Revealing, identifying, and assessing flaws in operating equipment by the acoustic emission image recognition method under strong background noise condition

Muravin, G. B.; Muravin, Boris; Lezvisky, Ludmila

doi:10.1117/12.547514

Cited by 1 publication

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“…An acoustic emission (AE) technique has been utilized for a condition monitoring of structures 1,2) and machines. 3) However, it is a difficulty to monitor AE signals in a noisy environment where vibration or electromagnetic noise exist as environmental noise.…”

Section: Introductionmentioning

confidence: 99%

Development of AE Monitoring System with Noise Reduction Function by Spectral Subtraction

Matsuo

Cho

2012

Mater. Trans.

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In order to monitor acoustic emission (AE) in a noisy environment, an AE monitoring system with a real-time noise reduction function using spectral subtraction (SS) was developed. First, the improvement in the S/N ratio and distortion of the waveform after the process were compare to those in ¾-filter and wavelet shrinkage methods. The improvement in the S/N ratio of the waveform processed by SS constantly increased and was observed to be independent of the S/N ratio of the wave before processing. The distortion of the waveform processed by SS was less than the distortions of the waves processed using ¾-filter and by wavelet shrinkage. Next, the effect of two parameters in the SS process ® frame number ( fn) and over-subtraction factor (¡) ® on the noise reduction performance was studied. The S/N ratio of the signals processed by the SS technique improved with decreasing fn and with increasing ¡. However, the processed waveform was distorted when ¡ was large. It is necessary to set the value of fn to 16 or less and ¡ to 5 or less so that SS showed an advantage to reduce noise with low waveform distortion.Cylindrical wave AE signals produced by the Hsu-Nielsen source (pencil lead breaking) were monitored with the developed system in an environment with artificial noise. The developed system was able to acquire AE signals with a sampling frequency of up to 25 MHz. The noise was reduced and AE signals with S/N ratio of 0 dB before the process could be detected. The S/N ratio of the AE signal was improved by approximately 10 dB using the SS technique.

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Section: Introductionmentioning

confidence: 99%