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Wavelet based compression and feature selection for vibration analysis
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DOI：10.1006/jsvi.1997.1380.png)
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摘要
En 中文
This paper is concerned with wavelet based linear transformations for data compression and feature selection in vibration analysis. Recent developments in wavelet data compression are summarized. A discussion of various types of data including periodic, continuous non-stationary and transient non-stationary signals, are used to show practical aspects of wavelet compression. The analysis employs smooth wavelets and compactly supported wavelets. It has been shown that compression in vibration analysis can be used not only for effective storage and transmission of the data but also for feature selection. A number of different approaches have been presented to show coefficient selection procedures. This includes procedures based on truncated wavelet coefficients according to their amplitude, position and frequency location and a data compression technique based on optimal wavelet coefficients. (C) 1998 Academic Press Limited.
