DETECTION OF HARDWARE FAILURES AT INTERMAGNET OBSERVATORIES: APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO GEOMAGNETIC RECORDS STUDY
Рубрики: ОРИГИНАЛЬНЫЕ СТАТЬИ
Авторы:
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
Тип:
Статья
Страницы:
с 1
по 6
Статус:
Опубликован
Получено:
25.12.2009
Одобрено:
25.12.2009
Опубликовано:
25.12.2009
Язык материала:
английский
Ключевые слова:
time series, pattern recognition, geomagnetic observations
Аннотация (русский):
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.
Ключевые слова:
time series, pattern recognition, geomagnetic observations
time series, pattern recognition, geomagnetic observations
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2. Kerridge, Proceedings of the Workshop on Space Weather, 2001.
3. Kolmogorov, Elements of Function Theory and Functional Analysis, 5-th ed., 1981.
