An hybrid detection system of control chart patterns using cascaded SVM and neural network–based detector

Neural Computing and Applications - Tập 20 - Trang 287-296 - 2010
Prasun Das1, Indranil Banerjee2
1SQC & OR Division, Indian Statistical Institute, Kolkata, India
2Department of Electrical Engineering, National Institute of Technology, Durgapur, India

Tóm tắt

Early detection of unnatural control chart patterns (CCP) is desirable for any industrial process. Most of recent CCP recognition works are on statistical feature extraction and artificial neural network (ANN)-based recognizers. In this paper, a two-stage hybrid detection system has been proposed using support vector machine (SVM) with self-organized maps. Direct Cosine transform of the CCP data is taken as input. Simulation results show significant improvement over conventional recognizers, with reduced detection window length. An analogous recognition system consisting of statistical feature vector input to the SVM classifier is further developed for comparison.

Tài liệu tham khảo

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