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Im Rahmen der Forschungsprojekte FeGeb und SPAI wurden bei zahlreichen Probanden Hautproben an mehreren Stellen des Gesichts, sowie der Arme und Hände, mit einem Nahinfrarot-Spektrometer (NIR, auch „Short Wave Infrared“, SWIR) erfasst und die Gesichter der Probanden zusätzlich mit einer hochwertigen Farb-Kamera, sowie einem selbst entwickelten multispektralen NIR-Kamerasystem aus mehreren Perspektiven aufgenommen. Vorrangiges Ziel dieser Messreihe war es, die Robustheit des an der Hochschule entwickelten Verfahrens zur berührungslosen Hauterkennung mittels multispektraler Nahinfrarotsensorik nachzuweisen. Haut ist im nahinfraroten Spektralbereich unabhängig von Geschlecht, Alter und Hauttyp sehr gut von anderen Materialien unterscheidbar. Weiterhin konnte mit Hilfe der so aufgenommenen Daten ein Klassifikator trainiert werden, der auch „Fälschungen“ wie beispielsweise Latexmasken zuverlässig von echter Haut unterscheiden kann.
Ein Teil der aus dieser Messreihe entstandenen Datenbank kann zum Download angefordert und für wissenschaftliche und akademische Zwecke in Forschung und Lehre kostenfrei verwendet werden.
Surface-enhanced Raman spectroscopy (SERS) with subsequent chemometric evaluation was performed for the rapid and non-destructive differentiation of seven important meat-associated microorganisms, namely Brochothrix thermosphacta DSM 20171, Pseudomonas fluorescens DSM 4358, Salmonella enterica subsp. enterica sv. Enteritidis DSM 14221, Listeria monocytogenes DSM 19094, Micrococcus luteus DSM 20030, Escherichia coli HB101 and Bacillus thuringiensis sv. israelensis DSM 5724. A simple method for collecting spectra from commercial paper-based SERS substrates without any laborious pre-treatments was used. In order to prepare the spectroscopic data for classification at genera level with a subsequent chemometric evaluation consisting of principal component analysis and discriminant analysis, a pre-processing method with spike correction and sum normalisation was performed. Because of the spike correction rather than exclusion, and therefore the use of a balanced data set, the multivariate analysis of the data is significantly resilient and meaningful. The analysis showed that the differentiation of meat-associated microorganisms and thereby the detection of important meat-related pathogenic bacteria was successful on genera level and a cross-validation as well as a classification of ungrouped data showed promising results, with 99.5 % and 97.5 %, respectively.
In the context of the Franco-German research project Re(h)strain, this work focuses on a global system analysis integrating both safety and security analysis of international and/or urban railway stations. The Re(h)strain project focuses on terrorist attacks on high speed train systems and investigates prevention and mitigation measures to reduce the overall vulnerability and strengthen the system resilience. One main criterion regarding public transport issues is the number of passengers. For example, the railway station of Paris “Gare du Nord” deals with a bigger number of passengers than the biggest airport in the world (SNCF open Data 2014), the Atlanta airport, but in terms of passengers, it is only around the 23rd rank railway station in the world. Due to the enormous mass of people, this leads to the system approach of breaking out the station into several classes of zones, e.g. entrance, main hall, quays, trains, etc. All classes are analysed considering state-of-the-art parameters, like targets attractiveness, feasibility of attack, possible damage, possible mitigation and defences. Then, safety incidence of security defence is discussed in order to refine security requirement with regard to the considered zone. Finally, global requirements of security defence correlated to the corresponding class of zones are proposed.
The choice of suitable semiconducting metal oxide (MOX) gas sensors for the detection of a specific gas or gas mixture is time-consuming since the sensor’s sensitivity needs to be characterized at multiple temperatures to find its optimal operating conditions. To obtain reliable measurement results, it is very important that the power for the sensor’s integrated heater is stable, regulated and error-free (or error-tolerant). Especially the error-free requirement can be only be achieved if the power supply implements failure-avoiding and failure-detection methods. The biggest challenge is deriving multiple different voltages from a common supply in an efficient way while keeping the system as small and lightweight as possible. This work presents a reliable, compact, embedded system that addresses the power supply requirements for fully automated simultaneous sensor characterization for up to 16 sensors at multiple temperatures. The system implements efficient (avg. 83.3% efficiency) voltage conversion with low ripple output (<32 mV) and supports static or temperature-cycled heating modes. Voltage and current of each channel are constantly monitored and regulated to guarantee reliable operation. To evaluate the proposed design, 16 sensors were screened. The results are shown in the experimental part of this work.
Artificial waters containing the xenobiotics atrazine, bisphenol A and chlorendic acid were treated by use of micro-disinfection apparatus, based on electrochemical ozone production. The design and working principle, as well as the applicability of the apparatus for the degradation of the target compounds is presented. The initial concentrations of the analytes were chosen to be in the mg L−1 order. Degradation and transformation of the analytes was determined via LC-MS, UV/Vis, and IC. Bisphenol A was degraded completely within short ozonation times, but complete mineralization could not be achieved. Ion chromatography indicated formic and oxalic acid to be transformation products. For atrazine a degradation of 96% could be achieved within 3 h. Intermediate transformation products, like desethylatrazine, desisopropylatrazine, and desethyl-desisopropylatrazine, are formed and further degraded to formic acid and chloride. Chlorendic acid was degraded by up to 40% of the initial concentration. Analyses by UV/Vis and IC again showed formic acid, chloride, and also chlorate to be transformation products.
In the presented project, new approaches for the prevention of hand movements leading to hazards and for non-contact detection of fingers are intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and/or unloading. Two new detection principles are explained. The first is the distinction between skin and wood or other material by spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliable. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The second principle is video image processing to detect persons, arms and fingers. In the first stage of development the detection of upper limb extremities within a defined hazard area by means of a computer based video image analysis is investigated.
