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Optimization of characteristic diagram based thermal error compensation via load case dependent model updates

Naumann Christian, Glänzel Janine, Dix Martin, Ihlenfeldt Steffen, Klimant Philipp

Journal of Machine Engineering

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2022

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Vol. 22, No. 2

43--56

EN

The compensation of thermal errors in machine tools is one of the major challenges in ensuring positioning accuracy during cutting operations. There are numerous methods for both the model-based estimation of the thermal tool center point (TCP) deflection and for controlling the thermal or thermo-elastic behavior of the machine tool. One branch of thermal error estimation uses regression models to map temperature sensors directly onto the TCP-displacement. This can, e.g., be accomplished using linear models, artificial neural networks or characteristic diagrams. One of the main limitations of these models is the poor extrapolation behavior with regard to untrained load cases. This paper presents a new method for updating characteristic diagram based compensation models by combining existing models with new measurements. This allows the optimization of the compensation for serial production load cases without the effort of computing a new model. The new method was validated on a 5-axis machining center.

2

Parallel computing in automation of decoupled fluid-thermostructural simulation approach

Glänzel Janine, Naumann Andreas, Kumar Tharun Suresh

Journal of Machine Engineering

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2020

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Vol. 20, No. 2

39--52

EN

Decoupling approach presents a novel solution/alternative to the highly time-consuming fluid-thermal-structural simulation procedures when thermal effects and resultant displacements on machine tools are analyzed. Using high dimensional Characteristic Diagrams (CDs) along with a Clustering Algorithm that immensely reduces the data needed for training, a limited number of CFD simulations can suffice in effectively decoupling fluid and thermal-structural simulations. This approach becomes highly significant when complex geometries or dynamic components are considered. However, there is still scope for improvement in the reduction of time needed to train CDs. Parallel computation can be effectively utilized in decoupling approach in simultaneous execution of (i) CFD simulations and data export, and (ii) Clustering technique involving Genetic Algorithm and Radial Basis Function interpolation, which clusters and optimizes the training data for CDs. Parallelization reduces the entire computation duration from several days to a few hours and thereby, improving the efficiency and ease-of-use of decoupling simulation approach.

3

Comparison of basis functions for thermal error compensation based on regression analysis – a simulation based case study

Naumann Christian, Glänzel Janine, Putz Matthias

Journal of Machine Engineering

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2020

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Vol. 20, No. 4

28--40

EN

It is a well-known problem of milling machines, that waste heat from motors, friction effects on guides, the environment and the milling process itself greatly affect positioning accuracy and thus production quality. An economic and energy-efficient method of correcting this thermo-elastic positioning error is to gather sensor data (temperatures, axis positions, etc.) from the machine tool and the process and to use that information to predict and correct the resulting tool center point displacement using regression analysis. This paper compares multilinear characteristic diagrams, B-spline characteristic diagrams, Radial Basis Function fitting and Wavelet fitting in general and also in the context of thermal error compensation. The demonstrations are made using FEM simulation data from a machine tool demonstrator. The results show that all of the above kernel types, if properly used, are able to create good compensation models. However, high-dimensional multivariate analysis usually only works by adding grid structures and regularization.

4

Simulation-based investigation for heat transfer behavior of steel reinforcements in concrete machine frames and their thermal effects

Glänzel Janine, Geist Alexander, Ihlenfeldt Steffen

Journal of Machine Engineering

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2019

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Vol. 19, No. 3

17--30

EN

The determination of the thermal-elastic behavior is one of the main aspects in the design phase of new machine frames. Prototypically simulation models are used for preliminary investigations, which are based on finite element approaches and usually work with simplified material laws. By the manufacturing of machine frames of concrete steel reinforcements are used to ensure the operation reliability due to the high sensitivity of concrete to tensile stresses. Because of different thermal conductivity and specific heat capacity of steel and concrete the reinforcement has a not negligible influence on the total thermal behavior of the system, which cannot be covered with conventional material laws, e.g. from material libraries. Preliminary investigations show, that a volume fraction more than 1 % of the reinforcement of the total volume can cause a relative error up to ten percent in the temperature field. To reflect the real behavior of reinforced concrete for a machine bed, the influence should be exanimated for two different approaches. Next to the real illustration of the geometry of the reinforcement in the FE-model, decoupled simulation approaches are used on reduced models, which should approach numerically the material behavior of the reinforcement.

5

Parameterization of environmental influences by automated characteristic diagrams for the decoupled fluid and structural-mechanical simulations

Glänzel Janine, Kumar Tharun Suresh, Naumann Christian, Putz Matthias

Journal of Machine Engineering

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2019

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Vol. 19, No. 1

98--113

EN

Thermo-elastic effects contribute the most to positioning errors in machine tools especially in operations where high precision machining is involved. When a machine tool is subjected to changes in environmental influences such as ambient air temperature, velocity or direction, then flow (CFD) simulations are necessary to effectively quantify the thermal behaviour between the machine tool surface and the surrounding air (fluid). Heat transfer coefficient (HTC) values effectively represent this solid-fluid heat transfer and it serves as the boundary data for thermo-elastic simulations. Thereby, deformation results can be obtained. This two-step simulation procedure involving fluid and thermo-structural simulations is highly complex and time-consuming. A suitable alternative for the above process can be obtained by introducing a clustering algorithm (CA) and characteristic diagrams (CDs) in the workflow. CDs are continuous maps of a set of input variables onto a single output variable, which are trained using data from a limited number of CFD simulations which is optimized using the clustering technique involving genetic algorithm (GA) and radial basis function (RBF) interpolation. The parameterized environmental influences are mapped directly onto corresponding HTC values in each CD. Thus, CDs serve as look-up tables which provide boundary data (HTC values along with nodal information) under several load cases (combinations of environmental influences) for thermo-elastic simulations. Ultimately, a decoupled fluid-structural simulation system is obtained where boundary (convection) data for thermo-mechanical simulations can be directly obtained from CDs and would no longer require fluid simulations to be carried out again. Thus, a novel approach for the correction of thermo-elastic deformations on a machine tool is obtained.