Title :
An SVR-Based Online Fault Detection Method
Author :
Shengchao, Su ; Na, Deng ; Gang, Hu Yi
Author_Institution :
Ind. Eng. Training Centre, Shanghai Univ. of Eng. Sci., Shanghai, China
Abstract :
Many complex engineering systems have the characteristics such as difficult modeling, dangerous testing, and high cost to experiment with fault. Aim at these points, a new framework for online fault detection is presented. This framework includes a mechanism for associating each detection result with a confidence value. Based on this framework, a concrete real-time fault detection method is developed by an online support vector regression algorithm. The method can detect predict fault quickly without any data and prior knowledge of fault, so it is provided with strong practical significance. The simulation on the fighter F-16 is performed to demonstrate the promising performance of the method.
Keywords :
Internet; fault diagnosis; fault simulation; nonlinear systems; regression analysis; support vector machines; SVR-based online fault detection method; complex engineering system; concrete real time fault detection method; fault prediction; fighter F-16; online support vector regression algorithm; Circuit faults; Density functional theory; Elevators; Fault detection; Mathematical model; Support vector machines; Training; Support Vector Regression; confidence; fault detection; nonlinear system; online; temporal sequence;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on
Conference_Location :
Shangshai
Print_ISBN :
978-1-4244-9010-3
DOI :
10.1109/ICMTMA.2011.113
