Gear fault diagnosis method based on local mean decomposition and generalized morphological fractal dimensions

2015 ◽  
Vol 91 ◽  
pp. 151-167 ◽  
Author(s):  
Zhi Zheng ◽  
Wanlu Jiang ◽  
Zhenwei Wang ◽  
Yong Zhu ◽  
Kai Yang
Keyword(s):  
Fault Diagnosis ◽  
Fractal Dimensions ◽  
Local Mean Decomposition ◽  
Gear Fault ◽  
Diagnosis Method ◽  
Local Mean ◽  
Gear Fault Diagnosis

The Application of Local Mean Decomposition and Variable Predictive Model-Based Class Discriminate in Gear Fault Diagnosis

2014 ◽  
Vol 1014 ◽  
pp. 510-515 ◽  
Author(s):  
You Cai Xu ◽  
Xin Shi Li ◽  
Ran Tao ◽  
Shu Guo ◽  
Min Gou ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Predictive Model ◽  
Feature Vector ◽  
Local Mean Decomposition ◽  
Outer Race ◽  
Model Based ◽  
Gear Fault ◽  
Local Mean ◽  
Gear Fault Diagnosis ◽  
Non Stationary Signal

The time-domain energy message conveyed by vibration signals of different gear fault are different, so a method based on local mean decomposition (LMD) and variable predictive model-based class discriminate (VPMCD) is proposed to diagnose gear fault model. The vibration signal of gear which is the research object in this paper is decomposed into a series of product functions (PF) by LMD method. Then a further analysis is to select the PF components which contain main fault information of gear, the energy feature parameters of the selected PF components are used to form a fault feature vector. The variable predictive model-based class discriminate is a new multivariate classification approach for pattern recognition, through taking fully advantages of the fault feature vector. Finally, gear fault diagnosis is distinguished into normal state, inner race fault and outer race fault. The results show that LMD method can decompose a complex non-stationary signal into a number of PF components whose frequency is from high to low. And the method based on LMD and VPMCD has a high fault recognition function by analyzing the fault feature vector of PF.

A Demodulating Approach Based on Local Mean Decomposition and Combined Morlet Wavelets and its Application in Mechanical Fault Diagnosis

2012 ◽  
Vol 239-240 ◽  
pp. 1039-1044
Author(s):  
Hui Mei Li ◽  
Zhao Zhong Cai ◽  
Gang An
Keyword(s):  
Numerical Simulation ◽  
Fault Diagnosis ◽  
Adaptive Filtering ◽  
Local Mean Decomposition ◽  
Gear Fault ◽  
Local Mean ◽  
Gear Fault Diagnosis

Local mean decomposition(LMD) as a new demodulating approach has some problems needing study and solution.This paper analyzed the overlapping phenomenon of product functions(PFs) generated when LMD decomposes signals through studying the adaptive filtering characteristic of LMD and numerical simulation. The results show that the overlapping phenomenon of PFs is general. Then in order to improve the demodulating effect of LMD, a new demodulating method based on LMD and combined Morlet wavelets was proposed and applied in gear fault diagnosis. The results show that this method is efficient.

Gear Fault Diagnosis Methods Based on EMD and HMM

2013 ◽  
Vol 333-335 ◽  
pp. 1684-1687
Author(s):  
Bin Wu ◽  
Song He Zhang ◽  
Yue Gang Luo ◽  
Shan Ping Yu
Keyword(s):  
Fault Diagnosis ◽  
Vibration Signal ◽  
Modulation Amplitude ◽  
Double Frequency ◽  
Gear Mesh ◽  
Gear Fault ◽  
Diagnosis Method ◽  
Modulation Signal ◽  
Gear Fault Diagnosis ◽  
Modulation Sideband

Due to the feature and the forms of motion of the gears, the vibration signal of the gear is mainly the frequency modulation, amplitude modulation, or hybrid modulation signal corresponding to the gear-mesh frequency and its double frequency signal. When faults arise on the gears, the number and shape of the modulation sideband will be changed. The structures and forms of the FM composition differ according to the type of faults. According to the above mentioned characteristic, this essay raises a method to disassemble the gear vibrate signal, points out the formulas to build up characteristic vector, on that basis, the essay raised a gear fault diagnosis method based on EMD and Hidden Markov Model (HMM), this method can identify the working condition of the normal gears, snaggletooth gears, and pitting gears.

A Novel Marine Gear Fault Diagnosis Method Based on VMD and MDE

2021 ◽  
Author(s):  
Xiaolong Zhou ◽  
Gang Liu ◽  
Xianliang Liu ◽  
Weidong Zhang
Keyword(s):  
Fault Diagnosis ◽  
Gear Fault ◽  
Diagnosis Method ◽  
Gear Fault Diagnosis

Maximum envelope-based Autogram and Symplectic geometry mode decomposition based gear fault diagnosis method

Measurement ◽  
2020 ◽  
pp. 108575
Author(s):  
Xinglong Wang ◽  
Jinde Zheng ◽  
Haiyang Pan ◽  
Qingyun Liu ◽  
Chengjun Wang
Keyword(s):  
Fault Diagnosis ◽  
Symplectic Geometry ◽  
Mode Decomposition ◽  
Gear Fault ◽  
Diagnosis Method ◽  
Gear Fault Diagnosis
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