A MSVM Quality Pattern Recognition Model for Dynamic Process

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Abstract:

Quality abnormal pattern recognition for dynamic process is the key problem to achieve the online quality control and diagnose of automatic production. Firstly, this paper analyzed the quality patterns of dynamic process. Secondly, we established recognition model of quality recognition in dynamic process using MSVM and compared the SVM recognition accuracy of different kernel functions for different quality patterns. Simulation experiment indicates that different SVM classifiers should choose specified kernel functions to recognition quality patterns. At last, we established MSVM recognition model of quality pattern in dynamic process using multi-kernel function according to the experiment results.

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555-561

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October 2013

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