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Wyszukujesz frazę "Dix, Martin" wg kryterium: Autor

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    Wyświetlanie 1-3 z 3
    Tytuł:
    Integration and verification of miniature fluid film pressure sensors in hydrodynamic linear guides
    Autorzy:
    Ibrar, Burhan
    Wittstock, Volker
    Regel, Joachim
    Dix, Martin
    Powiązania:
    https://bibliotekanauki.pl/articles/24084705.pdf
    Data publikacji:
    2023
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    hydrodynamic linear guide
    measurement technology
    oil film
    pressure measurement
    Opis:
    Previously, a 2D simulation model for hydrodynamic linear guides with two reduction factors has been developed to calculate oil film pressure and floating heights/angle numerically. However, no method was available to verify the oil film pressure experimentally but only with floating heights measurement. Therefore, different pressure sensor’s integration methods were tested in a stationary Plexiglas rail to measure fluid film pressure inside the lubrication gap. The pressure sensors were statically and dynamically calibrated. However, floating heights could not be measured with the preliminary used Plexiglas rail. This paper reports the suitable integration of pressure sensors into a stationary steel rail to compensate this drawback. It focuses on the measurement of pressure rise using pressure sensors inside the lubrication gap in combination with the floating heights. Experimental results have shown that the oil film pressure inside the lubrication gap can be measured using pressure sensors, which draw conclusions about cavitation and lack of lubrication. The variation of oil film pressure measured along the length of the carriage can be used to improve the simulation model i.e. the reduction factors. The pressure measurement can help to identify the lubrication conditions and further actions can be taken to improve the lubrication cycle.
    Źródło:
    Journal of Machine Engineering; 2023, 23, 3; 38--55
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Recognition of sports exercises using inertial sensor technology
    Autorzy:
    Krutz, Pascal
    Rehm, Matthias
    Schlegel, Holger
    Dix, Martin
    Powiązania:
    https://bibliotekanauki.pl/articles/30148258.pdf
    Data publikacji:
    2023
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    human activity recognition
    machine learning
    neural networks
    classifier
    Opis:
    Supervised learning as a sub-discipline of machine learning enables the recognition of correlations between input variables (features) and associated outputs (classes) and the application of these to previously unknown data sets. In addition to typical areas of application such as speech and image recognition, fields of applications are also being developed in the sports and fitness sector. The purpose of this work is to implement a workflow for the automated recognition of sports exercises in the Matlab® programming environment and to carry out a comparison of different model structures. First, the acquisition of the sensor signals provided in the local network and their processing is implemented. Realised functionalities include the interpolation of lossy time series, the labelling of the activity intervals performed and, in part, the generation of sliding windows with statistical parameters. The preprocessed data are used for the training of classifiers and artificial neural networks (ANN). These are iteratively optimised in their corresponding hyper parameters for the data structure to be learned. The most reliable models are finally trained with an increased data set, validated and compared with regard to the achieved performance. In addition to the usual evaluation metrics such as F1 score and accuracy, the temporal behaviour of the assignments is also displayed graphically, allowing statements to be made about potential causes of incorrect assignments. In this context, especially the transition areas between the classes are detected as erroneous assignments as well as exercises with insufficient or clearly deviating execution. The best overall accuracy achieved with ANN and the increased dataset was 93.7 %.
    Źródło:
    Applied Computer Science; 2023, 19, 1; 152-163
    1895-3735
    2353-6977
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimization of characteristic diagram based thermal error compensation via load case dependent model updates
    Autorzy:
    Naumann, Christian
    Glänzel, Janine
    Dix, Martin
    Ihlenfeldt, Steffen
    Klimant, Philipp
    Powiązania:
    https://bibliotekanauki.pl/articles/2086271.pdf
    Data publikacji:
    2022
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    thermal effect
    machine tool
    compensation
    regression analysis
    Opis:
    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.
    Źródło:
    Journal of Machine Engineering; 2022, 22, 2; 43--56
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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