• Smart Structures and Systems
• /
• v.4 no.3
• /
• pp.305-318
• /
• 2008

The development of a digital signal processor based prototype is described in relation to continuing efforts for realizing a fully self-contained active sensor system utilizing impedance-based structural health monitoring. The impedance method utilizes a piezoelectric material bonded to the structure under observation to act as both an actuator and sensor. By monitoring the electrical impedance of the piezoelectric material, insights into the health of the structured can be inferred. The active sensing system detailed in this paper interrogates a structure utilizing a self-sensing actuator and a low cost impedance method. Here, all the data processing, storage, and analysis is performed at the sensor location. A wireless transmitter is used to communicate the current status of the structure. With this new low cost, field deployable impedance analyzer, reliance on traditional expensive, bulky, and power consuming impedance analyzers is no longer necessary. A complete power analysis of the prototype is performed to determine the validity of power harvesting being utilized for self-containment of the hardware. Experimental validation of the prototype on a representative structure is also performed and compared to traditional methods of damage detection.

• Smart Structures and Systems
• /
• v.20 no.2
• /
• pp.163-173
• /
• 2017

Structural health monitoring (SHM) of civil infrastructure using fiber Bragg grating sensor networks (FBGSNs) has received significant public attention in recent years. However, there is currently little research on the health-monitoring technology of high-piled wharfs in coastal ports using the fiber Bragg grating (FBG) sensor technique. The benefits of FBG sensors are their small size, light weight, lack of conductivity, resistance corrosion, multiplexing ability and immunity to electromagnetic interference. Based on the properties of high-piled wharfs in coastal ports and servicing seawater environment and the benefits of FBG sensors, the SHM system for a high-piled wharf in the Tianjin Port of China is devised and deployed partly using the FBG sensor technique. In addition, the health-monitoring parameters are proposed. The system can monitor the structural mechanical properties and durability, which provides a state-of-the-art mean to monitor the health conditions of the wharf and display the monitored data with the BIM technique. In total, 289 FBG stain sensors, 87 FBG temperature sensors, 20 FBG obliquity sensors, 16 FBG pressure sensors, 8 FBG acceleration sensors and 4 anode ladders are installed in the components of the back platform and front platform. After the installation of some components in the wharf construction site, the good signal that each sensor measures demonstrates the suitability of the sensor setup methods, and it is proper for the full-scale, continuous, autonomous SHM deployment for the high-piled wharf in the costal port. The South 27# Wharf SHM system constitutes the largest deployment of FBG sensors for wharf structures in costal ports to date. This deployment demonstrates the strong potential of FBGSNs to monitor the health of large-scale coastal wharf structures. This study can provide a reference to the long-term health-monitoring system deployment for high-piled wharf structures in coastal ports.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.8
• /
• pp.327-342
• /
• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.

• International Journal of Aeronautical and Space Sciences
• /
• v.11 no.4
• /
• pp.338-344
• /
• 2010

This paper discusses the development of the control system of a mini quadrotor in Konkuk University for indoor applications. The attitude control system consists of a stability augmentation system, which acts as the inner loop control, and a modern control approach based on modeling will be implemented as the outer loop. The inner loop control was experimentally satisfied by a proportional-derivative controller; this was used to support the flight test in order to validate the modeling. This paper introduces the mathematical model for the simulation and design of the optimal control on the outer loop control. To perform the experimental tests, basic electronic hardware was developed using simple configurations; a microcontroller used as the embedded controller, a low-cost 100 Hz inertial sensors used for the inertial sensing, infra-red sensors were employed for horizontal ranging, an ultrasonic sensor was used for ground ranging and a high performance propeller system built on an quadrotor airframe was also employed. The results acquired from this compilation of hardware produced an automatic hovering ability of the system with ground control system support for the monitoring and fail-safe system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.5
• /
• pp.425-433
• /
• 2002

