Prognostic diagnosis of the health status of an air-turbine dental handpiece rotor by using sound and vibration signals

Huang Yi-Cheng, Liu Chang-Chih, Chuo Po-Chou

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper reports the diagnostic results of a free-running of air turbine dental handpiece (ATDH) with three rotor statuses by applying fast Fourier transform (FFT), Hilbert-Huang transform (HHT), and multiscale entropy (MSE) processes. The proposed method was tested under conditions of additional axial preload on the rotor and ceramic bearings with a damaged outer race supporting the rotor. A laser-Doppler vibrometer, condenser microphone, and portable MEMS system microphone were used to acquire the signals when the ATDH rotor features were changed. The results showed that changes in preload or malfunctioning ball bearings can be discriminated and abstracted using FFT and HHT to analyze the vibration frequencies. The experimental results showed that the proposed method can successfully predict the prognostic status of an ATDH rotor. The smart sensing of the health of the ATDH was achieved through a comparative evaluation of the MSE values. The proposed diagnostic method yielded satisfactory prognostic effectiveness in predicting the health status of the tested ATDH rotor.

Original languageEnglish
Pages (from-to)1514-1524
Number of pages11
JournalJournal of Vibroengineering
Volume18
Issue number3
DOIs
Publication statusPublished - 2016 Jan 1

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Compressed air motors
Vibrations (mechanical)
Rotors
Health
Acoustic waves
Microphones
Fast Fourier transforms
Entropy
Bearings (structural)
Ball bearings
MEMS
Lasers

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Mechanical Engineering

Cite this

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abstract = "This paper reports the diagnostic results of a free-running of air turbine dental handpiece (ATDH) with three rotor statuses by applying fast Fourier transform (FFT), Hilbert-Huang transform (HHT), and multiscale entropy (MSE) processes. The proposed method was tested under conditions of additional axial preload on the rotor and ceramic bearings with a damaged outer race supporting the rotor. A laser-Doppler vibrometer, condenser microphone, and portable MEMS system microphone were used to acquire the signals when the ATDH rotor features were changed. The results showed that changes in preload or malfunctioning ball bearings can be discriminated and abstracted using FFT and HHT to analyze the vibration frequencies. The experimental results showed that the proposed method can successfully predict the prognostic status of an ATDH rotor. The smart sensing of the health of the ATDH was achieved through a comparative evaluation of the MSE values. The proposed diagnostic method yielded satisfactory prognostic effectiveness in predicting the health status of the tested ATDH rotor.",
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Prognostic diagnosis of the health status of an air-turbine dental handpiece rotor by using sound and vibration signals. / Yi-Cheng, Huang; Chang-Chih, Liu; Po-Chou, Chuo.

In: Journal of Vibroengineering, Vol. 18, No. 3, 01.01.2016, p. 1514-1524.

Research output: Contribution to journalArticle

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