Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault

2021 ◽  
Author(s):  
Yingchao Luo ◽  
Lingli Cui ◽  
Jianyu Zhang ◽  
Jianfeng Ma
Keyword(s):  
Phenomenological Model ◽  
Ring Gear ◽  
Planetary Gearbox ◽  
Gear Fault ◽  
Vibration Mechanism

Vibration Mechanism and Improved Phenomenological Model of Planetary Gearbox with Broken Sun Gear Fault

Measurement ◽  
2021 ◽  
pp. 109356
Author(s):  
Yingchao Luo ◽  
Lingli Cui ◽  
Jianyu Zhang ◽  
Jianfeng Ma
Keyword(s):  
Phenomenological Model ◽  
Planetary Gearbox ◽  
Gear Fault ◽  
Vibration Mechanism

scholarly journals Planetary Gearbox Fault Diagnosis Using Envelope Manifold Demodulation

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Weigang Wen ◽  
Robert X. Gao ◽  
Weidong Cheng
Keyword(s):  
Fault Diagnosis ◽  
Frequency Band ◽  
Manifold Learning ◽  
Planetary Gear ◽  
Vibration Signal ◽  
Planetary Gearbox ◽  
Characteristic Extraction ◽  
Gear Fault ◽  
Planet Gear ◽  
Fault Characteristic

The important issue in planetary gear fault diagnosis is to extract the dependable fault characteristics from the noisy vibration signal of planetary gearbox. To address this critical problem, an envelope manifold demodulation method is proposed for planetary gear fault detection in the paper. This method combines complex wavelet, manifold learning, and frequency spectrogram to implement planetary gear fault characteristic extraction. The vibration signal of planetary gear is demodulated by wavelet enveloping. The envelope energy is adopted as an indicator to select meshing frequency band. Manifold learning is utilized to reduce the effect of noise within meshing frequency band. The fault characteristic frequency of the planetary gear is shown by spectrogram. The planetary gearbox model and test rig are established and experiments with planet gear faults are conducted for verification. All results of experiment analysis demonstrate its effectiveness and reliability.

scholarly journals Alpha Stable Distribution Based Morphological Filter for Bearing and Gear Fault Diagnosis in Nuclear Power Plant

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Xinghui Zhang ◽  
Jianshe Kang ◽  
Lei Xiao ◽  
Jianmin Zhao
Keyword(s):  
Fault Diagnosis ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Stable Distribution ◽  
Planetary Gearbox ◽  
Alpha Stable Distribution ◽  
Gear Fault

Gear and bearing play an important role as key components of rotating machinery power transmission systems in nuclear power plants. Their state conditions are very important for safety and normal operation of entire nuclear power plant. Vibration based condition monitoring is more complicated for the gear and bearing of planetary gearbox than those of fixed-axis gearbox. Many theoretical and engineering challenges in planetary gearbox fault diagnosis have not yet been resolved which are of great importance for nuclear power plants. A detailed vibration condition monitoring review of planetary gearbox used in nuclear power plants is conducted in this paper. A new fault diagnosis method of planetary gearbox gears is proposed. Bearing fault data, bearing simulation data, and gear fault data are used to test the new method. Signals preprocessed using dilation-erosion gradient filter and fast Fourier transform for fault information extraction. The length of structuring element (SE) of dilation-erosion gradient filter is optimized by alpha stable distribution. Method experimental verification confirmed that parameter alpha is superior compared to kurtosis since it can reflect the form of entire signal and it cannot be influenced by noise similar to impulse.

scholarly journals An Improved Phenomenological Model of the Planetary Gearbox Based on Meshing Vibration Characteristics

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 103462-103475
Author(s):  
Yingchao Luo ◽  
Lingli Cui ◽  
Jianfeng Ma
Keyword(s):  
Phenomenological Model ◽  
Vibration Characteristics ◽  
Planetary Gearbox

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.

scholarly journals Application of Reassigned Wavelet Scalogram in Wind Turbine Planetary Gearbox Fault Diagnosis under Nonstationary Conditions

