Lang, Walter
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Lang, Walter
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Lang, Walter
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Item-typ:Veröffentlichung, Wireless Sensors and Actuators for Structural Health Monitoring of Fiber Composite Materials(2017-04-12); ; ; This work evaluates and investigates the wireless generation and detection of Lamb-waves on fiber-reinforced materials using surface applied or embedded piezo elements. The general target is to achieve wireless systems or sensor networks for Structural Health Monitoring (SHM), a type of Non-Destructive-Evaluation (NDE). In this sense, a fully wireless measurement system that achieves power transmission implementing inductive coils is reported. This system allows a reduction of total system weight as well as better integration in the structure. A great concern is the characteristics of the material, in which the system is integrated, because the properties can have a direct impact on the strength of the magnetic field. Carbon-Fiber-Reinforced-Polymer (CFRP) is known to behave as an electrical conductor, shielding radio waves with increasing worse effects at higher frequencies. Due to the need of high power and voltage, interest is raised to evaluate the operation of piezo as actuators at the lower frequency ranges. To this end, actuating occurs at the International Scientific and Medical (ISM) band of 125 kHz or low-frequency (LF) range. The feasibility of such system is evaluated extensively in this work. Direct excitation, is done by combining the actuator bonded to the surface or embedded in the material with an inductive LF coil and setting the circuit in resonance. A more controlled possibility, also explored, is the use of electronics to generate a Hanning-windowed-sine to excite the PWAS in a narrow spectrum. In this case, only wireless power is transmitted to the actuator node, and this lastly implements a Piezo-driver to independently excite Lamb-waves. Sensing and data transfer, on the other hand, is done using the high-frequency (HF) 13.56 MHz. The HF range covers the requirements of faster sampling rate and lower energy content. A re-tuning of the antenna coils is performed to obtain better transmission qualities when the system is implemented in CFRP. Several quasi-isotropic (QI) CFRP plates with sensor and actuator nodes were made to measure the quality of transmission and the necessary energy to stimulate the actuator-sensor system. In order to produce baselines, measurements are prepared from a healthy plate under specific temperature and humidity conditions. The signals are evaluated to verify the functionality in the presence of defects. The measurements demonstrate that it is possible to wirelessly generate Lamb-waves while early results show the feasibility to determine the presence of structural failure. For instance, progress has been achieved detecting the presence of a failure in the form of drilled holes introduced to the structure. This work shows a complete set of experimental results of different sensor/-actuator nodes.Dissertation451 193 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Design of a Biosensor for Detection of Bacteria in Water, by means of a Microfluidic System(2019-09-26); ; ; In the context of the continuous growth of the worldwide population and the rapid ongoing urbanization around the globe, the need for affordable and effective systems to detect hazardous substances and pathogens in water has gained importance. In order to address this need, multi-disciplinary research efforts from the fields of micro-technology and micro-biology have led to the emergence of microfluidic devices in the form of Lab-on-a-Chip (LoC) and Micro Total Analysis (µTAS) devices, which are capable to host analytical and biorecognition assays, previously restricted to laboratory environments. Traditionally, the development of these devices had benefited from the microelectronics fabrication techniques, and afforded the replication of sub-micrometer channels and structures, as well as the implementation of functional materials to integrate diverse types of sensors (e.g. temperature, pressure, etc) in the same microfluidic device. Nevertheless, the reduction of the fabrication cost has become a persistent goal in order to popularize their utilization. This has urged the application of alternative materials like thermoplastics and large batch production techniques such as injection molding and hot embossing, at the same time to have set new challenges to their reliable and reproducible integration as analytical devices. The present report describes the design, development and testing of a microfluidic device for biosensing of bacteria, by means of RNA hybridization and fluorescence detection. The device consits in a fully Cyclo-Olefin Copolymer (COC) microfluidic chip, in size of 25,5 x 37,75 mm, structured by hot embossing. The microfluidic channels and cavities sum up a fluid volume of about 139 µL, comprising a heating chamber, temperature sensor chambers, cooling channel and reaction chamber. The device layout includes 7 inlets for the sample fluid and diverse reagents plus 1 outlet. On-chip assay starts with the intake of a volume of 1 mL of water sample. The sample fluid is pumped through the heater chamber, where heat from a screen printed heater is applied to lyse the bacteria and release their RNA content to the running flow. Following the same stream, the fluid with released RNA flows across the cooling channel