Title :
A LLE-based approach to sensor fault detection
Author :
Zhang, W. ; Li, B. ; Zhou, W.
Author_Institution :
State Key Lab. of Robot., Chinese Acad. of Sci., Shenyang
Abstract :
Feature extraction has been widely used in sensor fault detection. Commonly used feature extraction methods such as PCA and MDS involve signal process of liner time-invariant systems, which are less effective in dealing with the nonlinear systems. In this paper, we will present that Local Linear Embedding (LLE) concept is adopted to solve the fault detection problems and that certain enhancement have been made to make LLE approach more efficient and robust in the extraction of signal features. Test results are given to demonstrate the effectiveness of the enhanced LLE method.
Keywords :
fault diagnosis; feature extraction; sensors; signal processing; feature extraction methods; liner time-invariant systems; local linear embedding concept; nonlinear systems; sensor fault detection; Data systems; Fault detection; Feature extraction; Principal component analysis; Redundancy; Robust stability; Robustness; Sensor systems; Sparse matrices; Vectors;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634135