Method for monitoring multivariate processes
AssigneeTelefonaktiebolaget LM Ericsson
InventorsSvante Wold, Karl Olov Lasse Sundin
Life of this patent
Estimating the term…
Abstract
Variables associated with a multivariate process are monitored on a periodic basis. As a result of an observation of the variables, a residual standard deviation between the monitored variable values and a predictive model can be determined. The residual standard deviation is plotted as a series of connected points. Through the use of an adaptive model, the observations of the variables, and in turn, the residual standard deviation and the predictive model are adapted to changes in the multivariate process.
Claims16
A method for monitoring a multivariate process comprising the steps of:
- registering measured values of variables associated with said multivariate process as an observation at a predetermined time;
- describing the variables as a multidimensional space, wherein each variable represents one dimension in the space;
- representing each observation as a point in the multidimensional space, whereby a series of observations carried out at different times will be represented by a point cluster in space;
- calculating for the point cluster at least one first and one second principal directions in space;
- determining projections of the observations onto the first and second principal directions, whereby a model of the multivariate process is obtained;
- updating during the course of the multivariate process the first and second principal directions of the point cluster in space, whereby the model of the multivariate process is dynamically adapted to the multivariate process in real time.
A method for monitoring a multivariate process, comprising the steps of:
- registering measured values of variables associated with said multivariate process as an observation at a certain time;
- describing the variables as a multidimensional space, wherein each variable represents one dimension in the space;
- representing each observation as a point in the multidimensional space, whereby a series of observations carried out at different times are represented by a point cluster in space;
- calculating for the point cluster at least one first and one second principal directions in space;
- determining projections of the observations onto the first and second principal directions, whereby a model of the multivariate process is obtained;
- updating during the course of the multivariate process the first and second principal directions of the point cluster in space, whereby the model of the process is dynamically adapted to the process in real time;
- p1 calculating a residual standard deviation between a latest observed vector presentation of the multivariate process and an on-line updated model of the multivariate process;
- and
- initiating an alarm when the residual standard deviation of the multivariate process to the model exceeds a predetermined limit.
An apparatus for monitoring a multivariate process comprising:
- means for registering measured values of variables associated with said multivariate process as an observation at a predetermined time;
- means for describing the variables as a multidimensional space, wherein each variable represents one dimension in the space;
- means for representing each observation as a point in the multidimensional space, whereby a series of observations carried out at different times will be represented by a point cluster in space;
- means for calculating for the point cluster at least one first and one second principal directions in space;
- means for determining projections of the observations onto the first and second principal directions, whereby a model of the multivariate process is obtained;
- and
- means for updating during the course of the multivariate process the first and second principal directions of the point cluster in space, whereby the model of the multivariate process is dynamically adapted to the multivariate process in real time.
Dependencies are inferred from the claim text.