Moving average convergence and divergence indexes based online intelligent expert diagnosis system for anaerobic wastewater treatment process.

Abstract Anaerobic wastewater treatment process is efficient but unstable due to various disturbances, such as refractory organics and influent organic overloading. Therefore, sensitive and accurate status diagnosis is important for reasonable control to improve the stability of anaerobic process. In this study, an online intelligent expert diagnosis system for anaerobic process was established based on moving average convergence and divergence (MACD) indexes of gas- and liquid-phase parameters, combined with online monitoring system and expert diagnosis database. The effect of this diagnosis system was verified through refractory organics and organic overloading shock experiments. Results showed that this diagnosis system could make rapid, accurate and comprehensive diagnosis, predictions and early-warning. MACD algorithm could enhance pattern recognition capacity of status parameters, overcome the lagging of anaerobic process and filter irregular noisy fluctuations of status parameters. MACD index of H2 partial pressure is suitable as sensitive early-warning indicator in the initial shock stage.