As the rapid progress in technology changes our daily life, it also changes how the Industry works. The new developments enable technologies such as the Internet of Moving Things (IoMT), and through these technologies, new challenges arise. IoMT adds one more vital issue, localization, to be solved in comparison to the Internet of Things (IoT). To enable IoMT in the manufacturing industry, there are still problems that need to be overcome. Critical statements such as power consumption, price, accuracy, data management, and size. In this thesis, an evaluation of a new sensor system for an air pneumatic grinder is conducted. The features of the sensor system are to report data from the grinder to the cloud and to localize the position of the grinder. The focus was to optimize the localization algorithm and power consumption of the system. The localization of the grinder was conducted with a new and improved algorithm, Ring Error Difference System (REDS), introduced in this thesis. The new algorithm increased the previous known iRingLA accuracy from 2.91 m to 2.33 m for Bluetooth Low Energy (BLE) and from 3.99 m to 2.84 for Wi-Fi, according to the experiments performed. The final system was able to estimate the operation runtime with an error of 24 s for an operational runtime of 905 s. The operational lifetime of the system was 242 h and 45 h, respectively, for BLE and Wi-Fi. An optimized software was introduced to decrease power consumption. The optimized version was estimated to have an operational lifetime of 1540 h for BLE, which did not reach the wanted lifetime of 3000 h set by Atlas Copco. Hence, I conclude that the hardware, Wemos ESP32, used in the thesis, is not feasible for this solution. Simpler hardware, than the Wemos ESP32, should be used to be able to reach the goal of 3000 h. / De stora framstegen inom dagens teknik förvandlar inte bara vårt dagliga liv det förändrar också tekniken inom industrin. Den nya tekniken möjliggör framsteg så som Internet of Moving Things (IOMT), vilket leder till nya utmaningar. IoMT jämfört med Internet of Things (IoT) lägger till ytterligare utmaningar att lösa så som lokalisering. För att kunna använda IoMT inom tillverkningsindustrin måste ett flertal problem hanteras så som strömförbrukning, pris och noggrannhet på lokaliseringen, datahantering och storlek på systemet. I denna masteruppsatts gör jag en utvärdering av ett nytt sensorsystem för luftdrivna slipmaskiner. Detta sensorsystem rapporterar data från slipmaskinen till molnet och rapporterar positionen av utrustningen. Fokuset på uppsatsen var att optimera lokaliseringsalgoritmen och minska strömförbrukningen för systemet. Lokaliseringen av slipmaskinen gjordes med en ny och förbättrad algoritm, Ring Error Difference System (REDS), som jag introducerar i avhandlingen. Algoritmen förbättrade den tidigare kända RSSI-baserade iRingLA från 2,91 m till 2,33 m med Bluetooth Low Energy (BLE) och från 3,99 m till 2,84 m för Wi-Fi. Det slutliga systemet kunde uppskatta drifttiden med en avvikelse på 24 s av den verkliga drifttiden, 905 s. Systemets operativa livslängd var 242 timmar och 45 timmar för BLE respektive Wi-Fi. Dessutom infördes en optimerad programvara för att minska strömförbrukningen. Den optimerade versionen beräknades ha en livslängd på 1540 timmar för BLE, vilket inte når den önskade livslängden på 3000 timmar satt av Atlas Copco. Ifrån mitt arbete drar jag slutsatsen att hårdvaran som används i uppsatsen, inte kan användas i en slutlig produkt. En enklare hårdvara än Wemos ESP32 bör användas för att kunna nå målet på 3000 timmar.

