Research on Features Extraction of Magnetic Field Sensor Based on Kalman Filter

Jian Sun; Wei Guo Lin

doi:10.4028/www.scientific.net/AMR.396-398.2240

Paper Titles

Desulfurization of Fuel Oils by Extraction with Ionic Liquids
p.2221

Studies on the Coordination Reactions of Polyphenols and Vanadium (IV) Using pH-Potentiometry
p.2225

Research and Application of Thiocyanate-Selective Electrodes Based on Copper (II) Complex with Ethylene-Diamine-Bis-(Salicylaldehyde) Base as Carrier
p.2230

Heat Transfer Characteristics of an Array of Impinging Gaseous Slot Jets
p.2234

Research on Features Extraction of Magnetic Field Sensor Based on Kalman Filter
p.2240

Study on Predictin of Surface Subsidence of an Exremely Shallow Large-Span Double-Arch Tunnel
p.2245

Reaction Mechanism of 2-Propynyl-Aniline with Propyne
p.2249

Supercritical Carbon Dioxide Extraction of Carotenoids from Marigold Flower Using Orthogonal Test Design
p.2253

System Design of Comparison of Diesel Multiple Units (DMUs) Wearing Oil Ferrographic Analysis and Spectrometric Analysis
p.2256

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 396-398Research on Features Extraction of Magnetic Field...

Research on Features Extraction of Magnetic Field Sensor Based on Kalman Filter

Abstract:

In this paper,a method for wire rope non-destruction testing is proposed based on metal magnetic memory technology.The identification of metal magnetic memory signal depends on Signal Noise Ratio (SNR), but the sensor and signal processing determine the SNR.The unstabitily of environment and amplifier saturation can decrease the SNR, By signal processing, the necessity of realtime filtering for SNR is demonstrated.This paper utilizes Kalman filter to analysis the signal.The principle of Kalman filter is introduced The results shows us that the SNR and reliability of system is greatly improved with this method.

You might also be interested in these eBooks

Advances in Chemical Engineering: ICCMME 2011

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 396-398)

Pages:

2240-2244

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.396-398.2240

Citation:

Cite this paper

Online since:

November 2011

Authors:

Jian Sun, Wei Guo Lin

Keywords:

Feature Extraction, Kalman Filter (KF), Magnetic Sensor, SNR

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Dalei Song.J. NDT:1999(5).(In Chinese).

Google Scholar

[2] Li Ying,Wei Gu.J.Journal of Shanghai Maritime Unversity.Vol.20 No1.1999.(20):6-10. (In Chinese).

Google Scholar

[3] Doubov AA. J. Insp Diagn 2001.6:19–29.

Google Scholar

[4] Doubov AA. Principal features of metal magnetic memory method and inspection tools as compared to known magnetic NDT methods. In:Proceedings of the 16th Annual World Conference on Non-Destructive Testing. Montreal, Canada, 2004.

Google Scholar

[5] Doubov AA, Kolokolnikov S. The metal magnetic memory method and inspection instruments. Training handbook IIW Document no. V-1347.

Google Scholar

[6] Kalman R. E.J. Joural of basic Eng(ASME),1960,82D:95-108.

Google Scholar

[7] R.S. Gross T.M. Eubanks J.A. Steppe,et al.J.Jounal of Geodesy,1998,72(4):215-235.

Google Scholar

[8] REG WELCH，GARY BISHOP.J. Department of Computer Science University of North Carolina at Chapel Hill Chapel Hill，NC27599-3175，2006.

Google Scholar

[9] PETER S.MAYBECK.Stochastic models,estimation and control（Volume1) M.Academic Press New York,San Francisco,London,1979.

Google Scholar