利用振動與聲紋訊號診斷醫療用牙科手機氣動轉子之健康狀態

Diagnosing the Health Status of Air-Turbine Dental Handpieces Using the Sound and Vibration Signals

劉昶志(Chang-Chih Liu) ； 黃宜正(Yi-Cheng Huang)

《中華民國振動與噪音工程學會論文集》 2014 (2014/06) Pp. 272-279

摘要

本研究為建立牙科手機氣動轉子健康狀態之診斷方法，運用雷射都卜勒速度計作為振動測量儀器，分析並診斷轉子－軸承呈現正常態與異常態所產生的頻率之差異，藉以判斷牙科手機是否運作正常之依據。同時以電容式麥克風與一般手機來擷取牙科手機轉動之音頻聲音，使用希爾伯特黃轉換（Hilbert-Huang Transform, HHT），粹取牙科手機的聲紋變化，判斷牙科手機內部轉子的運轉健康狀態，對應雷射都普勒之數據是否相同，增加實驗系統診斷之精準度；排除以人耳測試分貝量之判斷準確度。本研究結果成功建立一套氣動牙科手機轉子動態特性之預先診斷的測量系統，判定牙科手機內部零件健康狀態，提供牙科手機製造商或是使用者在了解動態特性及臨床使用之健康診斷依據。

關鍵字

氣動牙科手機 ； 振動 ； 噪音 ； 診斷測量系統

並列摘要

This paper studies the diagnostic results for free-running of the air turbine dental handpieces (ATDH) with different rotor's status through the Fast Fourier Transform (FFT) and Hilbert-Huang transform (HHT) process. The method is tested using the axial preload on rotors and bad ceramic bearing conditions. The sound wave detected by decibel (dB) scale through the microphone for human ear hearing is not easy to weight the health status of the ATDH. FFT was used to identify the preload status and malfunctioned bearing of the rotor of ATDH through the vibration and sound signals. Laser Doppler vibration, condenser microphone and mobile MEMS microphone are used to extract the signal patterns when rotor features of ATDH are changed. The development of preload change or the malfunctioned bearing of the rotors can be discriminated and abstracted via FFT and HHT based on frequency perception. Experimental results show that the proposed approach can successfully predict the prognostic status of the ATDH rotor’s status. The smart sensing for the health of the ATDH is available based on comparative evaluation of FFT and HHT.

並列關鍵字

Air Turbine Dental Handpieces ； Bearing ； FFT ； HHT ； Sound and Vibration Signals