Abstract
In this chapter, a phase plane analysis method has been proposed as a new way of analyzing nonstationary signals, based on wavelet theory. Some basic concepts are defined to form a theoretical framework of this method. Several possible applications are discussed. This approach offers the potential for building new intelligent process signal analysis systems to identifying the process “finger prints”, i.e. the hidden time-frequency structure in signals.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cheung, J. T.-Y and G. Stephanopoulos “Representation of process trends -Part I. A formal representation framework.” Computers & chemical Engineering 14, 4/5 (1990): 495–510.
Cohen, L. “Time-frequency distributions A review.” Proceedings of the IEEE, 77, 7 (1989): 941–981.
Coifman, R. R., Y. Meyer, S. Quake and M. V. Wickerhauser “Signal processing and compression with wavelet packets.” Progress in Wavelet Analysis and Applications, Meyer and Roques eds., Editions Frontieres, Toulouse, France, (1992a): 77–93.
Coifman, R. R. and M. V. Wickerhauser “Entropy-based algorithms for best basis selection.” IEEE Trans. Information Theory 38, 2 (1992b): 713–718.
Dai, Xue-dong “Intelligent process signal analysis system.” D.Sc research proposal, Department of Chemical Engineering, Washington University in St. Louis, (1992).
Daubechies, I. Ten Lectures in Wavelets Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania, 1992.
Daubechies, I., S. Mallat and A. S. Willsky eds. Special Issue on Wavelet Transforms and Multiresolution Signal Analysis,IEEE Trans. Information Theory 38, 2 (1992).
Donoho, David L. and Iain M. Johnstone “Ideal Spatial Adaptation by Wavelet Shrinkage.” Preprint, Department of Statistics, Stanford University, (1992a).
Donoho, David L. “De-Noising by Soft-Thresholding.” Preprint, Department of Statistics, Stanford University, (1992b).
Hlawatsch, F. and G. F. Boudreaux-Bartels “Linear and quadratic time-frequency signal representations.” IEEE Signal Processing Magazine, (Apr. 1992): 21–67.
Jawerth, B. and Wim Sweldens “An overview of wavelet based multiresolution analysis.” Research report 1993:1, Department of Mathematics, University of South Carolina (1993).
Joshi, A. P. Extraction of Information from Time-series Process Operational Data D.Sc. Dissertation, Department of Chemical Engineering, Washington University in St. Louis, (1992).
Mallat, S. and W. L. Hwang “Singularity detection and processing with wavelets.” IEEE Trans. Information Theory 38, 2 (1992): 617–643.
Mallat, S. “Multiresolution approach to wavelets in computer vision.” Wavelets,Time-Frequency Methods and Phase Space Combes, J. M. et al. eds. Springer, 1989: 313–327.
Rioul, O. and M. Vetterli “Wavelets and signal processing.” IEEE Signal Processing Magazine, (Oct. 1991): 14–38.
Simoncelli, E. P., W. T. Freeman, E. H. Adelson and D. J. Heeger “Shiftable multiscale transform.” IEEE Trans. Information Theory 38, 2 (1992): 587–607.
Wickerhauser, M. V. Lectures on Wavelet Packet Algorithms Department of Mathematics, Washington University in St. Louis, (1991).
Wornell, G. W. and A. V. Oppenheim “Estimation of fractal signal from noisy measurements using wavelets.” IEEE Trans. Signal Processing 40, 3 (1992): 611–623.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1994 Springer Science+Business Media New York
About this chapter
Cite this chapter
Dai, Xd., Joseph, B., Motard, R.L. (1994). Process Signal Features Analysis. In: Motard, R.L., Joseph, B. (eds) Wavelet Applications in Chemical Engineering. The Kluwer International Series in Engineering and Computer Science, vol 272. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2708-4_4
Download citation
DOI: https://doi.org/10.1007/978-1-4615-2708-4_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-7923-9461-7
Online ISBN: 978-1-4615-2708-4
eBook Packages: Springer Book Archive