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In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.
The simulator aRTist combines analytical and Monte Carlo methods to efficiently model the radiographic process of industrial radiology. In this contribution we focus on virtual computer tomography, the simulation of tomographic scans. The possibilities to simulate complex scanning trajectories are shown in combination with the tomographic reconstruction using individual projection matrices.
This talk presents a new application for high-spatial resolution eddy current testing (ET) with magneto resistive (MR) sensor arrays. With rising popularity and availability of additive manufacturing (AM), companies mainly in the aerospace sector, set high requirements on quality control of AM parts, especially produced with selective laser melting (SLM). Since it was shown that those parts are prawn to flaws like pores or cracks, every part needs to be tested. Therefore, NDT Methods, like ET, could help to characterize SLM parts. Research on ET has shown, that offline ET with high spatial resolution MR sensor arrays is possible and that flaws as small as 50 µm could be detected while significantly reducing testing time. In this talk a first approach on automated online ET method for testing SLM parts is proposed. An approach with hundreds of MR sensor is made to maintain spatial resolution and short testing times. Classic signal conditioning methods are used to reduce cost and complexity while maintaining high testing bandwidths. The proposed idea enables further research on automated generation of testing reports, process control or automated flaw curing.
Remote gas sensors like those based on the Tunable Diode Laser Absorption Spectroscopy (TDLAS) enable mobile robots to scan huge areas for gas concentrations in reasonable time and are therefore well suited for tasks such as gas emission surveillance and environmental monitoring.
A further advantage of remote sensors is that the gas distribution is not disturbed by the sensing platform itself if the measurements are carried out from a sufficient distance, which is particularly interesting when a rotary-wing platform is used.
Since there is no possibility to obtain ground truth measurements of gas distributions, simulations are used to develop and evaluate suitable olfaction algorithms.
For this purpose several models of in-situ gas sensors have been developed, but models of remote gas sensors are missing.
In this paper we present two novel 3D ray-tracer-based TDLAS sensor models. While the first model simplifies the laser beam as a line, the second model takes the conical shape of the beam into account.
Using a simulated gas plume, we compare the line model with the cone model in terms of accuracy and computational cost and show that the results generated by the cone model can differ significantly from those of the line model.
The applicability of 1D-quadrupole-model on the depth estimation of overload-induced delaminations is tested in this contribution. While classical 1D-methods like Pulsed Phase Transformation and Thermographic Signal Reconstruction determine the depth of a defect by one parameter, a two-layer quadrupole model provides two parameters: depth and thermal resistance. In addition, the convectional losses at the surfaces may be considered. The defect investigated is a large-scale delamination in glass fibre reinforced polymer generated by tension overload.
Using magnetic materials for energy conversion as an example, this lecture shows how X-ray tomography investigations can contribute to structure elucidation in composites and solid samples. The components are tested non-destructively in order to characterize cracks, pores and other defects and their influence on the functional properties three-dimensionally and in good time in the life cycle of the material. If you combine microtomography with other methods of magnetic material characterization, you can make unique statements about the structure and the functional properties.