Im Arbeitsschutz spielt die Detektion von Fingern, Händen und Armen, insbesondere bei handbeschickten Maschinen, eine große Rolle. Gängige Schutzeinrichtungen, wie Lichtgitter, Laserscanner oder Ultraschallschutzeinrichtungen, können zwar generell Hindernisse im Gefahrenbereich von Maschinen erkennen, sind aber nicht in der Lage, zwischen Produktionsgut und Körperteilen zu unterscheiden. Die Deutsche Gesetzliche Unfallversicherung hat deshalb seit 2004 ein Forschungsvorhaben der Fachhochschule Bonn-Rhein-Sieg im Fachbereich Informatik gefördert, das zum Ziel hatte, Menschen und deren Finger und Hände durch ihre besondere Form und Farbe zu erkennen und von Produktionsgut zu unterscheiden. Als besonders kritischer Fall wurde dabei das Arbeiten an einer Tisch- und Formatkreissäge ausgewählt: Zum einen weil sich Hölzer nur schwer von Händen unterscheiden lassen, zum anderen weil an diesen Maschinen besonders viele schwere Unfällen passieren.
The FIVIS simulator system addresses the classical visual and acoustical cues as well as vestibular and further physiological cues. Sensory feedback from skin, muscles, and joints are integrated within this virtual reality visualization environment. By doing this it allows for simulating otherwise dangerous traffic situations in a controlled laboratory environment. The system has been successfully applied for road safety education applications of school children. In further research studies it is applied to perform multimedia perception experiments. It has been shown, that visual cues dominate by far the perception of visual depth in the majority of applications but the quality of depth perception might depend on the availability of other sensory information. This however, needs to be investigated in more detail in the future.
The device (10) has a handrail (18) provided with an optical contactless monitoring device formed as an active sensor system, where the monitoring device is arranged in a region of a guide (14) of the handrail at a front base (16) of an escalator (12) or a moving pavement. The monitoring device has two transmission paths (28, 30) with wavelength bands that are different from each other, where one of the paths includes the handrail. Ratio or difference between signals of the paths is used for recognizing foreign bodies e.g. hands of adults and children.
The freshness changes in poultry fillets during storage were studied using a portable fiber-optic Raman spectrometer. Poultry fillets with the same storage life (9 days) and expiry date were purchased from a local store and stored at 4 °C. Their Raman spectra were measured on a daily basis up to day 21 using a QE Pro-Raman spectrometer with a laser excitation wavelength of 785 nm. The complex spectra were analyzed using Principal Components Analysis (PCA), which resulted in a separation of the samples into three quality classes according to their freshness: fresh, semi-fresh, and spoiled. These classes were based on and similar to the information inferred from the product label on the packages of poultry fillets. The PCA loadings revealed a decrease in the protein content of the poultry meat during spoilage, an increase in the formation of free amino acids, an increase in oxidation of amino acid residues, and an increase in microbial growth on the surface of the poultry fillets, as well as revealing information about hydrophobic interaction around the aliphatic residues. Similar groupings (fresh, semi-fresh, and spoiled) were also obtained from the results of an Agglomerative Hierarchical Cluster Analysis (AHCA) of the first five principal components. The results allow the conclusion that the portable fiber-optic Raman spectrometer can be used as a reliable and fast method for real-time freshness evaluation of poultry during storage.
The proper use of protective hoods on panel saws should reliably prevent severe injuries from (hand) contact with the blade or material kickbacks. It also should minimize long-term lung damages from fine-particle pollution. To achieve both purposes the hood must be adjusted properly by the operator for each workpiece to fit its height. After a work process is finished, the hood must be lowered down completely to the bench. Unfortunately, in practice the protective hood is fixed at a high position for most of the work time and herein loses its safety features. A system for an automatic height adjustment of the hood would increase comfort and safety. If the system can distinguish between workpieces and skin reliably, it furthermore will reduce occupational hazards for panel saw users. A functional demonstrator of such a system has been designed and implemented to show the feasibility of this approach. A specific optical sensor system is used to observe a point on the extended cut axis in front of the blade. The sensor determines the surface material reliably and measures the distance to the workpiece surface simultaneously. If the distance changes because of a workpiece fed to the machine, the control unit will set the motor-adjusted hood to the correct height. If the sensor detects skin, the hood will not be moved. In addition a camera observes the area under the hood. If there are no workpieces or offcuts left under the hood, it will be lowered back to the default position.
Entering the work envelope of an industrial robot can lead to severe injury from collisions with moving parts of the system. Conventional safety mechanisms therefore mostly restrict access to the robot using physical barriers such as walls and fences or non-contact protective devices including light curtains and laser scanners. As none of these mechanisms applies to human-robot-collaboration (HRC), a concept in which human and machine complement one another by working hand in hand, there is a rising need for safe and reliable detection of human body parts amidst background clutter. For this application camera-based systems are typically well suited. Still, safety concerns remain, owing to possible detection failures caused by environmental occlusion, extraneous light or other adverse imaging conditions. While ultrasonic proximity sensing can provide physical diversity to the system, it does not yet allow to reliably distinguish relevant objects from background objects.This work investigates a new approach to detecting relevant objects and human body parts based on acoustic holography. The approach is experimentally validated using a low-cost application-specific ultrasonic sensor system created from micro-electromechanical systems (MEMS). The presented results show that this system far outperforms conventional proximity sensors in terms of lateral imaging resolution and thus allows for more intelligent muting processes without compromising the safety of people working close to the robot. Based upon this work, a next step could be the development of a multimodal sensor systems to safeguard workers who collaborate with robots using the described ultrasonic sensor system.
