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Expert system of a crude oil distillation unit for process optimization using neural networks

机译：使用神经网络进行工艺优化的原油蒸馏装置专家系统

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摘要

An expert system of crude oil distillation unit (CDU) was developed to carry out the process optimization on maximizing oil production rate under the required oil product qualities. The expert system was established using the expertise of a practical CDU operating system provided by a group of experienced engineers. The input operating variables of the CDU system were properties of crude oil and manipulated variables; while the system output variables were defined as oil product qualities. The knowledge database of the CDU operating model can be built using the input-output data with an approach of artificial neural networks (ANN). The built ANN model can be applied on predicting the oil product qualities with respect to the system input variables. In addition, a design of experiment was implemented to analyze the effect of the system input variables on the oil product qualities. Optimal operating conditions were then found using the knowledge database with an optimization method according to a defined objective function. The built expert system can provide on-line optimal operating information of the CDU process to the operators corresponding to the change of crude oil properties.
机译：开发了一套专家系统的原油蒸馏装置（CDU），以在所需的油品质量下最大化油的生产率进行工艺优化。专家系统是由一群经验丰富的工程师提供的实用CDU操作系统的专业知识而建立的。 CDU系统的输入操作变量是原油的性质和操作变量。而系统输出变量则定义为石油产品质量。 CDU运行模型的知识数据库可以通过人工神经网络（ANN）的输入输出数据来构建。建立的人工神经网络模型可用于预测与系统输入变量有关的油品质量。此外，还进行了实验设计，以分析系统输入变量对油品质量的影响。然后，根据定义的目标函数，使用具有优化方法的知识数据库找到最佳运行条件。内置的专家系统可以根据原油性质的变化，向操作员提供CDU过程的在线最佳运行信息。

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