WAVELET BASED COMPRESSION AND FEATURE SELECTION FOR VIBRATION ANALYSIS

✍ Scribed by W.J. Staszewski

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 354 KB
• Volume: 211
• Category: Article
• ISSN: 0022-460X
• DOI: 10.1006/jsvi.1997.1380

✦ Synopsis

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.

7 1998 Academic Press Limited * Strictly speaking a set is either compact or not. Therefore a function cannot be more or less compactly supported than another. However, if one has a measure, as in this case on L 2 (R), one can compare the sizes of the compact supports and introduce an order relation.