Sciweavers

EUSFLAT
2001

Computational intelligence approaches for parametric estimation and feature extraction of power spectral density

13 years 5 months ago
Computational intelligence approaches for parametric estimation and feature extraction of power spectral density
This paper reports an early progress of a feasibility study of a computational intelligence approach to the enhancement of the accuracy of flow measurements in the framework of a current cooperation between Tecnatom s.a. in Madrid and the OECD Halden Reactor Project in Halden. The aim of this research project is to contribute to the development and validation of a flow sensor in a nuclear power plant (NPP). The basic idea of the current project is to combine the use of applied computational intelligence approaches (noise analysis, neural networks, fuzzy systems, and wavelet etc.) with existing traditional flow measurements, and in particular with cross correlation flowmeter concepts. The design of possible algorithms based on computational intelligence approaches will be modified during the tests of a real NPP.
Da Ruan, Davide Roverso, Paolo F. Fantoni
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where EUSFLAT
Authors Da Ruan, Davide Roverso, Paolo F. Fantoni
Comments (0)