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Automated detection of Pi2 pulsations using wavelet analysis: 1. Method and an application for substorm monitoring

机译：利用小波分析自动检测Pi2脉动：1.亚暴监测方法和应用

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Wavelet analysis is suitable for investigating waves, such as Pi2 pulsations, which are limited in both time and frequency. We have developed an algorithm to detect Pi2 pulsations by wavelet analysis. We tested the algorithm and found that the results of Pi2 detection are consistent with those obtained by visual inspection. The algorithm is applied in a project which aims at the nowcasting of substorm onsets. In this project we use real-time geomagnetic field data, with a sampling rate of 1second, obtained at mid- and low-latitude stations (Mineyama in Japan, the York SAMNET station in the U.K., and Boulder in the U.S.). These stations are each separated by about 120° in longitude, so at least one station is on the nightside at all times. We plan to analyze the real-time data at each station using the Pi2 detection algorithm, and to exchange the detection results among these stations via the Internet. Therefore we can obtain information about substorm onsets in real-time, even if we are on the dayside. We have constructed a system to detect Pi2 pulsations automatically at Mineyama observatory. The detection results for the period of February to August 1996 showed that the rate of successful detection of Pi2 pulsations was 83.4% for the nightside (18-06MLT) and 26.5% for the dayside (06-18MLT). The detection results near local midnight (20-02MLT) give the rate of successful detection of 93.2%.
机译：小波分析适用于研究时间和频率都受限制的波，例如Pi2脉动。我们已经开发了一种通过小波分析检测Pi2脉动的算法。我们测试了该算法，发现Pi2检测的结果与通过视觉检查获得的结果一致。该算法被应用于旨在亚暴暴发临近预报的项目中。在此项目中，我们使用在中低纬度站（日本的Mineyama，英国的York York SAMNET站和美国的Boulder）获得的实时地磁场数据，采样率为1秒。这些站点在经度上的间隔约为120°，因此，始终都在夜间放置至少一个站点。我们计划使用Pi2检测算法分析每个站点的实时数据，并通过Internet在这些站点之间交换检测结果。因此，即使在白天，我们也可以实时获取有关亚暴发作的信息。我们已经建立了一个在Mineyama天文台自动检测Pi2脉动的系统。 1996年2月至1996年8月的检测结果表明，Pi2脉动的成功检测率在夜间（18-06MLT）为83.4％，在白天（06-18MLT）为26.5％。本地午夜（20-02MLT）附近的检测结果得出成功检测率为93.2％。

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