Vision-based methods for relative sag measurement of suspension bridge cables

Main cables, comprising a number of wire strands, constitute a vital element in long-span suspension bridges. The determination of their alignment during construction is of great importance, and relative sag is commonly measured for the efficient sag adjustment of general strands. The conventional approach uses the caterpillar method, which is inconvenient, difficult-to-implement, and potentially dangerous. In order to realize the high-precision measurement of cable alignment in a strong wind environment, a vision-based method for relative sag measurement of the general cable strands is proposed in this paper. In the proposed measurement system, images of pre-installed optical targets are collected and analyzed to realize the remote, automatic, and real-time measurement of the relative sag. The influences of wind-induced cable shaking and camera shaking on the accuracy of the height difference measurement are also theoretically analyzed. The results show that cable strand torsion and camera roll have a great impact on the measurement accuracy, while the impacts of the cable strand swing and vibration, camera swing and vibration, and camera pitch and yaw are insignificant. The vision-based measurement system tested in the field experiment also shows a measurement error within 3 mm, which meets the requirements for cable adjustment construction. At the same time, the vision-based measurement method proposed and validated in this paper can improve the measurement accuracy and efficiency of strand alignment in a strong wind environment. Potential risks involved in the manual measurement, e.g., working at heights and in strong wind environments, can be eliminated, facilitating the automation of the cable erection process

Probabilistic assessment of high-throughput wireless sensor networks

Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved.ope

Development of a multi-hop wireless sensor system for the dynamic event monitoring of civil infrastructure and its extension for seismic response monitoring

The dynamic response of civil infrastructures under transient dynamic events is of particular interests for structural engineers, because these event-induced responses usually provide useful insights into the real dynamic behavior of civil infrastructures under extreme conditions. Monitoring these dynamic event induced vibrations are among the most frequently conducted measurements and experiments in the structural engineering field, and a cheaper, simpler and more flexible monitoring system is always under pursuit of civil engineers. One particular such request comes from the seismic response monitoring applications. Seismic response monitoring for general civil infrastructure is critical in high-risk earthquake areas like Japan. It contributes to earthquake safety by providing quantitative measurement that enables improved understanding and predictive modeling of the earthquake response of these engineered systems. However, due to the limitations of the current monitoring systems, such seismic response records of general civil infrastructure are usually not available. Therefore, this research describes a novel development of an autonomous dynamic event monitoring system using Wireless Smart Sensor Network(WSSN), which is further extended to support the purpose of long-term seismic response monitoring. This developed WSSN monitoring system is portable and low-cost, it has a potential to provide long-term seismic response monitoring for a wide range of civil infrastructure. This system can run on existing power sources readily available in common civil infrastructure and thus is able to perform long-term continuous sensing as demanded by the seismic response monitoring applications. A quick and stable event detection method is developed to trigger the recording of the complete seismic response and also eliminate possible false alerts caused by unexpected disturbance. Long-term network-wide time synchronization is guaranteed by a customized long-term Flooding Time Synchronization Protocol(FTSP) so that the all sensor nodes in the network can provide consistent time records of their captured seismic response. An efficient multi-hop service module is also incorporated into the system to disseminate commands and accommodate the need of collecting data in a reliable and prompt manner after major earthquakes, the integrated multi-hop data collection protocol provides a theoretically optimum data collection efficiency. Various experiments have been done to validate the developed programs. Suggestions are also given towards the final realization of successful long-term implementation of the developed monitoring system.報告番号: ; 学位授与年月日: 2012-09-27 ; 学位の種別: 修士 ; 学位の種類: 修士（工学） ; 学位記番号: ; 研究科・専攻: 工学系研究科社会基盤学専

Galileo and EGNOS as an asset for UTM safety and security

GAUSS (Galileo-EGNOS as an Asset for UTM Safety and Security) is a H2020 project1 that aims at designing and developing high performance positioning systems for drones within the U-Space framework focusing on UAS (Unmanned Aircraft System) VLL (Very Low Level) operations. The key element within GAUSS is the integration and exploitation of Galileo and EGNOS exceptional features in terms of accuracy, integrity and security, which will be key assets for the safety of current and future drone operations. More concretely, high accuracy, authentication, precise timing (among others) are key GNSS (Global Navigation Satellite System) enablers of future integrated drone operations under UTM (UAS Traffic Management) operations, which in Europe will be deployed under U-Space [1]. The U-Space concept helps control, manage and integrate all UAS in the VLL airspace to ensure the security and efficiency of UAS operations. GAUSS will enable not only safe, timely and efficient operations but also coordination among a higher number of RPAS (Remotely Piloted Aircraft System) in the air with the appropriate levels of security, as it will improve anti-jamming and anti-spoofing capabilities through a multi-frequency and multi-constellation approach and Galileo authentication operations. The GAUSS system will be validated with two field trials in two different UTM real scenarios (in-land and sea) with the operation of a minimum of four UTM coordinated UAS from different types (fixed and rotary wing), manoeuvrability and EASA (European Aviation Safety Agency) operational categories. The outcome of the project will consist of Galileo-EGNOS based technological solutions to enhance safety and security levels in both, current UAS and future UTM operations. Increased levels of efficiency, reliability, safety, and security in UAS operations are key enabling features to foster the EU UAS regulation, market development and full acceptance by the society.Peer ReviewedPostprint (author's final draft

