Refine
H-BRS Bibliography
- yes (93) (remove)
Departments, institutes and facilities
- Institut für Sicherheitsforschung (ISF) (93) (remove)
Document Type
- Article (43)
- Conference Object (34)
- Report (5)
- Doctoral Thesis (3)
- Patent (3)
- Contribution to a Periodical (2)
- Part of a Book (1)
- Conference Proceedings (1)
- Research Data (1)
Year of publication
Keywords
- Chemometrics (4)
- DNA typing (3)
- Raman spectroscopy (3)
- Classification (2)
- Cooperative Awareness Message (2)
- Discriminant analysis (2)
- Hyperspectral image (2)
- Intelligent Transport System (2)
- Principal Components Analysis (2)
- Privacy (2)
Optical gas sensors based on chiral-nematic liquid crystals (N* LCs) forming one-dimensional photonic crystals do not require electrical energy and have a considerable potential to supplement established types of sensors. A chiral-nematic phase with tunable selective reflection is induced in a nematic host LC by adding reactive chiral dopants. The selective chemical reaction between dopant and analyte is capable to vary the pitch length (the lattice constant) of the soft, self-assembled, one-dimensional photonic crystal. The progress of the ongoing chemical reaction can be observed even by naked eye because the color of the samples varies. In this work, we encapsulate the responsive N* LC in microscale polyvinylpyrrolidone (PVP) fibers via coaxial electrospinning. The sensor is, thus, given a solid form and has an improved stability against nonavoidable environmental influences. The reaction behavior of encapsulated and nonencapsulated N* LC toward a gaseous analyte is compared, systematically. Making use of the encapsulation is an important step to improve the applicability.
The simultaneous operation of multiple different semiconducting metal oxide (MOX) gas sensors is demanding for the readout circuitry. The challenge results from the strongly varying signal intensities of the various sensor types to the target gas. While some sensors change their resistance only slightly, other types can react with a resistive change over a range of several decades. Therefore, a suitable readout circuit has to be able to capture all these resistive variations, requiring it to have a very large dynamic range. This work presents a compact embedded system that provides a full, high range input interface (readout and heater management) for MOX sensor operation. The system is modular and consists of a central mainboard that holds up to eight sensor-modules, each capable of supporting up to two MOX sensors, therefore supporting a total maximum of 16 different sensors. Its wide input range is archived using the resistance-to-time measurement method. The system is solely built with commercial off-the-shelf components and tested over a range spanning from 100Ω to 5 GΩ (9.7 decades) with an average measurement error of 0.27% and a maximum error of 2.11%. The heater management uses a well-tested power-circuit and supports multiple modes of operation, hence enabling the system to be used in highly automated measurement applications. The experimental part of this work presents the results of an exemplary screening of 16 sensors, which was performed to evaluate the system’s performance.
Explorative experiments were done to figure out differences in the emission of volatile organic compounds (VOCs) of not infested trees and trees infested by Anoplophora glabripennis (Asian longhorn beetle, ALB), a quarantine pest. Therefore, VOCs from some native insect species, Anoplophora glabripennis infested Acer, stressed Acer, healthy Acer, Populus and Salix were obtained by enrichment on adsorbents. Qualitative analysis was done by thermal desorption gas chromatography coupled with a mass selective detector (TD-GC/MS). Altogether 169 substances were identified. 11 substances occur from ALB infested or mechanically damaged trees i.e. stressed trees, but not from healthy trees. (+)-Cyclosativene, (+)-α-longipinene, copaene and caryophyllene are detectable only from ALB-infested Acer not from mechanically damaged or healthy Acer. However, these substances are also emitted by healthy Salix. 2,4-Dimethyl-1-heptene is among all tree samples exclusively present in the ambience of ALB-infested trees. It´s rarely detectable from native insect species’ samples.
Kollaborative Industrieroboter werden für produzierende Unternehmen immer kosteneffizienter. Während diese Systeme für den menschlichen Mitarbeiter eine große Hilfe sein können, stellen sie gleichzeitig ein ernstes Gesundheitsrisiko dar, wenn die zwingend notwendigen Sicherheitsmaßnahmen nur unzureichend umgesetzt werden. Herkömmliche Sicherheitseinrichtungen wie Zäune oder Lichtvorhänge bieten einen guten Schutz, aber solch statische Schutzvorrichtungen sind in neuen, hochdynamischen Arbeitsszenarien problematisch.