After the removal of SA (Selective Availability), horizontal accuracy of 25m(2dRMS) is easily obtained using GPS (Global Positioning System). In this paper, the error characteristics without SA are analyzed and a navigation algorithm concerns this error characteristics is proposed to further improve the accuracy. The proposed method utilizes the relationship between elevation angle and errors that are remained after ionospheric and troposheric delay compensation. The relationship is derived from real measurements and used as a weighting matrix of weighted least squares estimator. Furthermore, a RAIM (Receiver Autonomous Integrity Monitoring) technique is included to remove abnormal measurements affected by multi-path or low SNR (Signal-to-Noise Ratio). It is shown that using the proposed method, more than 4 times accurate result, which is comparable with DGPS (Differential GPS), can be obtained from experiments with real data. Besides accuracy and reliability, the proposed method reduces large jumps in position and maintains better performance than a method using mask angle to completely remove satellites below this mask angle. Thus it is expected that the proposed method can be efficiently applied to land navigation where some satellites are blocked by building or forest.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.279-286
• /
• 2015

The rapid increase of the current marine accidents is mainly due to the human execution errors. In an effort to address this, various kinds of researches such as construction of the digital vessels and vessel information monitoring systems have been conducted. But for safe navigation of vessels, it lack on systems study which can efficiently store, utilize and manage the mass data accepted by the vessel. In this paper, we propose a VWS(Virtual World System) that is based on the architecture of intelligent systems RVC(Reactive Layer-Virtual World-Considerative Layer) model of intelligent autonomous navigation system. VWS is responsible to store all the necessary information for safe navigation of the vessel and the information services to the sub-system of intelligent autonomous navigation system. VWS uses topology database to express the specific problem area, and utilizes a scheduling to reflect the characteristics of the real-time processing environment. Also, Virtual World defines API for the system to reflect the characteristics of the distributed processing environment. As a case study, the VWS is applied to a intelligent ship autonomous navigation system, and simulation is done to prove the effectiveness of the proposed system.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.675-687
• /
• 2010

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.317-320
• /
• 2009

At the present day, the use of containers crisscrossing seven seas and intercontinental transport has significantly increased and bringing the change on the shape of the world economy which we cannot be neglected. Additionally, with the recent technological advances in wireless sensor network (WSN) technologies, has providing an economically feasible monitoring solution to diverse application that allow us to envision the intelligent containers represent the next evolutionary development step in order to increase the efficiency, productivity, utilities, security and safe of containerized cargo shipping. This paper we present a comprehensive containerized cargo monitoring system which has adaptively embedded WSN technology into cargo logistic technology. We share the basic requirement for an autonomous logistic network that could provide optimum performance and a suite of algorithms for self-organization and bi-directional communication of a scalable large number of sensor node apply on container regardless inland and maritime transportation.

• The Journal of Korean Institute of Information Technology
• /
• v.16 no.12
• /
• pp.101-107
• /
• 2018

In wireless sensor network technology, which has been applied to various fields, the power supply and the power management of sensors are the most important issues. For this reason, a new concept of power supply and power management device is required. In this paper, we developed an autonomous independent power supply system that supplies the stable power to a sensor node without an additional external input by applying the energy harvesting technology using the electromagnetic induction principle by utilizing the current flowing in the transmission line. The proposed autonomous independent power supply system consists of a power supply using Power CT and a power management system including a charging circuit. The power management device uses a voltage limiter circuit and a monitoring circuit of charging voltage and current to ensure the safety of charging of the battery. In order to verify the performance of the proposed system, we applied it to the SVL diagnostic system and confirmed that it operates stably.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.439-459
• /
• 2010

Structural health monitoring (SHM) of civil infrastructure using wireless smart sensor networks (WSSNs) has received significant public attention in recent years. The benefits of WSSNs are that they are low-cost, easy to install, and provide effective data management via on-board computation. This paper reports on the deployment and evaluation of a state-of-the-art WSSN on the new Jindo Bridge, a cable-stayed bridge in South Korea with a 344-m main span and two 70-m side spans. The central components of the WSSN deployment are the Imote2 smart sensor platforms, a custom-designed multimetric sensor boards, base stations, and software provided by the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. In total, 70 sensor nodes and two base stations have been deployed to monitor the bridge using an autonomous SHM application with excessive wind and vibration triggering the system to initiate monitoring. Additionally, the performance of the system is evaluated in terms of hardware durability, software stability, power consumption and energy harvesting capabilities. The Jindo Bridge SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date. This deployment demonstrates the strong potential of WSSNs for monitoring of large scale civil infrastructure.