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Unbalance estimation using linear and nonlinear regression
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2010 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 46, no 11, 1752-1761 p.Article in journal (Refereed) Published
Abstract [en]

This paper considers the problem of unbalance estimation of rotating machinery. It is formulated as a parameter estimation problem, where the unknowns enter nonlinearly in a regression model. By use of a certain method, the problem can be reformulated as a linear estimation procedure with a closed form solution. This procedure is sometimes known as the influence coefficient method. In its derivation, no special treatment is devoted to disturbing terms and imperfections in the model. Therefore, a novel method is derived which takes disturbances into account, leading to a nonlinear estimator. The two procedures are compared and analyzed with respect to their statistical accuracy. Using the example of unbalance estimation of a separator, the nonlinear approach is shown to give superior performance.

Place, publisher, year, edition, pages
2010. Vol. 46, no 11, 1752-1761 p.
Keyword [en]
Balancing, Linear regression, Nonlinear regression, Unbalance estimation, Variable projection algorithms
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:uu:diva-136113DOI: 10.1016/j.automatica.2010.06.053ISI: 000284661000002OAI: oai:DiVA.org:uu-136113DiVA: diva2:376259
Available from: 2010-12-10 Created: 2010-12-10 Last updated: 2017-12-11Bibliographically approved

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