The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
To efficiently identifying the bearing fault in gear-rotor-bearing system of wind turbines, this paper presented an algorithmic solution to carry out the analysis of vibration signals of bearings by the use of ensemble empirical mode decomposition (EEMD) and support vector machine (SVM). Through appropriately decomposing the obtained original vibration signals into a collection of intrinsic mode functions...
For least squares support vector machine (LS-SVM) classifier to the loss of sparseness and generalization, a pruning modeling method is proposed based on Quadratic Renyi entropy. The kernel principal component is adopted for data pre-processing, and the training set is divided randomly. Then the concept of quadratic Renyi entropy is introduced as the basis of training and pruning in LS-SVM classifier...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.