until the reaction chamber. The reaction chamber bottom surface, previously functionalized with capture oligomers complementary to the RNA target sequences, hosts hybridization reactions to capture the target RNA. The captured RNA is later tagged with a fluorescence molecule in a second hybridization. After washing off unbound analytes, the overall fluorescence emission is collected, filtered and quantified. The net fluorescence intensity measurement is then interpreted as an indicator of the concentration of the viable bacteria presented in the sample. The microfluidic chip was tested in a custom testbench that included particle filtering and pre-concentration of bacteria from raw samples, and fluorescence detection system that performed a limit of detection of 18 fmol, with a sensitivity of 63,08 photon count per fmol. Theoretical evaluation of the microfluidic chip at 0,1 mL/min predicted a mass transport and heat transport efficiency of 68,57% and 67,27%, respectively. Experimentally, the microfluidic device in the biosensing system completed successful detection of bacteria from raw water in less than 1 hour. Fluorescence detection was completed from hybridized bacterial RNA, that was retrieved in the same chip by heat lysis on a dilution of 2x10^8 of E. coli. Theoretical limit of detection of 24,87x10^3 CFU/mL was calculated. The microfluidic chip, integrated with the fluorescence detection system, proved its functionality as biosensing system for on-site applications, as well as its potential as a reference of a low-cost, disposable device for real-time monitoring and control of bacteria pollution.Dissertation419 218 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Modellierung und experimentelle Untersuchung von materialintegrierten Sensoren(2015-11-06); ; The thesis is divided in a theoretical and an experimental part. In the theoretical part investigations on the foreign body effect of a sensor in a material in terms of mechanical, thermal and thermo-mechanical loads are done. The second part is based on experiments on the foreign body effect to prove the results of the first part. Therefore temperature and force sensors are integrated in epoxy resin, aluminum and steel.Dissertation489 634 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Biosensing for the analysis of raw milk(2014-07-14); ; ; Appropriate methods for monitoring raw milk in food sectors are required in order to prevent health-related issues from consuming milk or fermented dairy products such as cheese and yogurt. Conventional systems used for this purpose require sophisticated instruments, highly technical staff and several days to yield an estimated contaminant concentration profile. Currently, there is no technology available for fast and sensitive identification of unwanted substances that evidences several concentration levels in raw milk. As a contribution to the progress of innovative biochemical sensing systems, this thesis presents the design, development and construction of a prototype, which combines the expertise of sensitive immunoassay process with micro total analysis system (µTAS) to identify specific compounds encountered in raw milk. Since the concept of µTAS appeared, the development of microfluidic devices and their application have increased enormously. Microfluidic devices offer a highly efficient platform for analysis of biomolecules due to the capacity for manipulating small amounts of liquid quickly and with high precision. Particle size estimation, particle separation, cell collection, manipulation and cell detection are some of many functions which could be performed through microfluidic systems. Based on these advantages, microfluidic devices in combination with an associated immunoassay system were used in the prototype to concentrate contamination patterns or specific compounds encountered in raw milk. The NANODETECT prototype developed in this thesis should provide an economic, efficient and sensitive platform for multicomponent detection of specific substances in raw milk without requiring sophisticated instruments and trained staff. This thesis was performed for the European project NANODETECT (Development of nanosensors for the detection of quality parameters along the food chain) funded by European Commission within the 7th framework program.Dissertation347 135 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Fungus Detection Using Computer Vision and Machine Learning Techniques(2019-10-02); ; ; Fungus is extremely disreputable and dangerous for food, human health and archives because it causes food loss, various life threatening diseases to human and destroy important documents. Thousands of different fungus species exist in the world and their spores always present indoor and outdoor environments. Its sign and symptom are non-specific in medical science for extremely large areas and containers, which poses severe threat to human health, food and archives. Numerous traditional techniques were applied to meet the challenge of early detection of fungus but all are costly, laborious, time-consuming and required skilled staff. This revolutionary era emphasizes the need for novel, simple, automatic fungal detection system to control the devastation caused by fungal species. In this research, we develop a fungus detection system and algorithms to automatically detect fungus. Three computer vision based techniques were developed for the detection of fungus spores. One of them used HOG based features and achieved convincing results. Other technique consisted