Im Forschungsprojekt BeyondSPAI wurde ein Funktionsmuster eines Multisensorsystems zur Absicherung solcher dynamischer Arbeitsszenarien entworfen, implementiert und im Feld getestet. Kern des Systems ist eine robuste optische Materialklassifikation, die mit Hilfe eines intelligenten InGaAs-Kamerasystems Haut von anderen typischen Werkstückoberflächen (z.B. Holz, Metalle od. Kunststoffe) unterscheiden kann. Diese einzigartige Eigenschaft wird genutzt, um menschliche Mitarbeiter zuverlässig zu erkennen, so dass ein konventioneller Roboter in Folge als personenbewusster Cobot arbeiten kann.
Das System ist modular und kann leicht mit weiteren Sensoren verschiedenster Art erweitert werden. Es kann an verschiedene Marken von Industrierobotern angepasst werden und lässt sich schnell an bestehenden Robotersystemen integrieren. Die vier vom System bereitgestellten Sicherheitsausgänge können dazu verwendet werden - abhängig von der durchdrungenen Überwachungszone - entweder eine Warnung auszugeben, die Bewegung des Roboters auf eine sichere Geschwindigkeit zu verlangsamen, oder den Roboter sicher anzuhalten. Sobald alle Zonen wieder als „eindeutig frei von Personen“ identifiziert sind, kann der Roboter wieder beschleunigen, seine ursprüngliche Bewegung wiederaufnehmen und die Arbeit fortsetzen.
The application of Raman and infrared (IR) microspectroscopy is leading to hyperspectral data containing complementary information concerning the molecular composition of a sample. The classification of hyperspectral data from the individual spectroscopic approaches is already state-of-the-art in several fields of research. However, more complex structured samples and difficult measuring conditions might affect the accuracy of classification results negatively and could make a successful classification of the sample components challenging. This contribution presents a comprehensive comparison in supervised pixel classification of hyperspectral microscopic images, proving that a combined approach of Raman and IR microspectroscopy has a high potential to improve classification rates by a meaningful extension of the feature space. It shows that the complementary information in spatially co-registered hyperspectral images of polymer samples can be accessed using different feature extraction methods and, once fused on the feature-level, is in general more accurately classifiable in a pattern recognition task than the corresponding classification results for data derived from the individual spectroscopic approaches.
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.
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.
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.
The detection of human skin in images is a very desirable feature for applications such as biometric face recognition, which is becoming more frequently used for, e.g., automated border or access control. However, distinguishing real skin from other materials based on imagery captured in the visual spectrum alone and in spite of varying skin types and lighting conditions can be dicult and unreliable. Therefore, spoofing attacks with facial disguises or masks are still a serious problem for state of the art face recognition algorithms. This dissertation presents a novel approach for reliable skin detection based on spectral remission properties in the short-wave infrared (SWIR) spectrum and proposes a cross-modal method that enhances existing solutions for face verification to ensure the authenticity of a face even in the presence of partial disguises or masks. Furthermore, it presents a reference design and the necessary building blocks for an active multispectral camera system that implements this approach, as well as an in-depth evaluation. The system acquires four-band multispectral images within T = 50ms. Using a machine-learning-based classifier, it achieves unprecedented skin detection accuracy, even in the presence of skin-like materials used for spoofing attacks. Paired with a commercial face recognition software, the system successfully rejected all evaluated attempts to counterfeit a foreign face.
A deployment of the Vehicle-2-Vehicle communication technology according to ETSI is in preparation in Europe. Currently, a policy for a necessary Public Key Infrastructure to enrol cryptographic keys and certificates for vehicles and infrastructure component is in discussion to enable an interoperable Vehicle-2-Vehicle communication. Vehicle-2-Vehicle communication means that vehicles periodically send Cooperative Awareness Messages. These messages contain the current geographic position, driving direction, speed, acceleration, and the current time of a vehicle. To protect privacy (location privacy, “speed privacy”) of vehicles and drivers ETSI provides a specific pseudonym concept. We show that the Vehicle-2-Vehicle communication can be misused by an attacker to plot a trace of sequent Cooperative Awareness Messages and to link this trace to a specific vehicle. Such a trace is non-disputable due to the cryptographic signing of the messages. So, the periodically sending of Cooperative Awareness Messages causes privacy problems even if the pseudonym concept is applied.
