Diagnosis of Localized Faults in Multistage Gearboxes: A Vibrational Approach by Means of Automatic EMD-Based Algorithm

M Buzzoni,E Mucchi,G Dalpiaz,G D’Elia

doi:10.1155/2017/8345704

Abstract

The gear fault diagnosis on multistage gearboxes by vibration analysis is a challenging task due to the complexity of the vibration signal. The localization of the gear fault occurring in a wheel located in the intermediate shaft can be particularly complex due to the superposition of the vibration signature of the synchronous wheels. Indeed, the gear fault detection is commonly restricted to the identification of the stage containing the faulty gear rather than the faulty gear itself. In this context, the paper advances a methodology which combines the Empirical Mode Decomposition and the Time Synchronous Average in order to separate the vibration signals of the synchronous gears mounted on the same shaft. The physical meaningful modes are selected by means of a criterion based on Pearson’s coefficients and the fault detection is performed by dedicated condition indicators. The proposed method is validated taking into account simulated vibrations signals and real ones.

Highlights

Multistage gearboxes are employed in a wide range of mechanical systems and represent crucial components for the correct functioning of the entire machine
The state of the art about the identification of localized gear faults covers a wide range of different approaches such as the following: the cyclostationary theory [2,3,4], which takes advantage of the hidden periods embodied in the vibration signals; the Kurtogram [5] for the selection of the frequency band associated with the maximum Spectral Kurtosis; time-frequency signal representations like Continuous Wavelet Transform [6]; the blind deconvolution algorithms [7, 8], which estimate the excitation source due to the presence of the fault from the noisy observation; condition indicators based on the Time Synchronous Average [9]
The gear fault detection is restricted to the identification of the stage containing the faulty gear rather than the faulty gear itself

Summary

Introduction

Multistage gearboxes are employed in a wide range of mechanical systems and represent crucial components for the correct functioning of the entire machine Since they are often subjected to faults due to manufacturing errors or heavy working conditions, the gear fault identification is of prime importance in order to reduce the maintenance costs as well as to restrict machine downtimes. In this context, the exact knowledge of the fault position by means of nondestructive techniques simplifies the maintenance process avoiding burdensome visual inspections. The state of the art about the identification of localized gear faults covers a wide range of different approaches such as the following: the cyclostationary theory [2,3,4], which takes advantage of the hidden periods embodied in the vibration signals; the Kurtogram [5] for the selection of the frequency band associated with the maximum Spectral Kurtosis; time-frequency signal representations like Continuous Wavelet Transform [6]; the blind deconvolution algorithms [7, 8], which estimate the excitation source due to the presence of the fault from the noisy observation; condition indicators based on the Time Synchronous Average [9]

Objectives

Results

Conclusion