Fault analysis of worm gear box using symlets wavelet

Narendiranath Babu THAMBA, Kiran Kamesh THATIKONDA VENKATA, Sathvik NUTAKKI, Rama Prabha DURAISWAMY, Noor MOHAMMED, Razia Sultana WAHAB, Ramalinga Viswanathan MANGALARAJA, Ajay Vannan MANIVANNAN

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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%.

Original languageEnglish
Pages (from-to)521-540
Number of pages20
JournalArchives of Acoustics
Issue number3
StatePublished - 2020
Externally publishedYes


  • Artificial neural network
  • FFT
  • Symlet wavelets
  • Worm gear box


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