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Fault Diagnosis in Bevel Gearbox Using Coiflet Wavelet and Fault Classification Based on ANN Including DNN

  • Research Article-Mechanical Engineering
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Abstract

Condition monitoring plays a vital role in predictive maintenance of machinery in today’s world. It is very important to detect the faults in the machinery as early as possible in order to stop the propagation of faults which may lead to heavy damages. The objective of our study is to investigate the vibration analysis of bevel gearbox to detect the faults. An experimental setup was developed to carry out the vibration analysis. Various types of faults were induced in the gearbox. The vibration analysis was carried out for different types of faults with different lubrication levels in the gearbox. MATLAB toolbox was used for signal processing in which Coiflet wavelet was used for denoising the signal. An artificial neural network (ANN) and a deep neural network (DNN) were used to detect the faults in the bevel gearbox automatically. The results were promising in detecting the faults with high accuracy.

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Abbreviations

ANN:

Artificial neural network

DNN:

Deep neural network

HP:

Horsepower

FFT:

Fast Fourier transform

GMF:

Gear mesh frequency

MSE:

Mean squared error

SNR:

Signal-to-noise ratio

PSNR:

Peak signal-to-noise ratio

RMS:

Root mean square

ROC:

Receiver operating characteristic

RPM:

Revolution per minute

Hz:

Hertz

kHz:

Kilo Hertz

Max:

Maximum

Min:

Minimum

Eq.:

Equation

Sec.:

Section

∑:

Summation

 + ∞:

Positive infinity

 − ∞:

Negative infinity

σ:

Standard deviation

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Authors and Affiliations

  1. School of Mechanical Engineering, Vellore Institute of Technology, Vellore, India

    T. Narendiranath Babu & P. Sahir Nowshad Ali

  2. School of Electrical Engineering, Vellore Institute of Technology, Vellore, India

    D. Rama Prabha & Razia Sultana Wahab

  3. School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    V. Noor Mohammed

  4. School of Social Sciences and Languages, Vellore Institute of Technology, Vellore, India

    S. Vijayalakshmi

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  1. T. Narendiranath Babu
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Correspondence to T. Narendiranath Babu.

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Babu, T.N., Ali, P.S.N., Prabha, D.R. et al. Fault Diagnosis in Bevel Gearbox Using Coiflet Wavelet and Fault Classification Based on ANN Including DNN. Arab J Sci Eng 47, 15823–15849 (2022). https://doi.org/10.1007/s13369-022-06767-9

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