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- 8.1 Sensorik, mess- und prüftechnische Verfahren (35) (entfernen)
Paper des Monats
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The current establishment of stretchable electronics to form a seamless link between soft or even living materials and the digital world is at the forefront of multidisciplinary research efforts, bridging physics, engineering and materials science. Magnetic functionalities can provide a sense of displacement, orientation or proximity to this novel formulation of electronics. This work reviews the recent development of stretchable magnetic field sensorics relying on the combination of metallic thin films revealing a giant magnetoresistance effect with elastomeric materials. Stretchability of the magnetic nanomembranes is achieved by specific morphologic features (e.g. wrinkles or microcracks), which accommodate the applied tensile deformation while maintaining the electrical and magnetic integrity of the sensor device. The entire development, from the demonstration of the world’s first elastically stretchable magnetic sensor to the realization of a technology platform for robust, ready-to-use elastic magnetosensorics is described. Soft giant magnetoresistive elements exhibiting the same sensing performance as on conventional rigid supports, but with fully strain invariant properties up to 270% stretching have been demonstrated. With their unique mechanical properties, these sensor elements readily conform to ubiquitous objects of arbitrary shapes including the human skin. Stretchable magnetoelectronic sensors can equip soft and epidermal electronic systems with navigation, orientation, motion tracking and touchless control capabilities. A variety of novel technologies, like electronic skins, smart textiles, soft robotics and actuators, active medical implants and soft consumer electronics will benefit from these new magnetic functionalities.
This work focuses on the design and fabrication of low-cost and fast-response of an electronic nose (E-nose) based on semiconductor gas sensors, for discriminating some synthetic gases such as ammonia (NH3), ethanol (C2H5OH), and hydrogen sulfide (H2S). Additionally, the capability of separating different concentration levels of each considered gases was checked. Dataset treatment of E-nose by using Principal Component Analysis (PCA) showed a good discrimination of the different synthetic gases. Furthermore, perfect classification was reached of different concentration levels of the analysed gases by using Discriminant Function Analysis (DFA). In the light of these results, it could be stated that the developed E-nose system constitutes an inexpensive, rapid, simple to use, and efficient tool for synthetic gases detection.
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).
Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions.
Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of “bouts”, a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration.
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.
The vulnerability of low-quality concrete of some bridges to ageing and deterioration while they are exposed to environmental conditions during their service life, influence of growing population and climate changes, is a well-known effect and requires survey. For survey, the development of a low cost, cost-efficient sensor network to be embedded for continuous or attached to the surface for periodic monitoring is essential.
Changing ground water conditions, flood or even leakage in fresh or disposal of waste water can lead to in-creased moisture content in building materials and structural elements as walls or floors. Moisture allows the transport of other adverse chemicals that might reduce the durability of structures. The paper presents a feasibility study about the capability of microwave modules as bluetooth® or ZigBee with frequency range at 2,4 GHz to create advanced Wireless Sensor Networks (WSN) for estimation and visualization of moisture distribution in infrastructure assets. It was found that the value of the received signal strength indication (RSSI) depends on the moisture content and can be the basis for the moisture distribution inside a massive structure.
The microwave modules may be used to compose networks outside and inside of building materials or structural elements. The higher the number of connections between BLE modules, the more precise and the more distant information can be obtained from the network. Mesh networking was applied to increase the quantitative information.
This work reported the investigation on the effect of relaxation to the permittivity (epsilon' r ) characteristic of Mg1-x Zn x TiO3 ceramics for x = 0 – 0.5 (MZT0 – MZT0.5) measured from 1 Hz to 330 MHz. Within that frequency range, the relaxation effect that consists of the space charge (SC) and the dipolar (D) polarization mechanisms were identified. The contribution of the D relaxation in MZT0 – MZT0.2 systems extents overall from about 100 Hz to 330 MHz, while that in MZT0.3 – MZT0.5 systems is from 50 kHz to 330 MHz. The remaining frequencies, i.e. from 1 to 90 Hz for MZT0 – MZT0.2 and from 1 Hz to 50 kHz for MZT0.3 – MZT0.5, are attributed to the SC relaxation. The D polarization mechanism provides constant epsilon' r values which vary from (15.4 – 17.0) ± 0.3 throughout the samples. Contribution of the SC polarization mechanism to the characteristic is supported by the simultaneous presence of different content and level of resistivity of the secondary phase of (Mg1-αZnα)2TiO4 in MZT0 – MZT0.2 systems and of (Zn1-αMgα)2TiO4 in MZT0.3 – MZT0.5, along with the presence of the main Mg1-x Zn x TiO3 phase, as a result of the variation of zinc content in the systems.