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Multisensory Smartphone Applications in Vibration-Based Structural Health Monitoring

Advances in sensor technology and computer science in the last three decades have boosted the importance of system identification and vibration-based structural health monitoring (SHM) in civil infrastructure safety and integrity assessment. On the other hand, practical and financial issues in system instrumentation, maintenance, and operation have remained as fundamental problems obstructing the widespread use of SHM applications. For this reason, to reduce system costs and improve practicality as well as sustainability, researchers have been working on emerging methods such as wireless, distributed, mobile, remote, smart, multisensory, and heterogeneous sensing systems. Smartphones with built-in batteries, processor units, and a variety of sensors, have stood as a promising hardware and software environment that can be used as SHM components. Communication capabilities with the web, enable them to compose a smart and participatory sensor network of outnumbered individuals. Besides, crowdsourcing power offered by citizens, sets a decentralized and self-governing SHM framework which can even be pertained by very limited equipment and labor resources. Yet, citizen engagement in an SHM framework brings numerous challenges as well as opportunities. In a citizen-induced SHM scenario, the system administrators have limited or no control over the sensor instrumentation and the operation schedule, and the acquired data is subjected change depending on the measurement conditions. The citizen-induced errors can stem from spatial, temporal, and directional uncertainties since the sensor configuration relies on smartphone users’ decisions and actions. Moreover, the sensor-structure coupling may be unavailable where the smartphone is carried by the user, and as a consequence, the vibration features measured by smartphones can be modified due to the human biomechanical system. In addition, in contrast with the conventional high fidelity sensors, smartphone sensors are of limited quality and are subjected to high noise levels. This dissertation utilizes multisensory smartphone features to solve citizen-induced uncertainties and develops a smartphone-based SHM methodology which enables a cyber-physical system through mobile crowdsourcing. Using smartphone computational and communicational power, combined with a variety of embedded sensors such as accelerometer, gyroscope, magnetometer and camera, spatiotemporal and biomechanical citizen-induced uncertainties can be eliminated from the crowdsourced smartphone data, and eventually, structural vibrations collected from numerous buildings and bridges can be collected on a single cloud server. Therefore, unlike the conventional platforms designed and implemented for a particular structure, citizen-engaged and smartphone-based SHM can serve as intelligent, scalable, fully autonomous, cost-free, and durable cyber-physical systems drastically changing the forthcoming trends in civil infrastructure monitoring. In this dissertation, iOS is used as the application development platform to produce a smartphone-based SHM prototype, namely Citizen Sensors for SHM. In addition, a web-based software is developed and cloud services are implemented to connect individual smartphones to an administrator base and automate data submission and processing procedure accordingly. Finally, solutions to citizen-induced problems are provided through numerous laboratory and field test applications to prove the feasibility of smartphone-based SHM with real life examples. Through collaborative use of the software, principles and methodologies presented in this dissertation, smartphones can be the core component of futuristic smart, resilient, and sustainable city and infrastructure systems. And this study lays down an innovative and integrated foundation empowering citizens to achieve these goals

