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.
In this paper, an efficient bearing health condition assessment approach is proposed based on alpha-stable distribution model. The health condition assessment index is constructed with Kullback-Leibler distance (KLD) between two alpha-stable distributions, which are statistical models of vibration signals in normal condition and fault condition. Experimental results based on the run-to-failure bearing...
In the field of fault diagnosis, neural networks have been widely applied in distinguishing the type of fault. However, neural networks require training with large number of sample data, and as the input of neural networks, fault pattern vectors does not guarantee that can completely represent faults. Bayesian networks (BN) is a powerful method widely used to solve the problem with uncertainty and...
For a given structure, rotor's natural frequencies are closely related with the supporting stiffness of the rotor. To some extend, the supporting stiffness determines whether the rotor can avoid resonance phenomenon. Using the ANSYS, this paper studied the rotor's vibration characteristics and the characteristics of bearing instability by changing the LP rotor supporting stiffness of an ultra-supercritical...
In practical situations, the vibration collected from rotating machinery is often a mixture of many vibration components and noise, therefore it is very necessary to extract fault features from the mixture first in order to achieve effective rotating machinery fault diagnosis. In this paper, independent component analysis with reference (ICA-R) method is proposed to extract the fault features using...
A new statistical model for rolling element bearing fault signals is proposed based on alpha-stable distribution. Such a non-Gaussian model can accurately describe statistical characteristic of bearing fault signals with impulsive behavior. The characteristic exponent alpha of bearing fault signals with different fault degree is estimated by a stable distribution parameter estimation method. Estimation...
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.