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This study concerns with the diagnosis of composite defects using pitch-catch method in aircraft material by applying the Wavelet transform (WT) analysis, PCA along with support vector machine (SVM). A novel application is presented exploring the problem of detection and estimation of the various defects; the early detection and classification of aircraft defects is of particular importance, as the...
To overcome the deficiencies of low accuracy and high false alarm rate in fault diagnosis system, a new optimization method for f the fault diagnosis model is proposed based on support vector regression (SVR) and principal components analysis. Utilizing the character that principal components analysis algorithm can keep the discernability of original dataset after reduction, the reduces of the original...
Support vector machine (SVM) which overcomes the drawbacks of neural networks has been widely used for pattern recognition in recent years. A new optimization method for the fault diagnosis model is proposed. To overcome the deficiencies of low accuracy and high false alarm rate in fault diagnosis system, an integrated fault diagnosis model based on support vector regression and principal components...
When faults occur in power systems, it is hard to manually deal with the fault data reported by the system of supervisory control and data acquisition (SCADA) because of the huge amount of alarm information. In this paper, we study the problem of power system fault diagnosis by using support vector machine (SVM), and enhance the ability of fault diagnosis through optimizing support vectors. The results...
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