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Dynamic reasoning to solve complex problems in activated sludge processes: a step further in decision support systems

机译:解决活性污泥过程中复杂问题的动态推理:决策支持系统的又一步

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摘要

Decision support systems (DSS) have generated high expectations as a tool to support activated sludge operation because of their ability to represent heuristic reasoning and to handle large amounts of qualitative, uncertain and low-accuracy data. Previous applications have been satisfactory to control simple problems, when static reasoning and literature-based solutions were enough. However to face complex operational problems with biological origin and slow dynamics (e.g. solids separation problems), it is necessary to use dynamic reasoning and apply long-term control strategies, monitoring the evolution of the process and adjusting the action plan according to the feed back of the process. This paper presents a dynamic reasoning DSS to face solids separation problems in the activated sludge system. The DSS is capable of identifying the complex problem affecting the process, determining if the current situation is new or a continuation from the previous one, assessing what is the specific cause of the situation, and recommending a long-term control strategy, which is daily adjusted according to the evolution of the process.
机译:决策支持系统(DSS)由于能够表示启发式推理并能够处理大量定性,不确定和低准确性的数据,因此已成为支持活性污泥操作的工具,因此产生了很高的期望。当静态推理和基于文献的解决方案就足够了时,以前的应用程序已经可以令人满意地控制简单的问题。但是,要面对具有生物学起源和缓慢动力学的复杂操作问题(例如,固体分离问题),则必须使用动态推理并应用长期控制策略,监视过程的进展并根据反馈调整操作计划的过程。本文提出了一种动态推理DSS来面对活性污泥系统中的固体分离问题。 DSS能够识别影响过程的复杂问题,确定当前情况是新情况还是上一情况的延续,评估造成这种情况的具体原因是什么,并建议长期的控制策略,该策略应每天进行根据过程的演变进行调整。

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