摘要
针对烟气制酸中的酸浓在线难以准确检测的问题,提出了一种基于软测量技术的在线检测酸浓方法。通过对现场生产数据的采集和预处理,建立了基于径向基函数神经网络的软测量模型;再利用实验平台对该模型进行了验证。实验结果表明:该模型可以得到较精准的硫酸质量分数,能有效地指导生产,具有良好的应用前景。
A new detecting method based on soft sensor technology is introduced to solve the problem of sulfuric acid concentration on-line detection. The method completes on-site data acquisition and data preprocessing, establishes the soft-sensor model based on RBF neural network and verifies the model on experimental platform. The result shows that the model obtains accurate sulfuric acid mass fraction, which guides production effectively and has good application prospect.
出处
《湖南工业大学学报》
2012年第4期101-104,共4页
Journal of Hunan University of Technology
基金
湖南工业大学研究生科研创新基金资助项目(CX1201)
湖南省科技厅基金资助项目(2012GK3089)
关键词
软测量技术
硫酸工艺
径向基函数神经网络
soft sensor technique
sulfuric acid process
radial basis function neural network
