The usage of embedded systems is omnipresent in our everyday life, e.g., in smartphones, tablets, or automotive devices. These devices are able to deal with challenging image processing tasks like real-time detection of faces or high dynamic range imaging. However, the size and computational power of an embedded system is a limiting demand. To help students understanding these challenges, a new lab course "Image and Video Signal Processing on Embedded Systems" has been developed and is presented in this paper. The Raspberry Pi 3 Model B and the open source programming language Python have been chosen, because of low hardware cost and free availability of the programming language. In this lab course the students learn handling both hard- and software, Python as an alternative to MATLAB, the image signal processing path, and how to develop an embedded image processing system, from the idea to implementation and debugging. At the beginning of the lab course an introduction to Python and the Raspberry Pi is given. After that, various experiments like the implementation of a corner detector and creation of a panorama image are prepared in the lab course. Students participating in the lab course develop a profound understanding of embedded image and video processing algorithms which is verified by comparing questionnaires at the beginning and the end of the lab course. Moreover, compared to a peer group attending an accompanying lecture with exercises, students having participated in this lab course outperform their peer group in the exam for the lecture by 0.5 on a five-point scale.
Friction has a considerable influence in metal forming both in economic and technical terms. This is especially true for sheet-bulk metal forming (SBMF). The contact pressure that occurs here can be low making Coulomb’s friction law advisable, but also very high so that Tresca’s friction law is preferable. By means of an elasto-plastic half-space model rough surfaces have been investigated, which are deformed in such contact states. The elasto-plastic half-space model has been verified and calibrated experimentally. The result is the development of a constitutive friction law, which can reproduce the frictional interactions for both low and high contact pressures. In addition, the law gives conclusion regarding plastic smoothening of rough surfaces. The law is implemented in the framework of the Finite-Element-Method. However, compared to usual friction relations the tribological interplay presented here comes with the disadvantage of rising numerical effort. In order to minimise this drawback, a model adaptive finite-element-simulation is performed additionally. In this approach, contact regions are identified, where a conventional friction law is applicable, where the newly developed constitutive friction law should be used, or where frictional effects are negligible. The corresponding goal-oriented indicators are derived based on the “dual-weighted-residual” (DWR) method taking into account both the model and the discretisation error. This leads to an efficient simulation that applies the necessary friction law in dependence of contact complexity.
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