Die Detektion von Explosivstoffen stellt ein zentrales Feld der zivilen Sicherheitsforschung dar. Eine besondere Herausforderung liegt hierbei in dem Nachweis verpackter Substanzen, wie es bei Unkonventionellen Spreng- und Brandvorrichtung (USBV) häufig der Fall ist. Derzeit eingesetzte Verfahren arbeiten meist mit bildgebenden Techniken, durch die sich ein Anfangsverdacht ergibt. Der tatsächliche chemische Inhalt der USBV lässt sich jedoch nicht exakt ermitteln. Eine genaue Beurteilung der Gefährdung durch solche Substanzen ist allerdings von großer Bedeutung, insbesondere wenn die Entschärfung des Objekts in bewohntem Gebiet stattfinden muss. In der vorliegenden Arbeit wird ein Verfahren vorgestellt, das sich als Verifikationsverfahren bei bestehendem Anfangsverdacht gezielt einsetzen lässt. Hierzu wird mittels Laserbohrtechnik zunächst die äußere Hülle des zu untersuchenden Gegenstandes durchdrungen. Anschließend finden eine lasergestützte Probenahme des Inhalts sowie die Detektion unter Verwendung geeigneter Analysemöglichkeiten statt. Der Bohr- und Probenahmefortschritt wird über verschiedene spektroskopische und sensorische Verfahren begleitend überwacht. Zukünftig soll das System abstandsfähig auf Entschärfungsrobotern eingesetzt werden.
Der Asiatische Laubholzbockkäfer (Anoplophora glabripennis, kurz: ALB) ist ein Bockkäfer, der 2001 seinen Weg nach Europa fand. Er ist als Quarantäneschaderreger eingestuft und muss in Europa bekämpft werden. Eine der Möglichkeiten zum Aufspüren befallener Bäume ist der Einsatz von Spürhunden. Die Einstufung des ALB als Quarantäneschädling bringt große Probleme bei der Verwendung von Trainingsmaterial mit sich. Da es sich zudem um biologisches Material handelt, das geruchchemisch Änderungen und Variationen unterworfen ist, und da die für den Hund relevanten Geruchsstoffe nicht bekannt sind, ist es häufig schwierig, geeignete und frische Geruchsträger als Trainingshilfsmittel zur Verfügung zu stellen.
A deployment of the Vehicle-to-Vehicle communication technology according to ETSI is in preparation in Europe. Currently, a Public Key Infrastructure policy for Intelligent Transport Systems in Europe is in discussion to enable V2V communication. This policy set aside two classes of keys and certificates for ITS vehicle stations: long term authentication keys and pseudonymous keys and certificates. We show that from our point of view the periodic sent Cooperative Awareness Messages with extensive data have technical limitations and together with the pseudonym concept cause privacy problems.
Design of an Active Multispectral SWIR Camera System for Skin Detection and Face Verification
(2016)
Biometric face recognition is becoming more frequently used in different application scenarios. However, spoofing attacks with facial disguises are still a serious problem for state of the art face recognition algorithms. This work proposes an approach to face verification based on spectral signatures of material surfaces in the short wave infrared (SWIR) range. They allow distinguishing authentic human skin reliably from other materials, independent of the skin type. We present the design of an active SWIR imaging system that acquires four-band multispectral image stacks in real-time. The system uses pulsed small band illumination, which allows for fast image acquisition and high spectral resolution and renders it widely independent of ambient light. After extracting the spectral signatures from the acquired images, detected faces can be verified or rejected by classifying the material as "skin" or "no-skin". The approach is extensively evaluated with respect to both acquisition and classification performance. In addition, we present a database containing RGB and multispectral SWIR face images, as well as spectrometer measurements of a variety of subjects, which is used to evaluate our approach and will be made available to the research community by the time this work is published.
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.
In der vorliegenden Arbeit wird ein neuartiges Verfahren zur Echtzeitüberwachung von Laserbohrprozessen vorgestellt. Die Untersuchungen werden an unterschiedlichen Materialien unter Einsatz eines passiv-gütegeschalteten Nd:YAG Lasers durchgeführt. Prozessbegleitend findet eine Aufzeichnung der akustischen Emissionen mit anschließender Analyse durch schnelle Fourier-Transformation statt. Hierdurch lassen sich der Durchbruch beim Bohren durch ein Material sowie der Materialübergang mehrschichtiger Systeme detektieren. Die akustischen Messungen werden durchAuswertung der Pulsfolge des Lasers mittels einer Fotodiode gestützt. Hierbei zeigt sich eine gute Übereinstimmung der im akustischen Spektrum dominanten Frequenz mit der jeweils im Laserburstauftretenden Pulsfrequenz. Das vorgestellte Verfahren ermöglicht eine Echtzeitüberwachung beim Laserbohren mittels kostengünstiger und einfacher Hardware. Zudem zeichnet es sich im Gegensatz zu bestehenden Verfahren durch eine hohe Robustheit gegen äußere Störeinflüsse aus, da eine frequenzbasierte Auswertung stattfindet.