In mobile robot applications, some sensors such as open-path gas detectors or laser rangefinders need to be aimed at specific targets in order to get the desired measurements. To do this in a fast and elegant manner, we present a spherical parallel manipulator with three degrees of freedom. Compared to typical serial manipulators, it offers superior dynamics and structural stiffness, which are important parameters for this type of task. We present the mechanical design and derive kinematic equations both to compute set-points for the desired orientation and to estimate the current state of the system. A PID controller is used to generate control signals.
Trace humidity was measured by using miniaturized planar coulometric sensors in technical gases such as hydrogen, nitrogen, helium, nitrous oxide, and synthetic air. Frost point temperatures tf in the gases ranged from −60 °C to −30 °C, which is equivalent to a vapour mole fraction xv from 10 μmol mol−1 to 376 μmol mol−1. In addition, the generated humidity was determined by using a precision dew point hygrometer as reference. Nonlinear calibration functions were calculated that correlated electric current (sensor signal) and reference humidity. Parameters of functions were tested with one-way analysis of variances (ANOVA) to prove if all used sensors had a similar behavior in the same gas during experiments. Results of ANOVA confirmed that averaged functions can be applied for trace humidity measurement in nitrogen, helium, nitrous oxide, and synthetic air. The calculated functions were negligibly different for nitrogen, helium, and synthetic air. In humidified nitrous oxide, a minor change of parameters was observed due to lower electrical currents. In total contrast to that, the measured sensor signals were significantly higher in humidified hydrogen and each sensor required its own calibration function. The reason was a recombination effect that favoured multiple measurements of water molecules. Nevertheless, it was possible to measure continuously trace humidity in all tested gases by using coulometric sensors with an expanded uncertainty below 2 K (k = 2).
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.
In this communication a novel concept for pH sensing is introduced which is specifically adapted to monitor carbonation induced corrosion in concrete structures. The method is based on a ratiometric measurement principle, exploiting the pH sensitive colour switching of thymol blue in the basic pH regime and the emissive properties of two different (Zn)CdSe/ZnS core shell quantum dots. The transition point of thymol blue in a Hydrogel D4 matrix was determined to be at around pH 11.6, which fits ideally to the intended application. Next to the fundamental spectroscopic characterization of the ratiometric response, a new design for a sensor head, suitable for the incorporation into concrete matrices is presented. Toward this, a manufacturing process was developed which includes the preparation of a double layer of polymers containing either thymol blue or a quantum dot mixture inside a porous ceramic tube. Results of a proof-of-priciple performance test of the sensor head in solutions of different pH and in cement specimens are presented, with encouraging results paving the way for future field tests in concrete.
Contamination of natural bodies of water or soil with oils and lubricants (or generally, hydrocarbon derivatives such as petrol, fuels, and others) is a commonly found phenomenon around the world due to the extensive production, transfer, and use of fossil fuels. In this work, we develop a simple system for the on-field detection of total petroleum hydrocarbons (TPHs) in water and soil. The test is based on the measurement of the fluorescence signal emitted by the molecular rotor 2-[ethyl[4-[2-(4-nitrophenyl)ethenyl]phenyl]amino]ethanol (4-DNS-OH). This dye is embedded in a hydrophobic polymeric matrix (polyvinylidene fluoride), avoiding interactions with water and providing a robust support for use in a test strip fashion. Together with the strips, an embedded optical system was designed for fluorescence signal read-out, featuring a Bluetooth low-energy connection to a commercial tablet device for data processing and analysis. This system works for the detection and quantification of TPHs in water and soil through a simple extraction protocol using a cycloalkane solvent with a limit of detection of 6 ppm. Assays in surface and sea waters were conclusive, proving the feasibility of the method for in-the-field operation.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize a 5 cm wide chemical trail, a detection criterion was developed that uses only relative changes in the transient phase of the sensor response. The reduction in signal strength dependence improves the robustness of its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot can correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
In this paper, we present 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) sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile octocopter. The TDLAS sensor provides integral gas concentration measurements but no information regarding the distance traveled by the laser diode's beam or the distribution of the gas along the optical path. We complemented the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from these integral concentration measurements. To allow for a rudimentary 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 first results showing the 2D plume reconstruction capabilities of the system under realistic conditions.
