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Organisationseinheit der BAM
- 8.1 Sensorik, mess- und prüftechnische Verfahren (5) (entfernen)
In civil engineering, many structures are made of reinforced concrete. Most Degradation processes relevant to this material, e.g., corrosion, are related to an increased level of material moisture.
Therefore, moisture monitoring in reinforced concrete is regarded as a crucial method for structural health monitoring. In this study, passive radio frequency identification (RFID)-based sensors are embedded into the concrete. They are well suited for long-term operation over decades and are well protected against harsh environmental conditions. The energy supply and the data transfer of the humidity sensors are provided by RFID. The sensor casing materials are optimised to withstand the high alkaline environment in concrete, having pH values of more than 12. Membrane materials are also investigated to identify materials capable of enabling water vapour transport from the porous cement matrix to the embedded humidity sensor. By measuring the corresponding relative humidity with embedded passive RFID-based sensors, the cement hydration is monitored for 170 days.
Moreover, long-term moisture monitoring is performed for more than 1000 days. The Experiments show that embedded passive RFID-based sensors are highly suitable for long-term structural health monitoring in civil engineering.
In this paper, we introduce a nano aerial robot swarm for indoor air quality monitoring applications such as occupational health and safety of (industrial) workplaces. The concept combines a robotic swarm composing of nano Unmanned Aerial Vehicles (nano UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight metal oxide gas sensors for measuring the Total Volatile Organic Compound (TVOC) in ppb and estimating the eCO2 (equivalent calculated carbon-dioxide) concentration in ppm. TVOC is a measure for the indoor air quality. An indoor localization and positioning system will be used to estimate the absolute 3D position of the swarm like GPS. Based on this novel indoor air quality monitoring concept, the development and validation of new algorithms in the field of Mobile Robot Olfaction (MRO) are planned, namely gas source localization and gas distribution mapping. A test scenario will be built up to validate and optimize the gas-sensitive nano aerial robot swarm for the intended applications.
In this paper, we present and validate the concept of an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor with a 3-axis aerial stabilization gimbal for aiming at a versatile octocopter. While the TDLAS sensor provides integral gas concentration measurements, it does not measure the distance traveled by the laser diode’s beam nor the distribution of gas along the optical path. Thus, we complement the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from a set of integral concentration measurements. To allow for a fundamental ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present results showing its performance characteristics and 2D plume reconstruction capabilities under realistic conditions. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO).
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements.
Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold.
This paper describes the development of a semi-automatic gas measurement device presenting potentially a broad range of applications, noteworthy in the agricultural sector. Non-reversible fluorescent molecular sensors were designed and syn-thesized. Upon, integration into a hydrogel matrix with an optimal ratio of co-solvents, the sensors reacting selectively to ammonia were illuminated by excitation light to produce a concentration-correlated fluorescence emission. An automated mechanical-elec-trical device initiates a given gas mixture and thus simulates con-centrations similar to a threshold value. The aim of this project is to develop a sensor or a low-cost method which can monitor low concentrations of harmful gases and aid in their elimination or regulation in livestock housing, barns or stables.