@ARTICLE{Thamba_Narendiranath_Babu_Fault_2020,
 author={Thamba, Narendiranath Babu and Thatikonda Venkata, Kiran Kamesh and Nutakki, Sathvik and Duraiswamy, Rama Prabha and Mohammed, Noor and Wahab, Razia Sultana and Mangalaraja, Ramalinga Viswanathan and Manivannan, Ajay Vannan},
 volume={vol. 45},
 number={No 3},
 journal={Archives of Acoustics},
 pages={521-540},
 howpublished={online},
 year={2020},
 publisher={Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics},
 abstract={This research highlights the vibration analysis on worm gears at various conditions of oil using the experimental set up. An experimental rig was developed to facilitate the collection of the vibration signals which consisted of a worm gear box coupled to an AC motor. The four faults were induced in the gear box and the vibration data were collected under full, half and quarter oil conditions. An accelerometer was used to collect the signals and for further analysis of the vibration signals, MATLAB software was used to process the data. Symlet wavelet transform was applied to the raw FFT to compare the features of the data. ANN was implemented to classify various faults and the accuracy is 93.3%.},
 type={Article},
 title={Fault Analysis of Worm Gear Box Using Symlets Wavelet},
 URL={http://ochroma.man.poznan.pl/Content/117163/PDF/aoa.2020.134069.pdf},
 doi={10.24425/aoa.2020.134069},
 keywords={worm gear box, FFT, symlet wavelets, artificial neural network},
}