DETECTION OF HARDWARE FAILURES AT INTERMAGNET OBSERVATORIES: APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO GEOMAGNETIC RECORDS STUDY
Rubrics: ORIGINAL ARTICLES
Authors:
1.
Geophysical Center RAS, Moscow, Russia
2.
Geophysical Center RAS, Moscow, Russia
3.
Geophysical Center RAS, Moscow, Russia
4.
Geophysical Center RAS, Moscow, Russia
5.
National Geophysical Data Center, Boulder, Colorado, USA
Type:
Article
Pages:
from 1
to 6
Status:
Published
Received:
25.12.2009
Accepted:
25.12.2009
Published:
25.12.2009
Language:
English
Keywords:
time series, pattern recognition, geomagnetic observations
Abstract (English):
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.
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.
Keywords:
time series, pattern recognition, geomagnetic observations
time series, pattern recognition, geomagnetic observations
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