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RUSSIAN JOURNAL OF EARTH SCIENCES VOL. 11, ES2006, doi:10.2205/2009ES000387, 2009

Detection of hardware failures at INTERMAGNET observatories: application of artificial intelligence techniques to geomagnetic records study

A. A. Soloviev, Sh. R. Bogoutdinov, S. M. Agayan, A. D. Gvishiani

Geophysical Center RAS, Moscow, Russia

E. Kihn

National Geophysical Data Center (NOAA's NGDC), Boulder, Colorado, USA


Abstract

INTERMAGNET global network consists of 114 observatories around the world, which monitor the Earth's magnetic field in real time. Data from geomagnetic observatories represent time series. In spite of high quality of measuring instruments all of them are subjected to external impact, which affects the quality of records. The present work is devoted to detection of "Spike", "Baseline jump" and "Baseline drift" failures on records. A search is implemented in the framework of a new geoinformatics approach entitled Discrete Mathematical Analysis (DMA) developed at the Geophysical Center of RAS. It is based on fuzzy logic methods and intended for study of multidimensional data sets and time series. Failures on records are treated as anomalies of particular shapes: e.g., jump/spike is an anomaly on a record leading/not leading to its baseline shift. Preliminarily anomalies on records are detected by FCARS algorithm (Fuzzy Comparison Algorithm for Recognition of Signals). A further search of spikes, baseline jumps and baseline drifts among them is done by additional testing, which uses DMA technique.

Received 24 October 2009; accepted 14 November 2009; published 17 December 2009.

Keywords: time series, pattern recognition, geomagnetic observations


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Citation: Soloviev, A. A., Sh. R. Bogoutdinov, S. M. Agayan, A. D. Gvishiani, and E. Kihn (2009), Detection of hardware failures at INTERMAGNET observatories: application of artificial intelligence techniques to geomagnetic records study, Russ. J. Earth Sci., 11, ES2006, doi:10.2205/2009ES000387.

Copyright 2009 by the Russian Journal of Earth Sciences