A positive energy residual (PER) based planetary gear fault detection method under variable speed conditions

2019 ◽  
Vol 117 ◽  
pp. 347-360 ◽  
Author(s):  
Jungho Park ◽  
Moussa Hamadache ◽  
Jong M. Ha ◽  
Yunhan Kim ◽  
Kyumin Na ◽  
...  
Keyword(s):  
Fault Detection ◽  
Detection Method ◽  
Planetary Gear ◽  
Positive Energy ◽  
Variable Speed ◽  
Gear Fault

A Gear Fault Detection Method Based on a Fiber Bragg Grating Sensor

2020 ◽  
Vol 47 (3) ◽  
pp. 0304007
Author(s):  
陈勇 Chen Yong ◽  
陈亚武 Chen Yawu ◽  
刘志强 Liu Zhiqiang ◽  
刘焕淋 Liu Huanlin
Keyword(s):  
Fault Detection ◽  
Fiber Bragg Grating ◽  
Detection Method ◽  
Fiber Bragg Grating Sensor ◽  
Bragg Grating ◽  
Gear Fault ◽  
Bragg Grating Sensor

Ground Fault Detection Method for Variable Speed Drives

2021 ◽  
pp. 1-1
Author(s):  
Jose Manuel Guerrero ◽  
Gustavo Navarro ◽  
Kumar Mahtani ◽  
Carlos Antonio Platero
Keyword(s):  
Fault Detection ◽  
Detection Method ◽  
Variable Speed ◽  
Variable Speed Drives ◽  
Ground Fault ◽  
Ground Fault Detection

A Gear Chain Fault Detection Method Using an Adaptive Interference Canceling

2007 ◽  
Vol 345-346 ◽  
pp. 1303-1306
Author(s):  
Bum Won Bae ◽  
In Pil Kang ◽  
Yeon Sun Choi
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Detection Method ◽  
Gear Tooth ◽  
Vibration Signal ◽  
Gear Fault ◽  
Diagnosis Method ◽  
Vibration Signal Analysis ◽  
Processing Techniques ◽  
Signal Processing Techniques

A fault diagnosis method based on wavelet and adaptive interference canceling is presented for the identification of a damaged gear tooth. A damaged tooth of a certain gear chain generates impulsive signals that could be informative to fault detections. Many publications are available not only for the impulsive vibration signal analysis but the application of signal processing techniques to the impulsive signal detections. However, most of the studies about the gear fault detection using the impulsive vibration signals of a driving gear chain are limited to the verification of damage existence on a gear pair. Requirements for more advanced method locating damaged tooth in a driving gear chain should be a motivation of further studies. In this work an adaptive interference canceling combined with wavelet method is used for a successful identification of the damaged tooth location. An application of the wavelet technique provides a superior resolution for the damage detection to the traditional frequency spectrum based methods. An analysis and experiment with three pair gear chain show the feasibility of this study yielding a precise location of the damaged gear tooth.

scholarly journals Research on the Electromagnetic Conversion Method of Stator Current for Local Fault Detection of a Planetary Gearbox

Machines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 277
Author(s):  
Xiangyang Xu ◽  
Guanrui Liu ◽  
Xihui Liang
Keyword(s):  
Fault Detection ◽  
Planetary Gear ◽  
Magnetomotive Force ◽  
Planetary Gearbox ◽  
Transfer Path ◽  
Stator Current ◽  
Motor Current ◽  
Gear Fault ◽  
Motor Current Signature Analysis ◽  
Signal Processing Methods

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.

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

2018 ◽  
Vol 33 (3) ◽  
pp. 1072-1085 ◽  
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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