Abstract
Long-term operation of the mechanical equipment leads to structural fatigue damages. The damages always come with internal crack initiation and propagation, which radiate acoustic emission (AE) signal. It is possible to monitor the whole damage development process of mechanical equipment by AE technology. AE signal is usually collected at a high sampling rate which leads to large data sets, and occupying huge storage space. This goes against long-term online monitoring. This research uses different threshold-level settings of wavelet transform to compress raw AE signal. Compared with the original signal, the compressed signal could retain key features including energy, rms, kurtosis, etc. The signal-to-noise ratio (SNR) of the reconstruction signal also has been improved. This algorithm was confirmed by AE signal of rolling bearing in a fatigue damage test.
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Acknowledgment
This research was supported in part by Science and Technology Department Foundation Project of Yunnan Province under Grant No. 2011FZ017 and Education Department Foundation Project of Yunnan Province under Grant No. 2013J060. We thank all of our dear teammates in MCVN for their support for this work.
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Wang, Z., Wu, X., Liu, X., Liu, C., Jia, H. (2015). Research on Compression Method of Acoustic Emission Signal Based on Wavelet Transform. In: Shen, G., Wu, Z., Zhang, J. (eds) Advances in Acoustic Emission Technology. Springer Proceedings in Physics, vol 158. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1239-1_16
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DOI: https://doi.org/10.1007/978-1-4939-1239-1_16
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