TY  - JOUR
A1  - Sitz, Andre
A1  - Schwarz, Udo
A1  - Kurths, Jürgen
T1  - The unscented Kalman filter : a powerful tool for data analysis
Y1  - 2004
ER  - 
TY  - JOUR
A1  - Wessel, Niels
A1  - Aßmus, Joerg
A1  - Weidermann, Frank
A1  - Konvicka, Jan
A1  - Nestmann, S.
A1  - Neugebauer, R.
A1  - Schwarz, Udo
A1  - Kurths, Jürgen
T1  - Modeling thermal displacements in modular tool systems
N2  - In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated firstly from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE-algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and get again promising results. The thermally induced errors can be estimated with 1-2${mu m}$ accuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems.
Y1  - 2004
ER  - 
TY  - JOUR
A1  - Kopitzki, K.
A1  - Warnke, P. C.
A1  - Saparin, Peter
A1  - Kurths, Jürgen
A1  - Timmer, Jens
T1  - Comment on "Kullback-Leibler and renormalized entropies: Applications to electroencephalograms of epilepsy patients"
Y1  - 2002
ER  - 
TY  - JOUR
A1  - Zhang, H.
A1  - Hu, B.
A1  - Hu, G.
A1  - Ouyang, Q.
A1  - Kurths, Jürgen
T1  - Turbulence control by developing a spiral wave with a periodic signal injection in the complex Ginzburg-Laundau equation
Y1  - 2002
ER  - 
TY  - JOUR
A1  - Tokuda, I.
A1  - Kurths, Jürgen
A1  - Rosa, Epaminondas
T1  - Learning phase synchronization from nonsynchronized chaotic regimes
Y1  - 2002
ER  - 
TY  - JOUR
A1  - Boccaletti, Stefano
A1  - Valladares, D. L.
A1  - Kurths, Jürgen
T1  - Synchronization of chaotic structurally nonequivalent systems
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Zaks, Michael A.
A1  - Park, Eun Hyoung
A1  - Kurths, Jürgen
T1  - On phase synchronization by periodic force in chaotic oscillators with saddle equilibria
Y1  - 2000
ER  - 
TY  - JOUR
A1  - Zhou, Changsong
A1  - Kurths, Jürgen
A1  - Kiss, Istvan Z.
A1  - Hudson, J. L.
T1  - Noise-enhanced phase synchronization of chaotic oscillators
Y1  - 2002
ER  - 
TY  - JOUR
A1  - Boccaletti, Stefano
A1  - Kurths, Jürgen
A1  - Osipov, Grigory V.
T1  - The synchronization of chaotic systems
Y1  - 2002
ER  -