The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
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Development of diagnosis index for tick/click and tone noise of blower motor using vibration signals

진동 신호를 이용한 블로워 모터 틱/클릭과 톤 소음의 진단 지수 개발

  • Received : 2019.03.27
  • Accepted : 2019.05.13
  • Published : 2019.05.31
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Abstract

Various studies have been conducted for the diagnosis of noise condition of complex rotary machines. In this study, diagnosis index using vibration signal is developed for the efficient and objective assessment of noise condition of a blower motor. The noise most commonly caused by the abnormal blower motor are Tick/Click noise and Tone noise. According to cause and noise characteristics, time-frequency analysis is used to diagnose Tick/Click noise, and smoothing in frequency domain is used to diagnose tone noise condition. The noise condition of the blower motors were diagnosed using the developed index and these results are compared with the diagnostic results by the experts. As a result, the agreement rate was about 95 %.

복잡한 회전 기계의 소음 상태 진단을 위한 다양한 연구가 수행되고 있다. 본 연구에서는 진동신호를 이용하여 블로워 모터의 효율적이고 객관적인 소음 상태진단을 위한 지수를 개발하였다. 블로워 모터의 이상 시 가장 흔히 나타나는 소음으로 틱/클릭 소음과 톤 소음이 있다. 발생 원인과 소음 특성에 따라 틱/클릭 소음의 상태 진단에는 시간-주파수 분석법을 그리고 톤 소음 상태 진단에는 주파수 영역에서의 평활화 기법을 이용하였다. 개발한 지수를 이용하여 블로워 모터의 소음 상태 진단을 수행하고 이를 전문가에 의한 진단 결과와 비교하였다. 그 결과 약 95 %의 일치율을 보였다.

Keywords

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Fig. 1. Target (a) blower motor system and (b) HVAC module.

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Fig. 2. Sensor location on HVAC module for measurement of vibration.

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Fig. 3. Wavelet decomposition of time signal using inverse wavelet transform.

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Fig. 4. Two-dimensional illustration of the wavelet coefficients magnitude matrix.

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Fig. 5. Impulse response of a linear underdampedsecond system; (a) time domain, (b) frequency domain.

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Fig. 6. Auto-correlation spectrum of time-frequency algorism.

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Fig. 7. The steps of the procedure for Tick/Click noise diagnosis of blower motor.

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Fig. 8. Frequency spectrum and its smoothed result on frequency domain.

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Fig. 9. Result of tick/click noise and tone noise diagnosis using time-frequency algorisms.

Table 1. Noise types and occurrence frequency of blower motor system.

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Table 2. Rotating speed of blower motor according to its operating stage.

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Table 3. The number of samples.

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Table 4. The number of samples of diagnosed results.

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