RBF neural network inferential sensor for process emission monitoring
RBF neural network inferential sensor for process emission monitoring
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DOI：
10.1016/j.conengprac.2013.01.007
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发表时间：
2013-07-01
影响因子：
4.9
通讯作者：
Adeniran, Ahmed A.
中科院分区：
文献类型：
--
作者：
Iliyas, Surajdeen A.;Elshafei, Moustafa;Adeniran, Ahmed A.
推理传感或软传感近年来作为连续排放监测系统的替代方案而受到欢迎，因为与类似的硬件传感器相比，它简单、可靠且具有成本效益。在本文中，我们使用工业锅炉的炉膛模型来解决 NOx 排放问题，并提出了一种用于 NOx 和 O-2 高性能预测的神经网络结构。所研究的锅炉为 160 MW、使用天然气的燃气水管锅炉，具有两个垂直排列的燃烧器。锅炉模型是一个 3D 问题，除了 NOx 建模之外还涉及湍流、燃烧、辐射。 3D 计算流体动力学模型是使用 Fluent 仿真包开发的。该模型提供了 3D 温度分布以及氮氧化物污染物形成速率的计算，有助于更好地了解氮氧化物的产生方式和地点。模拟了锅炉在各种运行条件下的情况。然后，生成的数据用于神经网络软传感器的初始开发和评估，以基于传统过程变量测量进行排放预测。然后使用工业锅炉的实际数据评估所提出的软传感器的性能。所开发的软传感器达到了与连续排放监测分析仪相当的精度，同时大幅降低了设备和维护成本。 (C) 2013 Elsevier Ltd. 保留所有权利。
Inferential sensing, or soft sensing, gained popularity in recent years as an alternative to continuous emission monitoring systems because of its simplicity, reliability, and cost effectiveness as compared to analogous hardware sensors. In this paper we address the problem of NOx emission using a model of furnace of an industrial boiler, and propose a neural network structure for high performance prediction of NOx as well as O-2. The studied boiler is 160 MW, gas fired with natural gas, water-tube boiler, having two vertically aligned burners. The boiler model is a 3D problem that involves turbulence, combustion, radiation in addition to NOx modeling. The 3D computational fluid dynamic model is developed using Fluent simulation package. The model provides calculations of the 3D temperature distribution as well as the rate of formation of the NOx pollutant, enabling a better understanding on how and where NOx are produced. The boiler was simulated under various operating conditions. The generated data is then used for initial development and assessment of neural network soft sensors for emission prediction based on the conventional process variable measurements. The performance of the proposed soft sensor is then evaluated using actual data from an industrial boiler. The developed soft sensor achieves comparable accuracy to the continuous emission monitor analyzer, however, with substantial reduction in the cost of equipment and maintenance. (C) 2013 Elsevier Ltd. All rights reserved.