No description available.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第25444号 / 情博第882号 / 新制||情||148(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 佐藤 高史, 教授 橋本 昌宜, 教授 新津 葵一 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Konsequent betriebener Leichtbau führte und führt weiterhin zu steigender Komplexität in der Blechumformung. Erkenntnisse aus Forschungsaktivitäten zur gezielten Beeinflussung, Regelung und Vollautomatisierung des Tiefziehprozesses konnten jedoch bisher nicht in Großserienpresswerke transferiert werden. Aus diesem Grund wird in dieser Arbeit ein Werkzeugkonzept vorgestellt, welches unter Berücksichtigung der relevanten Randbedingungen eine gezielte lokale Beeinflussung des Umformprozesses ermöglicht. Gleichzeitig gestattet es, mit Hilfe eines neuartigen, optischen Sensorkonzeptes die Geschwindigkeit sowie den Einlaufweg der Platine zu überwachen. Es wird eine methodische Vorgehensweise zur Herstellung von Umformwerkzeugen, auf der neuen Konzeption basierend, beschrieben. Umformsimulationen dienen dabei zur Identifikation von kritischen Bauteilen und deren neuralgischen Zonen. Eine entsprechend angepasste Konstruktion bietet Bauraum für die Implementierung von zusätzlichen Aktuatoren und einem definiert elastischen Einsatz. Abschließende FEM-Analysen mit Volumenmodellen sowie die Kalkulation der Lebensdauer bestätigen eine ausreichende Flexibilität und die erforderliche Dauerfestigkeit. Im Rahmen der experimentellen Analyse konnte eine drastische Verkürzung der Anlaufzeit durch deutlich reduzierten Tuschieraufwand aufgrund der Anpassungsfähigkeit sowie Flexibilität des definiert elastischen Werkzeugkonzeptes nachgewiesen werden. Neben diesem Potential hinsichtlich strukturierter Inbetriebnahmen ermöglicht die Konzeption eine Kompensation von Pressenunterschieden und individuellen Maschinencharakteristika (wie bspw. Stößelverkippungen) wodurch der Transfer von der Einarbeitspresse auf die Produktionsanlage wesentlich weniger Korrekturschleifen hervorruft. Außerdem werden der Qualitätsaufwand (Nachtuschieren) während der laufenden Serienproduktion, Stillstandszeiten und Ausschussquoten stark verringert. Darüber hinaus ergeben sich erweiterte Anwendungsmöglichkeiten bei der Umformung von tailored blanks und aus der Minimierung/Optimierung des Platinenzuschnittes enorme Einsparungs- und Kostenpotentiale. Abschließend werden die Vorteile eines geschlossenen Prozessregelkreises durch die Verknüpfung von Sensorik und Aktorik analysiert. Dabei bestätigt das vorgeschlagene Regelkonzept einer Prozessnachführung die Erhöhung der Prozessstabilität bei schwankenden Prozessparametern durch die gezielte, lokale Verteilung der Flächenpressung. Zuletzt diskutiert der vorliegende Beitrag Transfermöglichkeiten der Verbesserungspotentiale in kommende Serienwerkzeuge vor dem Hintergrund von Kostenrestriktionen und Minimierung des bedientechnischen sowie konstruktiven Aufwandes.

With the advancement of technology and the development of more sophisticated remote sensing sensor systems, the use of satellite imagery has opened up various fields of exploration and application. There has been an increased interest in analysis of multi-temporal satellite image in the past few years because of the wide variety of possible applications of in both short-term and long-term image analysis. The type of changes that might be of interest can range from short-term phenomena such as flood assessment and crop growth stage, to long-term phenomena such as urban fringe development. This thesis studies flood assessment and land cover mapping of satellite images, and proposes nature inspired algorithms that can be easily implemented in realistic scenarios. Disaster monitoring using space technology is one of the key areas of research with vast potential; particularly flood based disasters are more challenging. Every year floods occur in many regions of the world and cause great losses. In order to monitor and assess such situations, decision-makers need accurate near real-time knowledge of the field situation. How to provide actual information to decision-makers for effective flood monitoring and mitigation is an important task, from the point of view of public welfare. Over-estimation of the flooded area leads to over-compensation to people, while under-estimation results in production loss and negative impacts on the population. Hence it is essential to assess the flood damage accurately, both in qualitative and quantitative terms. In such situations, land cover maps play a very critical role. Updating land cover maps is a time consuming and costlier operation when it is performed using traditional or manual methods. Hence, there is a need to find solutions for such problem through automation. Design of automatic systems dedicated to satellite image processing which involves change detection to discriminate areas of land cover change between imaging dates. The system integrates the spectral and spatial information with the techniques of image registration and pattern classification using nature inspired techniques. In the literature, various works have been carried out for solving the problem of image registration and pattern classification using conventional methods. Many researchers have proved, for different situations, that nature inspired techniques are promising in comparison with that of conventional methods. The main advantage of nature inspired technique over any other conventional methods is its stochastic nature, which converges to optimal solution for any dynamic variation in a given satellite image. Results are given in such terms as to delineate change in multi-date imagery using change-versus-no-change information to guide multi-date data analysis. The main objective of this study is to analyze spatio-temporal satellite data to bring out significant changes in the land cover map through automated image processing methods. In this study, for satellite image analysis of flood assessment and land cover mapping, the study areas and images considered are: Multi-temporal MODerate-resolution Imaging Spectroradiometer (MODIS) image around Krishna river basin in Andhra Pradesh India; Linear Imaging Self Scanning Sensor III (LISS III)and Synthetic Aperture Radar(SAR)image around Kosi river basin in Bihar, India; Landsat7thematicmapperimage from the southern part of India; Quick-Bird image of the central Bangalore, India; Hyperion image around Meerut city, Uttar Pradesh, India; and Indian pines hyperspectral image. In order to develop a flood assessment framework for this study, a database was created from remotely sensed images (optical and/or Synthetic Aperture Radar data), covering a period of time. The nature inspired techniques are used to find solutions to problems of image registration and pattern classification of a multi-sensor and multi-temporal satellite image. Results obtained are used to localize and estimate accurately the flood extent and also to identify the type of the inundated area based on land cover mapping. The nature inspired techniques used for satellite image processing are Artificial Neural Network (ANN), Genetic Algorithm (GA),Particle Swarm Optimization (PSO), Firefly Algorithm(FA),Glowworm Swarm Optimization(GSO)and Artificial Immune System (AIS). From the obtained results, we evaluate the performance of the methods used for image registration and pattern classification to compare the accuracy of satellite image processing using nature inspired techniques. In summary, the main contributions of this thesis include (a) analysis of flood assessment and land cover mapping using satellite images and (b) efficient image registration and pattern classification using nature inspired algorithms, which are more popular than conventional optimization methods because of their simplicity, parallelism and convergence of the population towards the optimal solution in a given search space.