Development of low-cost sensors for structural health monitoring applications

(English) There is increasing interest in developing low-cost sensors for economical structural health monitoring of civil engineering infrastructures. In addition to their price, they have the additional benefit of being easily connected to low-cost microcontrollers such as Arduino. A reliable data acquisition system based on Arduino technology can further lower the cost of data collection and monitoring, enabling long-term monitoring at an affordable cost. This thesis proposes the following four high-precision low-cost monitoring systems.Firstly, to correctly measure structural responses, a Cost Hyper-Efficient Arduino Product (CHEAP) has been developed. CHEAP is a system made up of five synchronized accelerometers connected to an Arduino microcontroller that works as a data collecting device. CHEAP is a uniaxial MEMS accelerometer with a sampling frequency of 85 Hz. To validate its performance, laboratory experiments were carried out and the results were compared with those of two high-precision accelerometers (PCB393A03 and PCB 356B18).Secondly, a unique low-cost inclinometer is presented, the Low-cost Adaptable Reliable Angle-meter (LARA), which measures inclination through the fusion of different sensors: five gyroscopes and five accelerometers. LARA combines a microcontroller based on Internet of Things technology (NODEMCU), allows wireless data transmission, and free commercial software for data collection (SerialPlot). To confirm the precision and resolution of this device, its measurements under laboratory conditions were compared with the theoretical ones and with those of a commercial inclinometer (HI-INC). Laboratory results of a load test on a beam demonstrate LARA's remarkable accuracy. It is concluded that the accuracy of LARA is sufficient for its application in detecting bridge damage.Thirdly, the effect of combining similar range sensors to investigate the increase of the accuracy and mitigation of the ambiental noises, is also elucidated. To investigate the sensor combination theory, a measuring equipment composed of 75 contactless ranging sensors controlled by only two microcontrollers (Arduinos), was built. The 75 sensors are 25 HC-SR04 (analog), 25 VL53L0X (digital), and 25 VL53L1X. (digital). In addition, the impact of various environmental conditions on the standard deviation, distribution functions, and error level of these sensors (HC-SR04, VL53L0X, and VL53L1X) is determined.Finally, a novel remote versatile data acquisition system is presented that allows the recording of time with microsecond resolution for the subsequent synchronization of the acquired data of the wireless sensors located at various points of a structure. This functionality is what would allow its application to static or quasi-static load tests or to the modal analysis of structures. The system developed has a noise density of 51 g/Hz and a sampling frequency of 333 Hz. This device was used to identify the eigenfrequencies and modal analysis of several structures (polvorín footbridges in Barcelona and Andoain Bridge, Donostia-San Sebastian). The comparison of the modal analysis of the Andoain Bridge using the acquired data of the developed accelerometer and data acquisition equipment with those of commercial accelerometers (PCB 607A61) were satisfactory.The low-cost accelerometer, inclinometer and data acquisition system developed and validated in this thesis can make SHM and infrastructure damage detection a reality at low cost, long term and remotely.(Español) Cada vez hay más interés en desarrollar sensores baratos para conocer de manera económica el estado de las infraestructuras civiles. Además de su precio, estos sensores tienen la ventaja añadida de poder conectarse fácilmente a microcontroladores de bajo coste como Arduino. Un sistema fiable de adquisición de datos basado en la tecnología Arduino puede disminuir aún más el coste de la recogida de datos y la monitorización, lo que permitiría una monitorización a largo plazo a un coste asequible. Esta tesis propone los cuatro siguientes sistemas de monitorización de alta precisión y bajo coste.En primer lugar, para medir correctamente las respuestas estructurales, se ha desarrollado el Cost Hyper-Efficient Arduino Product (CHEAP). CHEAP es un sistema compuesto por cinco acelerómetros sincronizados de bajo coste conectados a un microcontrolador Arduino que hace el papel de dispositivo de recogida de datos. CHEAP es un acelerómetro MEMS uniaxial con una frecuencia de muestreo de 85 Hz. Para validar su rendimiento, se efectuaron unos experimentos de laboratorio y sus resultados se compararon con los de dos acelerómetros de alta precisión (PCB393A03 y PCB 356B18). En segundo lugar, se presenta un inclinómetro de bajo coste, un Low-cost Adaptable Reliable Angle-meter (LARA), que mide la inclinación mediante la fusión de distintos sensores: cinco giroscopios y cinco acelerómetros. LARA combina un microcontrolador basado en la tecnología del Internet de las Cosas (NODEMCU), que permite la transmisión inalámbrica de datos, y un software comercial gratuito para la recogida de datos (SerialPlot). Para confirmar la precisión y resolución de este dispositivo, se compararon sus mediciones en condiciones de laboratorio con las teóricas y con las de un inclinómetro comercial (HI-INC). Los resultados de laboratorio de una prueba de carga en una viga demuestran la notable precisión de LARA. Se concluye que la precisión de LARA es suficiente para su aplicación en la detección de daños en puentes.En tercer lugar, también se dilucida el efecto de la combinación de sensores de rango similar para investigar el aumento de la precisión y la mitigación de los ruidos ambientales. Para investigar la teoría de la combinación de sensores, se construyó un equipo de medición compuesto por 75 sensores para la medición de distancias acoplados a dos microcontroladores de Arduino. Los 75 sensores son 25 HC-SR04 (analógicos), 25 VL53L0X (digitales) y 25 VL53L1X (digitales). Además, se determina el impacto de diversas condiciones ambientales en la desviación estándar, las funciones de distribución y el nivel de error de estos sensores.Por último, se presenta un novedoso y versátil sistema de adquisición de datos a distancia que permite el registro del tiempo con una resolución de microsegundos para la sincronización posterior de las lecturas de los sensores inalámbricos situados en diversos puntos de una estructura. Esta funcionalidad es lo que permitiría su aplicación a pruebas de carga estáticas o quasi-estaticas o al análisis modal de las estructuras. El sistema desarrollado tiene una densidad de ruido de 51 g/Hz y una frecuencia de muestreo de 333 Hz. Este dispositivo se utilizó para identificar las frecuencias propias y los modos de vibración de varias estructuras (pasarelas polvorín en Barcelona y Puente de Andoain, Donostia-San Sebastian). Los modos calculados en una de ellas, el Puente de Andoain, a partir de los datos obtenidos con el acelerómetro y sistema de adquisición de datos desarrollado se comparan satisfactoriamente con los de sensores comerciales (PCB 607A61). El acelerómetro, el inclinómetro y el sistema de adquisición de datos de bajo coste desarrollados y validados en esta tesis pueden hacer realidad la SHM y la detección de daños en infraestructuras a bajo coste, a largo plazo y de forma remota.Postprint (published version

