The Faults Detection Methods for Embedded Equipment

Abstract:

Due to the objects in the embedded control procedure are difficult to obtain a variety of fault data and fault features, it’s necessary to establish simulation models in accordance with the operational mechanisms of the embedded equipment to simulate and diagnose the practical faults. This paper proposes a SVM integrated diagnostic method and further proposes the faults classification model with improved neural network. The faults diagnose performance is greatly improved by analyzing the types of the faults in different facets. For the embedded valve failure modes, the simulation results of the proposed method are compared with that of the previous mature independent element analysis method. The simulation results show that the fault diagnosis method in this paper can effectively improve the speed and accuracy of fault diagnosis for the embedded equipment.

• Periodical: Applied Mechanics and Materials (Volumes 602-605)
• Pages: 2041-2043
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.602-605.2041
• Online since: August 2014
• Authors: Bin Wang*
• Keywords: Embedded System, Faults Detection, Neural Network (NN), SVM

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