<p>Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. </p><p><br></p><p>Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO₂ and Chip 2: WO₃). These sensors were tested at different relative humidity (RH) levels, and VOC concentrations. Contact angle which measures hydrophobicity, was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.</p>

The master theses deals with a detailed analysis of optical fiber sensors. Specifically, there are discussed optical fibers, various types of sensors and realization optical fiber senzor and senzor system that has been optimized and processed data in real time. In master theses also describes the LabView programming enviroment and uses components, including the entire sensor systém of a sensors system that sends measured data

Indiana University-Purdue University Indianapolis (IUPUI) / A novel method of power management and sequential monitoring of several sensors is proposed in this work. Application specific integrated circuits (ASICs) consisting of analog and digital sub-systems forming a system on chip (SoC) has been designed using complementary metal-oxide-semiconductor (CMOS) technology. The analog sub-system comprises the sensor-drivers that convert the input voltage variations to output pulse-frequency. The digital sub-system includes the system management unit (SMU), counter, and shift register modules. This performs the power-usagemanagement, sensor-sequence-control, and output-data-frame-generation functions. The SMU is the key unit within the digital sub-system is that enables or disables a sensor. It captures the pulse waves from a sensor for 3 clocks out of a 16-clock cycle, and transmits the signal to the counter modules. As a result, the analog sub-system is at on-state for only 3/16th fraction (18 %) of the time, leading to reduced power consumption. Three cycles is an optimal number selected for the presented design as the system is unstable with less than 3 cycles and higher clock cycles results in increased power consumption. However, the system can achieve both higher sensitivity and better stability with increased on-state clock cycles. A current-starved-ring-oscillator generates pulse waves that depend on the sensor input parameter. By counting the number of pulses of a sensor-driver in one clock cycle, a sensor input parameter is converted to digital. The digital sub-system constructs a 16-bit frame consisting of 8-bit sensor data, start and stop bits, and a parity bit. Ring oscillators that drive capacitance and resistance-based sensors use an arrangement of delay elements with two levels of control voltages. A bias unit which provides these two levels of control voltages consists of CMOS cascade current mirror to maximize voltage swing for control voltage level swings which give the oscillator wider tuning range and lower temperature induced variations. The ring oscillator was simulated separately for 250 nm and 180 nm CMOS technologies. The simulation results show that when the input voltage of the oscillator is changed by 1 V, the output frequency changes linearly by 440 MHz for 180 nm technology and 206 MHz for 250 nm technology. In a separate design, a temperature sensitive ring oscillator with symmetrical load and temperature dependent input voltage was implemented. When the temperature in the simulation model was varied from -50C to 100C the oscillator output frequency reduced by 510 MHz for the 250 nm and by 810 MHz for 180 nm CMOS technologies, respectively. The presented system does not include memory unit, thus, the captured sensor data has to be instantaneously transmitted to a remote station, e.g. end user interface. This may result in a loss of sensor data in an event of loss of communication link with the remote station. In addition, the presented design does not include transmitter and receiver modules, and thus necessitates the use of separate modules for the transfer of the data.