of fusion of Fourier transform and SIFT features to achieve promising results. Third method based on superpixel and handcrafted features. The results of all these techniques encourage for the possibility of early detection of fungus spores from dirt particles. The other main objective of this research was to develop a CNN based approach for the detection and classification of different types of fungus spores. However, a large amount of data is an essential prerequisite for its effective application. In pursuing this idea, we developed a new novel fungus dataset of its kind, with the goal of advancing the state-of-the-art in fungus classification by placing the question of fungus detection. This is achieved by gathering various images of complex fungal spores by extracting samples from contaminated fruits, archives and lab incubated fungus colonies. These images primarily consisted of five different types of fungus spores and dirt. The fungus detection system was utilized to obtain these images. Which were further annotated to mark fungal spores as a region of interest using specially designed graphical user interface. As a result, 40,800 labeled images were used to develop fungus dataset to aid in precise fungus detection and classification. A CNN architecture was designed and it showed the promising result with an accuracy of 94.8%. The obtained results proved the possibility of early detection and classification of several types of fungus spores using CNN and could estimate all possible threats due to fungus.Dissertation800 538 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Plausibility check and energy management in a semi-autonomous sensor network using a model-based approach(2010-05-3); ; ; The present dissertation carries out both energy management and model-based fault detection while using wireless sensor networks (WSNs). It deals with an application of a WSN which uses scattered sensor nodes inside a closed space container to monitor environmental variables, temperature and relative humidity. Since the environmental system under discussion is non-linear, multivariable and time variant, a hybrid mathematical model is extracted. A novel approach to simplify the hybrid model and decouple the monitoring variables is introduced for the first time in this research. This outstanding idea, so-called Floating Input Approach (FIA) exploits system identification as well as the properties of a distributed measurement systems to simplify the modeling task. It performs a Multi Input-Single Output (MISO) linear dynamic model and estimates environmental variables on a desired sensor node as output by using actual measured variables from surrounding sensor nodes as inputs. Developing both on-line and off-line model identifications based on the FIA, model-based fault detection and energy saving of the wireless sensor network without performance degradation is successfully achieved. The FIA-based techniques detect and discriminate different fault types in sensors and system under discussion. Moreover, in the basis of the proposed mathematical dynamic model, an effective technique is introduced to enlarge life time of the sensor nodes. A combinational fault detection and energy management is introduced at the end.Benefits of the addressed techniques are verified using simulations and implementations on a progressive platform of WSN (Imote2). They can also be developed simply for a wide variety of applications in the future.Dissertation557 220 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Development and evaluation of an autonomous wirelesssensor actuator network in logistic systems(2010-04-26); ; ; In this work, definition, development and evaluation of Autonomous Wireless Sensor Actuator Network (AWSAN) is discussed. Firstly the central and distributed systems are described. Then characteristic for autonomous system are considered. Based on the feedback model it is explained how the autonomous concept is applied in sensor actuator network. The necessity of developing the intelligent container to establish autonomous logistic system and reinforcing the system performance is explained.In order to develop an autonomous network a target-oriented routing algorithm is invented. By this routing algorithm the message is routed over the minimum length tree of the network graph and directed by sequential coordinates. This routing algorithm is called SCAR. Moreover to implement the AWSAN in automation process application it was required to find an optimal sample number for the sensor. A method is introduced by which it can be answered how often the sensors should take samples from the environment. A typical sensor node for implementation is also introduced.To evaluate the sensor network, it is simulated by a Probabilistic Wireless Network Simulator (Prowler). The network energy consumption and its distribution over the nodes in network with central and autonomous structure are studied. It is shown that the autonomous network consumes less energy than the central network. In the autonomous network the network energy consumption is distributed over the nodes more even compare to central network. This claim implies that the autonomous network is more sustainable. In another simulation an apple garden humidity is taken as case study to compare the robustness of the autonomous and central networks. The result is shown that the autonomous network is more robust. According to the optimal sample number method, it is also shown that with the autonomous network better control quality is