An Order Analysis Based Second-Order Cyclic Function Technique for Planetary Gear Fault Detection

Motor current signature analysis (MCSA) is a useful technique for planetary gear fault detection. Motor current signals have easier accessibility and are free from time-varying transfer path effects. If the fault symptoms in current signals are well understood, it will be more beneficial to develop effective current signal processing methods. Some researchers have developed mathematical models to study the characteristics of current signals. However, no one has considered the coupling of rotor eccentricity and gear failures, resulting in an inaccurate analysis of the current signals. This study considers the sun gear failure of a planetary gearbox and the eccentricity of the motor rotor. An improved induction motor model is proposed based on the magnetomotive force (MMF) to simulate the stator current. By analyzing the current, the modulation relationships of gearbox meshing frequency, fault frequency, power supply frequency, and gear rotating frequency are obtained. The proposed model is validated to some extent using experimental data.

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Planetary Gear Fault Detection Based on Mechanical Torque and Stator Current Signatures of a Wound Rotor Induction Generator

IEEE Transactions on Energy Conversion ◽

10.1109/tec.2018.2811044 ◽

2018 ◽

Vol 33 (3) ◽

pp. 1072-1085 ◽

Cited By ~ 12

Author(s):

Mohammad Hoseintabar Marzebali ◽

Jawad Faiz ◽

Gerard-Andre Capolino ◽

Shahin Hedayati Kia ◽

Humberto Henao

Keyword(s):

Fault Detection ◽

Planetary Gear ◽

Induction Generator ◽

Stator Current ◽

Gear Fault ◽

Current Signatures

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Torsional vibration signal analysis as a diagnostic tool for planetary gear fault detection

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2017.07.038 ◽

2018 ◽

Vol 100 ◽

pp. 706-728 ◽

Cited By ~ 23

Author(s):

Song Xue ◽

Ian Howard

Keyword(s):

Fault Detection ◽

Torsional Vibration ◽

Diagnostic Tool ◽

Signal Analysis ◽

Planetary Gear ◽

Vibration Signal ◽

Gear Fault ◽

Vibration Signal Analysis

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Helicopter main reduction planetary gear fault diagnosis method based on SVDD

International Journal of Applied Electromagnetics and Mechanics ◽

10.3233/jae-209316 ◽

2020 ◽

Vol 64 (1-4) ◽

pp. 137-145

Author(s):

Yubin Xia ◽

Dakai Liang ◽

Guo Zheng ◽

Jingling Wang ◽

Jie Zeng

Keyword(s):

Fault Diagnosis ◽

Planetary Gear ◽

Gaussian Kernel ◽

Support Vector ◽

Support Vector Data Description ◽

Vector Data ◽

Energy Characteristics ◽

Gear Fault ◽

Channel Information ◽

Diagnosis Method

Aiming at the irregularity of the fault characteristics of the helicopter main reducer planetary gear, a fault diagnosis method based on support vector data description (SVDD) is proposed. The working condition of the helicopter is complex and changeable, and the fault characteristics of the planetary gear also show irregularity with the change of working conditions. It is impossible to diagnose the fault by the regularity of a single fault feature; so a method of SVDD based on Gaussian kernel function is used. By connecting the energy characteristics and fault characteristics of the helicopter main reducer running state signal and performing vector quantization, the planetary gear of the helicopter main reducer is characterized, and simultaneously couple the multi-channel information, which can accurately characterize the operational state of the planetary gear’s state.

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