Due to temporary inabilities of the models to match the real values with the predictions, random spikes can arise in the “alarm” time series. Thus, in order to make the alarm system more reliable, we use a two-level structure: this first alarm, the one defined above, is merely a warning signal and is processed again to produce a more accurate second level alarm signal. Using a Moving Aggregation node, the moving averages are calculated on a backward window of 21 samples of the level 1 alarm (warning) signals. This moving average operation smooths out all short random spikes in the level 1 alarm time series, retaining only the ones that persist over time.
