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Modelling and optimization of machine tools on foundations

Novotny L., Sindler J., Fiala S., Sveda J.

Journal of Machine Engineering

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2016

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Vol. 16, No. 1

43--56

EN

This paper aims to expand existing complex mathematical models of machines in a manner that would respect the influence of their installation on the foundation. For this purpose, a method of modelling and optimization of foundations was developed. It consists of four basic parts: Mathematical modelling of machines, optimization of the number and placement of fixing (levelling) elements, optimization and modelling of the reinforced concrete foundation and modelling of the subsoil with respect to engineering geological conditions. The main optimization criterion is to increase the lowest natural frequency of the machine while reducing the foundation weight (amount of reinforced concrete).The result is a virtual mathematical model of the machine tool, including the influence of its foundation and subsoil. The proposed optimization can be used for designing new machines, machine foundations and the number and distribution of machine levelling elements. This method has been applied and tested on a virtual model of a multi-purpose machining center for workpieces up to 15 tons.

2

Comparison of Two Model Coupling Methods for Joint Identication

Susen J., Sulitka M., Sindler J., Janota M.

Journal of Machine Engineering

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2015

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Vol. 15, No. 1

58--70

EN

An experimental identification of joint dynamic properties requires accurate models of the joined bodies and an appropriate model coupling method. The bodies to be coupled can be described by their mass, stiffness and damping matrices (M, K, C) or by receptance matrices. Each approach has its advantages and disadvantages. The receptance matrix method requires a high number of measurements. However the measured data can be used directly and no model identification is needed. The experimental identification of the M, K, C matrices feasible for creating precise coupled models is difficult. Therefore, an approach based on a verified FE model can be employed. The two methods of model identification and coupling are discussed using a case study of two bolted beams. Several ways of the receptance matrices measurement simplification and their influence on the accuracy of the results are studied. The effect of noise, measured FRF peak accuracy and data filtering on the resulting coupled receptance matrix is studied as well. The results obtained by the receptance matrix method are compared to the results obtained by the method of coupling the verified FE models. It has been found that the method based on coupling the verified M, K, C matrices proves to be a more reliable approach, which will allow a more precise joint dynamic model identification in the next step.

3

Coupled modelling for machine tool structural optimization

Sulitka M., Sindler J., Susen J.

Journal of Machine Engineering

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2014

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Vol. 14, No. 3

21--34

EN

Effective machine tool design needs to take into account various kinematic configurations and possible combinations of structural parts, which meet the requirements of both the structural properties on one hand and technology and cost limitation on the other hand. Prior to a detailed developing a certain machine tool structure, an expert based decision on the machine tool conception needs to be performed. A high number of design variants should be explored in a short time. Fulfilling those demands leads to developing a machine tool modular models, enabling easy changing the kinematic configuration or various structural parts. In the paper the techniques for effective component coupling and model order reduction using mode truncation or Krylov subspace based technique for creating the machine tool coupled models are introduced. Case studies considering real machine tool structures are given. High quality of Krylov subspace reduction technique in connection with multipoint constraint surface coupling is shown both in terms of dynamic properties of the reduced multibody model and a very low time demands at the same time.