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.
We present a collection of pattern recognition techniques applied to fault detection and diagnosis of motor pumps. Vibrational patterns are the basis for describing the condition of the process. We rely on the data-driven approach to the learning of the fault classes, i.e. supervised learning in pattern recognition. Our work is motivated by the diversity of the studied defects, the availability of...
We report about fault diagnosis experiments to improve the maintenance quality of motor pumps installed on oil rigs. We rely on the data-driven approach to the learning of the fault classes, i.e. supervised learning in pattern recognition. Features are extracted from the vibration signals to detect and diagnose misalignment and mechanical looseness problems. We show the results of automatic pattern...
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.