Endress + Hauser Flowtec Ag

Universitat Basel

Peter Huggenberger

Rebecca Page

Stefan Wiesmeier

Daniel Waldmann

A method for automated in-line detection of deviations of an actual state of a fluid from a reference state is disclosed wherein measured values captured at the same time are evaluated in a combined manner with respect to at least three measurement variables that are different measurement quantities of the fluid and/or a measurement quantity of the fluid measured at different measuring points. The method includes creating a reference data set, wherein reference measured values are mapped to a reference vector of a vector space using a neural network; in-line measurement, wherein measured values at all times are mapped to a measurement vector using the neural network; comparing the measurement vector with the reference vectors using a kernel density estimator of a predefinable window width; and creating an assessment with respect to a deviation of the actual state from the reference state on the basis of the kernel density estimator.

Method for the automated in-line detection of deviations of an actual state of a fluid from a reference state of the fluid on the basis of statistical methods, in particular for monitoring a drinking water supply

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Dornach, Switzerland

Peter Huggenberger