Innovative Solutions for Navigation and Mission Management of Unmanned Aircraft Systems

The last decades have witnessed a significant increase in Unmanned Aircraft Systems (UAS) of all shapes and sizes. UAS are finding many new applications in supporting several human activities, offering solutions to many dirty, dull, and dangerous missions, carried out by military and civilian users. However, limited access to the airspace is the principal barrier to the realization of the full potential that can be derived from UAS capabilities. The aim of this thesis is to support the safe integration of UAS operations, taking into account both the user's requirements and flight regulations. The main technical and operational issues, considered among the principal inhibitors to the integration and wide-spread acceptance of UAS, are identified and two solutions for safe UAS operations are proposed: A. Improving navigation performance of UAS by exploiting low-cost sensors. To enhance the performance of the low-cost and light-weight integrated navigation system based on Global Navigation Satellite System (GNSS) and Micro Electro-Mechanical Systems (MEMS) inertial sensors, an efficient calibration method for MEMS inertial sensors is required. Two solutions are proposed: 1) The innovative Thermal Compensated Zero Velocity Update (TCZUPT) filter, which embeds the compensation of thermal effect on bias in the filter itself and uses Back-Propagation Neural Networks to build the calibration function. Experimental results show that the TCZUPT filter is faster than the traditional ZUPT filter in mapping significant bias variations and presents better performance in the overall testing period. Moreover, no calibration pre-processing stage is required to keep measurement drift under control, improving the accuracy, reliability, and maintainability of the processing software; 2) A redundant configuration of consumer grade inertial sensors to obtain a self-calibration of typical inertial sensors biases. The result is a significant reduction of uncertainty in attitude determination. In conclusion, both methods improve dead-reckoning performance for handling intermittent GNSS coverage. B. Proposing novel solutions for mission management to support the Unmanned Traffic Management (UTM) system in monitoring and coordinating the operations of a large number of UAS. Two solutions are proposed: 1) A trajectory prediction tool for small UAS, based on Learning Vector Quantization (LVQ) Neural Networks. By exploiting flight data collected when the UAS executes a pre-assigned flight path, the tool is able to predict the time taken to fly generic trajectory elements. Moreover, being self-adaptive in constructing a mathematical model, LVQ Neural Networks allow creating different models for the different UAS types in several environmental conditions; 2) A software tool aimed at supporting standardized procedures for decision-making process to identify UAS/payload configurations suitable for any type of mission that can be authorized standing flight regulations. The proposed methods improve the management and safe operation of large-scale UAS missions, speeding up the flight authorization process by the UTM system and supporting the increasing level of autonomy in UAS operations

Advanced Sensors for Real-Time Monitoring Applications

It is impossible to imagine the modern world without sensors, or without real-time information about almost everything—from local temperature to material composition and health parameters. We sense, measure, and process data and act accordingly all the time. In fact, real-time monitoring and information is key to a successful business, an assistant in life-saving decisions that healthcare professionals make, and a tool in research that could revolutionize the future. To ensure that sensors address the rapidly developing needs of various areas of our lives and activities, scientists, researchers, manufacturers, and end-users have established an efficient dialogue so that the newest technological achievements in all aspects of real-time sensing can be implemented for the benefit of the wider community. This book documents some of the results of such a dialogue and reports on advances in sensors and sensor systems for existing and emerging real-time monitoring applications