Tennessee Eastman process monitoring based on support vector data description

摘要：

Modern industrial processes are often accompanied with high temperature, high pressure, flammable and explosive environment, which makes the safety and reliability very important. Based on the dimension decrease and de-noise of the data by principal component analysis, a support vector data description approach is applied to process monitoring, which is independent of the normal distribution of the data support vector data description and its application to Tennessee Eastman process. The application to Tennessee Eastman process has proved the sensitivity of the method, which is helpful to taking measures on time and stablizing the product quality.

关键词： Principal Component Analysis Support Vector Data Description Tennessee Eastman Process

作者: Liu Yanguo Xu Chunwei Shi Jian

作者单位: Zhejiang Institute of Mechanical & Electrical Engineering, Hangzhou, 310053, China Changshu Institute of Technology, Changshu,215500, China

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System Design and Engineering Applications(2012年智能系统设计与工程应用国际会议 ISDEA 2012)

会议地点: 三亚

会议语种:英文

页码: 553-555

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）