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.
A new batch process monitoring based on Multilinear Principal Component Analysis (MLPCA) is proposed in this paper. In the existing vector-based method on batch process monitoring such as Multiway Principal Component Analysis (MPCA), a batch data is represented as a vector in high-dimensional space. But vectorizing the batch data will lead to large storage requirements and information loss. MLPCA...
Multiway Principal Component Analysis (MPCA) has been widely used to monitor multivariate batch process. In MPCA method, the batch data is represented as a vector in high-dimensional space, resulting in large computation, storage space and loss of important information inevitably. A new batch process fault diagnosis method based on the 2-Dimensional Principal Component Analysis (2DPCA) is presented...
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.