Air pollution within industrial scenarios is a major risk for workers, which is why detailed knowledge about the dispersion of dusts and gases is necessary. This paper introduces a system combining stationary low-cost and high-quality sensors, carried by ground robots and unmanned aerial vehicles. Based on these dense sampling capabilities, detailed distribution maps of dusts and gases will be created. This system enables various research opportunities, especially on the fields of distribution mapping and sensor planning. Standard approaches for distribution mapping can be enhanced with knowledge about the environment’s characteristics, while the effectiveness of new approaches, utilizing neural networks, can be further investigated. The influence of different sensor network setups on the predictive quality of distribution algorithms will be researched and metrics for the quantification of a sensor network’s quality will be investigated.
Imperceptible magnetic sensor matrix system integrated with organic driver and amplifier circuits
(2020)
Artificial electronic skins (e-skins) comprise an integrated matrix of flexible devices arranged on a soft, reconfigurable surface. These sensors must perceive physical interaction spaces between external objects and robots or humans. Among various types of sensors, flexible magnetic sensors and the matrix configuration are preferable for such position sensing. However, sensor matrices must efficiently map the magnetic field with real-time encoding of the positions and motions of magnetic objects. This paper reports an ultrathin magnetic sensor matrix system comprising a 2 × 4 array of magnetoresistance sensors, a bootstrap organic shift register driving the sensor matrix, and organic signal amplifiers integrated within a single imperceptible platform. The system demonstrates high magnetic sensitivity owing to the use of organic amplifiers. Moreover, the shift register enabled real-time mapping of 2D magnetic field distribution.
One challenge associated with navigating a nano aerial robot swarm indoors in unstructured environments is, i.a., the limited air space. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined. In this paper, we investigate the impact of the downwash of a nano-drone on the stability of another nearby nano-drone. In the experiments, we found out that this downwash has a negative influence of a second nano-drone in a distance of around 1 m vertically and 0.2 m horizontally. Based on the obtained data, we developed a model describing the above-mentioned safety region to enable a safe operation of the swarm in these environments with fewer constraints.
Wood-based composites hold the promise of sustainable construction. Understanding the influence on wood cellular microstructure in the macroscopic mechanical behavior is key for engineering highperformance composites. In this work, we report a novel Individual Cell Tracking (ICT) approach for in-situ quantification of nanometer-scale deformations of individual wood cells during mechanical loading of macroscopic millimeter-scale wood samples. Softwood samples containing > 104 cells were subjected to controlled radial tensile and longitudinal compressive load in a synchrotron radiation micro-computed tomography (SRμCT) setup. Tracheid and wood ray cells were automatically segmented, and their geometric variations were tracked during load. Finally, interactions between microstructure deformations (lumen geometry, cell wall thickness), cellular arrangement (annual growth rings, anisotropy, wood ray presence) with the macroscopic deformation response were investigated. The results provide cellular insight into macroscopic relations, such as anisotropic Poisson effects, and allow direct observation of previously suspected wood ray reinforcing effects.
The method is also appropriate for investigation of non-linear deformation effects, such as buckling and deformation recovery after failure, and gives insight into less studied aspects, such as changes in lumen diameter and cell wall thickness during uniaxial load. ICT provides an experimental tool for direct validation of hierarchical mechanical models on real biological composites.