...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Sensors >Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
【24h】

Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System

机译：基于自适应神经模糊推理系统的SMB色谱分离过程的软感应建模

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Simulated moving bed (SMB) chromatographic separation technology is a new adsorption separation technology with strong separation ability. Based on the principle of the adaptive neural fuzzy inference system (ANFIS), a soft sensing modeling method was proposed for realizing the prediction of the purity of the extract and raffinate components in the SMB chromatographic separation process. The input data space of the established soft sensor model is divided, and the premise parameters are determined by utilizing the meshing partition method, subtractive clustering algorithm, and fuzzy C-means (FCM) clustering algorithm. The gradient, Kalman, Kaczmarz, and PseudoInv algorithms were used to optimize the conclusion parameters of ANFIS soft sensor models so as to predict the purity of the extract and raffinate components in the SMB chromatographic separation process. The simulation results indicate that the proposed ANFIS soft sensor models can effectively predict the key economic and technical indicators of the SMB chromatographic separation process.
机译：模拟移动床（SMB）色谱分离技术是一种具有强的分离能力的新吸附分离技术。基于自适应神经模糊推理系统（ANFIS）的原理，提出了一种用于实现SMB色谱分离过程中提取物和萃余液组分的纯度预测的软感测型方法。所建立的软传感器模型的输入数据空间划分，并且通过利用啮合分区方法，减法聚类算法和模糊C-MEARE（FCM）聚类算法来确定前提参数。使用梯度，卡尔曼，kaczmarz和伪素算法来优化ANFIS软传感器模型的结论参数，以预测SMB色谱分离过程中提取物和萃余液组分的纯度。仿真结果表明，所提出的ANFIS软传感器模型可以有效地预测SMB色谱分离过程的关键经济和技术指标。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号