Konsequent betriebener Leichtbau führte und führt weiterhin zu steigender Komplexität in der Blechumformung. Erkenntnisse aus Forschungsaktivitäten zur gezielten Beeinflussung, Regelung und Vollautomatisierung des Tiefziehprozesses konnten jedoch bisher nicht in Großserienpresswerke transferiert werden. Aus diesem Grund wird in dieser Arbeit ein Werkzeugkonzept vorgestellt, welches unter Berücksichtigung der relevanten Randbedingungen eine gezielte lokale Beeinflussung des Umformprozesses ermöglicht. Gleichzeitig gestattet es, mit Hilfe eines neuartigen, optischen Sensorkonzeptes die Geschwindigkeit sowie den Einlaufweg der Platine zu überwachen. Es wird eine methodische Vorgehensweise zur Herstellung von Umformwerkzeugen, auf der neuen Konzeption basierend, beschrieben. Umformsimulationen dienen dabei zur Identifikation von kritischen Bauteilen und deren neuralgischen Zonen. Eine entsprechend angepasste Konstruktion bietet Bauraum für die Implementierung von zusätzlichen Aktuatoren und einem definiert elastischen Einsatz. Abschließende FEM-Analysen mit Volumenmodellen sowie die Kalkulation der Lebensdauer bestätigen eine ausreichende Flexibilität und die erforderliche Dauerfestigkeit. Im Rahmen der experimentellen Analyse konnte eine drastische Verkürzung der Anlaufzeit durch deutlich reduzierten Tuschieraufwand aufgrund der Anpassungsfähigkeit sowie Flexibilität des definiert elastischen Werkzeugkonzeptes nachgewiesen werden. Neben diesem Potential hinsichtlich strukturierter Inbetriebnahmen ermöglicht die Konzeption eine Kompensation von Pressenunterschieden und individuellen Maschinencharakteristika (wie bspw. Stößelverkippungen) wodurch der Transfer von der Einarbeitspresse auf die Produktionsanlage wesentlich weniger Korrekturschleifen hervorruft. Außerdem werden der Qualitätsaufwand (Nachtuschieren) während der laufenden Serienproduktion, Stillstandszeiten und Ausschussquoten stark verringert. Darüber hinaus ergeben sich erweiterte Anwendungsmöglichkeiten bei der Umformung von tailored blanks und aus der Minimierung/Optimierung des Platinenzuschnittes enorme Einsparungs- und Kostenpotentiale. Abschließend werden die Vorteile eines geschlossenen Prozessregelkreises durch die Verknüpfung von Sensorik und Aktorik analysiert. Dabei bestätigt das vorgeschlagene Regelkonzept einer Prozessnachführung die Erhöhung der Prozessstabilität bei schwankenden Prozessparametern durch die gezielte, lokale Verteilung der Flächenpressung. Zuletzt diskutiert der vorliegende Beitrag Transfermöglichkeiten der Verbesserungspotentiale in kommende Serienwerkzeuge vor dem Hintergrund von Kostenrestriktionen und Minimierung des bedientechnischen sowie konstruktiven Aufwandes.

This study addresses the challenges faced by industries requiring precise water quality monitoring by developing and evaluating a modular multi-sensor system. Existing solutions often lack scalability and flexibility, necessitating multiple devices for comprehensive analysis. The methodology employed a recursive prototype development approach, integrating various hardware and software components, including microcontrollers and a user-friendly mobile application. The prototype facilitated real-time data acquisition and management through a dedicated server, supporting essential water quality parameters such as pH, temperature, and conductivity. Results indicate that the system significantly enhances measurement accuracy and operational efficiency. However, the implementation of a smart home connectivity standard was unsuccessful, highlighting the complexities associated with integrating new communication protocols. Despite this, the system offers a scalable, cost-effective solution for continuous water quality monitoring, presenting significant improvements over existing technologies in terms of flexibility, user engagement, and data reliability. / Denna studie behandlar de utmaningar som industrier står inför som kräver noggrann övervakning av vattenkvalitet genom att utveckla och utvärdera ett modulärt multisensorsystem. Befintliga lösningar saknar ofta skalbarhet och flexibilitet, vilket kräver flera enheter för omfattande analys. Metodiken använde en rekursiv prototyputvecklingsansats, som integrerade olika hårdvaru- och mjukvarukomponenter, inklusive mikrokontroller och en användarvänlig mobilapplikation. Prototypen underlättade insamling och hantering av realtidsdata genom en dedikerad server, som stödde viktiga vattenkvalitetsparametrar såsom pH, temperatur och konduktivitet. Resultaten indikerar att systemet avsevärt förbättrar mätnoggrannhet och operationell effektivitet. Dock var implementeringen av smarta hem-anslutningsstandard inte framgångsrik, vilket belyser komplexiteten med att integrera nya kommunikationsprotokoll. Trots detta erbjuder systemet en skalbar, kostnadseffektiv lösning för kontinuerlig övervakning av vattenkvalitet, med betydande förbättringar jämfört med befintliga teknologier när det gäller flexibilitet, användarengagemang och datareliabilitet.