Unkonventionelle Spreng- und Brandvorrichtungen sind Bedrohungen in den weltweiten Konfliktherden und werden bei terroristischen Aktivitäten verwendet. Der Schutz von Menschen und Material erfordert daher effektive Gegenmaßnahmen. Dazu gehört auch die Anforderung an Sicherheitskräfte oder militärisches Personal, unbekannte Substanzfunde mit geringem zeitlichem und logistischem Aufwand vor Ort als gefährdend oder unkritisch einzustufen. Um Explosivstoffe von nicht-explosiven Materialien zu unterscheiden, kann die bei Explosivstoffen initiierbare, stark exotherme Reaktion genutzt werden. Diese resultiert in Strahlungsemissionen sowie in lokaler Druck- und Temperaturerhöhung. Die Messung dieser Reaktionseffekte und die Anforderung an eine mobile, einfach zu bedienende und robuste Analytik werden durch ein System ermöglicht, das Proben im einstelligen mg-Bereich durch schnelles Erhitzen auf mikrostrukturierten Heizern zum chemischen Umsatz anregt. Die emittierte Strahlung wird mit Photodioden im Bereich des sichtbaren und nah-infraroten Lichts aufgenommen, ein Sensor registriert die Druckerhöhung in einer geschlossenen Versuchskammer. In einem zweiten Aufbau werden die gasförmigen Reaktionsprodukte über ein Sensorarray von vier kommerziellen Gassensoren geleitet und die Signalantworten der Halbleitergassensoren mittels Hauptkomponentenanalyse ausgewertet. Die Ergebnisse zeigen, dass die schnelle thermische Aktivierung für die untersuchten primären Explosivstoffe, Treibladungspulver, sowie Trinitrotoluol (TNT) reproduzierbar erfolgt. Nicht-Explosivstoffe werden dabei im untersuchten Umfang sicher als unkritisch erkannt. Die Auswertung der Gassensorsignale liefert eine Unterscheidung von Nitrat- und Peroxid-basierten Sprengstoffen sowie von nicht-explosiven Substanzen.
Durch Dotierung eines nematischen Flüssigkristalles mit einer chiralen Substanz wird eine helikal strukturierte Phase induziert, die in der Lage ist, einfallendes Licht wellenlängenselektiv zu reflektieren. Bei der Reaktion des Dotiermittels mit einem gasförmigen Analyten verändern sich die Ganghöhe dieser Struktur und damit die reflektierte Wellenlänge. Liegt diese im Bereich des sichtbaren Lichts, ist eine Farbänderung mit dem menschlichen Auge zu beobachten. Es ist dabei sinnvoll den Flüssigkristall z.B. in einem Polymer einzukapseln, um ihn vor mechanischen Einflüssen und Umwelteinflüssen zu schützen. Eine Möglichkeit zur Einkapselung ist das koaxiale Elektrospinnen. Vorteile sind unter anderem die Realisierung einer großen Oberfläche und einer sehr geringen Wanddicke der schützenden Schale, die die Diffusion von Gasen durch die Wand hindurch ermöglicht. Um die Funktionsfähigkeit eines solchen Sensors zu testen, wurde ein CO2-sensitiver Flüssigkristall verwendet. Dieser wurde in eine Schale aus Polyvinylpyrrolidon (PVP) versponnen und die Reaktion mit CO2 spektroskopisch analysiert.
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.
Persons entering the working range of industrial robots are exposed to a high risk of collision with moving parts of the system, potentially causing severe injuries. Conventional systems, which restrict the access to this area, range from walls and fences to light barriers and other vision based protective devices (VBPD). None of these systems allow to distinguish between humans and workpieces in a safe and reliable manner. In this work, a new approach is investigated, which uses an active near-infrared (NIR) camera system with advanced capabilities of skin detection to distinguish humans from workpieces based on characteristic spectral signatures. This approach allows to implement more intelligent muting processes and at the same time increases the safety of persons working close to the robots. The conceptual integration of such a camera system into a VBPD and the enhancement of person detection methods through skin detection are described and evaluated in this paper. Based upon this work, next steps could be the development of multimodal sensor systems to safeguard working ranges of collaborating robots using the described camera system.
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.
This paper presents recent research on an active multispectral scanning sensor capable of classifying an object's surface material in order to distinguish between different kinds of materials and human skin. The sensor itself has already been presented in previous work and can be used in conjunction with safeguarding equipment at manually-fed machines or robot workplaces, for example. This work shows how an extended sensor system with advanced material classifiers can be used to provide additional value by distinguishing different materials of work pieces in order to suggest different tools or parameters for the machine (e.g. the use of a different saw blade or rotation speed at table saws). Additionally, a first implementation and evaluation of an active multispectral camera system addressing new safety applications is described. Both approaches intend to increase the productivity and the user's acceptance of the sensor technology.