Abstract
A flexible, stable and controllable real-time algorithm of Auto-Regressive and Moving Average based on Swing Door Trending (ARMA-SDT) is proposed for the compression of impact-type signals in gear fault detection systems. The Auto-Regressive and Moving Average (ARMA) model is used to predict the variation trend of signal features. To guarantee the adaptability, an empirical equation is proposed to calculate the compression threshold of the Swing Door Trending (SDT). Based on the empirical equation and prediction results, dynamic self-regulation of compression threshold is realized, and the compression error always stays around a preconfigured value. Moreover, an experimental setup and an engineering solution are proposed to verify the usefulness, reliability, and stability of the proposed ARMA-SDT algorithm in data compression.
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