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Today, the assembly of laser systems requires a large share of manual operations due to its complexity regarding the optimal alignment of optics. Although the feasibility of automated alignment of laser optics has been shown in research labs, the development effort for the automation of assembly does not meet economic requirements – especially for low-volume laser production. This paper presents a model-based and sensor-integrated assembly execution approach for flexible assembly cells consisting of a macro-positioner covering a large workspace and a compact micromanipulator with camera attached to the positioner. In order to make full use of available models from computer-aided design (CAD) and optical simulation, sensor systems at different levels of accuracy are used for matching perceived information with model data. This approach is named "chain of refined perception", and it allows for automated planning of complex assembly tasks along all major phases of assembly such as collision-free path planning, part feeding, and active and passive alignment. The focus of the paper is put on the in-process image-based metrology and information extraction used for identifying and calibrating local coordinate systems as well as the exploitation of that information for a part feeding process for micro-optics. Results will be presented regarding the processes of automated calibration of the robot camera as well as the local coordinate systems of part feeding area and robot base.
High-intensity discharge lamps can be driven by radio-frequency signals in the ISM frequency band at 2.45 GHz, using a matching network to transform the impedance of the plasma to the source impedance. To achieve an optimal operating condition, a good characterization of the lamp in terms of radio frequency equivalent circuits under operating conditions is necessary, enabling the design of an efficient matching network. This paper presents the characterization technique for such lamps and presents the design of the required matching network. For the characterization, a high-intensity discharge lamp was driven by a monofrequent large signal at 2.45 GHz, whereas a frequency sweep over 300 MHz was performed across this signal to measure so-called small-signal hot S-parameters using a vector network analyzer. These parameters are then used as an equivalent load in a circuit simulator to design an appropriate matching network. Using the measured data as a black-box model in the simulation results in a quick and efficient method to simulate and design efficient matching networks in spite of the complex plasma behavior. Furthermore, photometric analysis of high-intensity discharge lamps are carried out, comparing microwave operation to conventional operation.
In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.