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Elements of Support Vector Machine was applied to the fault diagnosis of gear system, and the two-class algorithms for 3 individual fault modes, which are No Fault Gear Mode, Crack of Dedendum Mode and Tooth Surface Abrasion Mode respectively, are well developed and set up. Through the training and testing simulation data samples and the signal samples from gear oscillation, these 3 different types...
Detecting machine faults at an early stage is very important. In this study, an intelligent fault detection method based on relevance vector machine (RVM) is proposed for incipient fault detection of gear. First, by combining wavelet packet transform with Fisher criterion, it is able to adaptively find the optimal decomposition level and select the global optimal features from all node energies of...
Support vector machine (SVM) is an efficient method for data mining of oil analysis. The principle and structural risk of SVM are described in this paper. And the structural risk is studied using oil analysis data. During the process, parameters determination is a very important part because parameters have great influence on the performance of SVM. We select the Radial Basis Function (RBF) as the...
Support Vector Machine (SVM), based on structural risk minimization principle, is now widely used in pattern recognition, classification and other research fields. It shows better generalization performance than traditional statistical learning theory, especially in small samples. In this paper, some dimensionless parameter is selected as SVM eigenvector, and then support vector machine is applied...
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