Fault Prediction for Nonlinear Time Series Based on Temporal Pattern Estimation

摘要：

　　An on-line Least Square Support Vector Regression (LS-SVR) algorithm is given in this paper.Based on this algorithm the method of on-line fault prediction by temporal pattern estimation is proposed.The method needs neither the model to approximate the true system nor the fault training data and primary knowledge.It can study and predict while systems running,and it is believed with fast speed,fewer amounts of calculation and better real-time capability.The result of simulation on CSTR proved the efficiency.

关键词： Temporal pattern estimation Nonlinear time series Fault prognosis Least Squares Support Vector Machines

作者: Shengchao Su Xiaolan Fan

作者单位: Industrial Engineering Training Centre, Shanghai University of Engineering Science, Shanghai201620, China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4471-4475

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）