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On the current state of flotation modelling for process control

机译:关于浮选建模的当前状态以进行过程控制

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Despite significant effort in modelling and simulating flotation circuits, comprehensive model based control and optimisation implementations on industrial circuits remain scarce. In this paper, the factors preventing more widespread implementation of model-based control and optimisation applications are investigated by focussing on three aspects. Firstly, the critical variables required in a simplified flotation model are identified. Models that are currently used in control, optimisation and supervisory applications are thereafter analysed to determine to what extent the required variables are modelled. Finally, online instrumentation available to support these models are investigated, also including instrumentation that is still under development and not commonly available in commercial applications. Although models used in control applications tend to focus on subsections of the flotation process, there seem to be a good agreement between the required and modelled variables. Model fitting however often relies on extensive sampling campaigns that will need to be repeated regularly to maintain model accuracy. A number of online measurements of sufficient accuracy are still not available to support these models, compromising the long term reliable use of models in online applications. The fact that flotation processes are in many instances not extensively instrumented, constrains online maintenance and adaption of model based solutions further.
机译:尽管在浮选电路的建模和仿真方面付出了巨大的努力,但仍缺乏在工业电路上基于模型的全面控制和优化实施方案。在本文中,着眼于三个方面,研究了阻止基于模型的控制和优化应用程序更广泛实施的因素。首先,确定简化浮选模型所需的关键变量。此后,分析当前在控制,优化和监管应用程序中使用的模型,以确定所需变量的建模程度。最后,研究了可用于支持这些模型的在线仪器,其中还包括仍在开发中且在商业应用中不常见的仪器。尽管控制应用中使用的模型倾向于集中于浮选过程的各个部分,但所需变量和建模变量之间似乎有很好的一致性。但是,模型拟合通常依赖于广泛的抽样活动,需要定期重复进行抽样以保持模型的准确性。仍然无法使用许多足够准确的在线测量来支持这些模型,从而损害了模型在在线应用程序中的长期可靠使用。浮选过程在许多情况下没有得到广泛的检测,这一事实进一步限制了在线维护和基于模型的解决方案的适应性。

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