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|Title:||Parameter identification of fluid line networks by frequency-domain maximum likelihood estimation|
|Citation:||Mechanical Systems and Signal Processing, 2013; 37(1-2):370-387|
|Publisher:||Academic Press Ltd Elsevier Science|
|Aaron C. Zecchin, Langford B. White, Martin F. Lambert, Angus R. Simpson|
|Abstract:||The accurate hydraulic simulation of fluid line networks is important for many applications, however, in many instances (such as surge analysis in water distribution networks) the system parameters are subject to much uncertainty. This paper presents a parameter identification method for fluid line networks based on transient-state measurements of the hydraulic variables of pressure and ow within the network. From a Laplace-domain admittance matrix representation of the system, a measurement model is derived that decouples the influence of unmeasured state variables from the measured state variables. This de-coupled measurement model is used as the basis of the development of a frequency-domain maximum likelihood estimation method. The proposed method is applied to different case studies with successful results.|
Maximum likelihood estimation
|Rights:||Crown Copyright © 2013|
|Appears in Collections:||Aurora harvest 7|
Electrical and Electronic Engineering publications
Environment Institute publications
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