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaowang Chen ◽  
Zhipeng Feng
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Frequency Resolution ◽  
Vibration Signals ◽  
Cross Term ◽  
Planetary Gearbox ◽  
Time Frequency ◽  
Gear Fault ◽  
Nonstationary Conditions

Wind turbine planetary gearboxes often run under nonstationary conditions due to volatile wind conditions, thus resulting in nonstationary vibration signals. Time-frequency analysis gives insight into the structure of an arbitrary nonstationary signal in joint time-frequency domain, but conventional time-frequency representations suffer from either time-frequency smearing or cross-term interferences. Reassigned wavelet scalogram has merits of fine time-frequency resolution and cross-term free nature but has very limited applications in machinery fault diagnosis. In this paper, we use reassigned wavelet scalogram to extract fault feature from wind turbine planetary gearbox vibration signals. Both experimental and in situ vibration signals are used to evaluate the effectiveness of reassigned wavelet scalogram in fault diagnosis of wind turbine planetary gearbox. For experimental evaluation, the gear characteristic instantaneous frequency curves on time-frequency plane are clearly pinpointed in both local and distributed sun gear fault cases. For in situ evaluation, the periodical impulses due to planet gear fault are also clearly identified. The results verify the feasibility and effectiveness of reassigned wavelet scalogram in planetary gearbox fault diagnosis under nonstationary conditions.

Gearbox Fault Simulation and Analysis Based on Virtual Prototype Technology

2013 ◽  
Vol 819 ◽  
pp. 373-378
Author(s):  
Xue Chen ◽  
Ling Li Cui
Keyword(s):  
Fault Simulation ◽  
Vibration Signal ◽  
Coupling Model ◽  
Virtual Prototype ◽  
Frequency Domain Analysis ◽  
Matlab Simulation ◽  
Signal Modulation ◽  
Gear Fault ◽  
Vibration Mechanism ◽  
Virtual Prototype Technology

Simulation study of the failure of gearbox system using virtual prototype technology and analysis of its vibration signal is a foreword topic in recent years. This paper established a rigid-flexible coupling model of gearbox system using SolidWorks, ANSYS and ADAMS. Then, make simulation under the following three conditions: normal, gear fault and bearing outer ring fault. Next, make time domain and frequency domain analysis of the simulated fault signal using MATLAB. Simulation results are consistent with gear vibration mechanism and signal modulation theory, which verified correctness and feasibility of virtual prototype technology in gearbox fault simulation. Lay foundation for gearbox fault diagnosis.

scholarly journals Fault Diagnosis of Planet Gear Using Continuous Vibration Separation and Minimum Entropy Deconvolution

2020 ◽  
Vol 10 (22) ◽  
pp. 8062
Author(s):  
Jian Shen ◽  
Lun Zhang ◽  
Niaoqing Hu
Keyword(s):  
Fault Diagnosis ◽  
Planetary Gear ◽  
Dynamic Responses ◽  
Minimum Entropy ◽  
Modulation Effect ◽  
Dynamic Component ◽  
Planetary Gearbox ◽  
Gear Fault ◽  
Vibration Responses ◽  
Planet Gear

Planet gear is the most unique dynamic component in planetary gearbox. It rotates around sun gear while rotating around its own central axis, causing modulation effect in monitoring signal. Planetary gear is usually connected to heavy external loads and other transmissions, fault feature of planet gear may be overwhelmed by noises and other signals. Focused on planet gear inside planetary gearbox, a method for fault diagnosis is proposed in this paper based on continuous vibration separation (CVS) and minimum entropy deconvolution (MED). In this method, CVS is designed to separate dynamic responses of planet gear from overall vibration responses of planetary gearbox by overcoming the modulation effect and depressing noises. MED is used for enhancement detection of fault-related impulses. Simulations and experiments are conducted to collect signals for analysis. The proposed method is also compared with vibration separation method (VS). Both simulation and experiment analysis indicate that the proposed planet gear fault diagnosis method is effective. Comparative study indicates that CVS-MED method improves VS by keeping signal periodicity while overcoming modulation effect and depressing noises.

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