achievable and the network is more scalable. During this work the AWSAN is seen as a micro scale of large autonomous systems and with some resemblances the result are generalized to autonomous system as well. Finally it is discussed that if decision by entities becomes dependent on conditions, the above results will face challenges and shows that the merits of autonomous network are not absolute.Dissertation503 128 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Herstellung und Charakterisierung eines flexiblen kapazitiven Sensors für die Überwachung von kohlenfaservertärkten Polymeren(2017-12-13); ; ; The following thesis deals with the modeling, development and technology of a miniaturized interdigital sensor on flexible substrates to measure the degree of curing during manufacturing of the carbon fiber reinforced plastics. The special feature of the sensor is a very thin flexible substrate. Despite the small thickness, the film of the polyimide has a very good mechanical, thermal and chemical stability. This reduces the foreign body effect and makes it possible to leave the sensor in the compound material for long term use. The FEM simulations are used to calculate the sensor capacitance in the air and the sensitivity of the sensors to different types. In the technological implementation, all microsystem technology processes are realized on SI wafers. At the end of the manufacturing process, the flexible sensor of the second generation can be peeled off back from the silicon substrate. After the sensor characterization with different media the sensors with isolated electrodes are embedded in to CFRP. During the curing process, the implemented interdigital sensors provide the necessary data for online process monitoring. The complete curing of the CFRP plate is confirmed by using differential scanning calorimetry analysis. To demonstrate the secondary use of the flexible interdigital sensor in the context of structural health monitoring is proved the water intake of the CFRP plate with integrated sensor.Dissertation485 335 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Spatial Statistical Data Fusion on Java-enabled Machines in Ubiquitous Sensor Networks(2014-04-16); ; ; Wireless Sensor Networks (WSN) consist of small, cheap devices that have a combination of sensing, computing and communication capabilities. They must be able to communicate and process data efficiently using minimum amount of energy and cover an area of interest with the minimum number of sensors. This thesis proposes the use of techniques that were designed for Geostatistics and applies them to WSN field. Kriging and Cokriging interpolation that can be considered as Information Fusion algorithms were tested to prove the feasibility of the methods to increase coverage. To reduce energy consumption, a compression method that models correlations based on variograms was developed. A second challenge is to establish the communication to the external networks and to react to unexpected events. A demonstrator that uses commercial Java-enabled devices was implemented. It is able to perform remote monitoring, send SMS alarms and deploy remote updates.Dissertation680 184 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, A Flex-Rigid, Multi-Channel ECoG Microelectrode Array: Reliable Electrical Contact&Long-Term Stability in Saline(2017-11-27); ; ; An Electrocorticography Micro-Electrode Array (ECoG MEA) is a promising signal-acquisition solution for weakly-invasive brain-computer interfaces. This PhD Thesis proposes a microfabrication scheme for a high-density ECoG MEA and investigates its long-term performance in saline. The ECoG device contains 124 circular electrodes of 100, 300 and 500 um diameters, situated on concentric hexagons (150 mm2 total recording area). The reference electrode, situated beside them, is to be bent to the array backside to become a skull-facing electrode (2.5 mm2 surface area). Metallization paths connect the electrodes to the assembly pads of 4 x 32 SMD Omnetics connectors. The ECoG device was realized as a polyimide-metal-polyimide stack on a silicon wafer. A DRIE process shaped a silicon interposer out of the carrier wafer, serving as mechanical platform for the assembly of fine-pitch electrical connectors. Electrical characterization was performed by means of electrochemical impedance spectroscopy. The electrode impedance scaled with electrode area. The strength of the solder joints was tested by means of pull tests. Electrical and mechanical tests revealed that removing the bottom polyimide from the solder-joint area enables a more reliable electrical contact. The array was implanted on the primary visual cortex (V1) of a macaque and recorded natural electrophysiological signals: the larger the electrode, the larger the signal. The skull-facing reference electrode provided signals of greater average Power Spectral Density (PSD) than common average referencing. However, the onset of parasitic short-circuits formation was encountered ca. 3-4 months after implantation. Accelerated soak tests were performed on planar-capacitor IDE structures to simulate the formation of parasitic short-circuits. The influence of curing, adhesion and sterilization on the water-barrier properties of polyimide and parylene coatings was monitored. Based on the results, a new ECoG MEA was fabricated and stored under accelerated soak conditions. The proposed ECoG MEA can be beneficial for the design, microfabrication and long-term stability of future flexible microdevices.Dissertation531 500