical vibration signal models for the localized fault case of each main component. These analytical signal models provide an insight into the multiple modulation nature of vibrations, and justify the presence of gear rotating and fault characteristic frequencies in vibrations from kinetics perspective. In order to extract fault symptoms from multiple modulation signals, we further derive the explicit equations of Fourier and envelope spectra, thus revealing the fault vibration characteristics explicitly. Such explicit spectral signatures provide a guidance for vibration based fault diagnosis. The above theoretical derivations are validated experimentally. The localized fault of both cycloidal and planetary gear stages is successfully diagnosed.

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Publication Details

Journal
Mechanical Systems and Signal Processing
Published
2026-10-13
DOI
https://doi.org/10.1016/j.ymssp.2026.115080
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Vibration signal AM-FM models and spectral characteristics for rotate vector reducer fault diagnosis: an insight into multiple modulations and fault feature analysis

Zhipeng Feng, Ying Zhang, Rongzhou Lin, Tongxin Gao et al.
Mechanical Systems and Signal Processing
Machine Fault Diagnosis Techniques
article

Vibration signal AM-FM models and spectral characteristics for rotate vector reducer fault diagnosis: an insight into multiple modulations and fault feature analysis

Zhipeng Feng, Ying Zhang, Rongzhou Lin, Tongxin Gao, Zi'an Li
article en

Abstract

Rotate vector (RV) reducers need to undertake cyclic heavy load, and therefore are prone to faults. However, they feature highly intricate kinematics, due to their complex structure, simultaneous multiple point contacts and coupled spin–revolution of cycloidal and planetary gear stages. This leads to high vibration complexity, and poses a great challenge to vibration based fault diagnosis. To address the above issue, we derive the fault characteristic frequency equations for the main components in both cycloidal and planetary gear stages, including the sun, planets, cycloids and pinwheel. Considering the multiple modulation effects on meshing vibration (including the amplitude modulation and frequency modulation effects due to localized fault, and the extra amplitude modulation effects caused by time-varying measurement angle and vibration transfer path), we establish analytical vibration signal models for the localized fault case of each main component. These analytical signal models provide an insight into the multiple modulation nature of vibrations, and justify the presence of gear rotating and fault characteristic frequencies in vibrations from kinetics perspective. In order to extract fault symptoms from multiple modulation signals, we further derive the explicit equations of Fourier and envelope spectra, thus revealing the fault vibration characteristics explicitly. Such explicit spectral signatures provide a guidance for vibration based fault diagnosis. The above theoretical derivations are validated experimentally. The localized fault of both cycloidal and planetary gear stages is successfully diagnosed.

Mechanical Systems and Signal ProcessingVol. 261
China North Industries Group Corporation (China) (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 17%
Machine Fault Diagnosis Techniques
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