• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.544-544
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• 2014

Energy harvesting technology, which scavenges electric power from ambient, otherwise wasted, energy sources, has been explored to develop self-powered wireless sensors and possibly eliminate the battery replacement cost for wireless sensors. Among ambient energy sources, vibration energy can be converted into electric power through a piezoelectric energy harvester. For the last decade, although tremendous advances have been made in design methodology to maximize harvestable electric power under a given vibration condition, the research in reliability assessment to ensure durability has been stagnant due to the complicated nature of the multiple failure modes of a piezoelectric energy harvester, such as the interfacial delamination, fatigue failure, and dynamic fracture. Therefore, this study presents the first-ever system reliability analysis for multiple failure modes of a piezoelectric energy harvester using the Generalized Complementary Intersection Method (GCIM), while accounts for the energy conversion performance. The GCIM enables to decompose the probabilities of high-order joint failure events into probabilities of complementary intersection events. The electromechanically-coupled analytical model is implemented based on the Kirchhoff plate theory to analyze its output performances of a piezoelectric energy harvester. Since a durable as well as efficient design of a piezoelectric energy harvester is significantly important in sustainably utilizing self-powered electronics, we believe that technical development on system reliability analysis will have an immediate and major impact on piezoelectric energy harvesting technology.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.435-442
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• 2016

For inertial navigation systems, initial information such as position, velocity and attitude is required for navigation. Self-alignment is the process to determine initial attitude on stationary condition using inertial measurements such as accelerations and angular rates. The accuracy of self-alignment is determined by inertial sensor error. As soon as an inertial navigation system is powered on, the temperature of accelerometer rises rapidly until temperature stabilization. It causes acceleration error which is called temperature stabilizing error of accelerometer. Therefore, temperature stabilizing error degrades the alignment accuracy and also increases alignment time. This paper suggests a method to calculate azimuthal attitude using curve fitting of horizontal control angular rate in fixed-gain self-alignment. It is verified by simulation and experiment that the accuracy is improved and the alignment time is reduced using the proposed method under existence of the temperature stabilizing error.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.5
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• pp.494-499
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• 2024

The possibility of a dye-sensitized solar cell (DSSC) submodule was evaluated as an independent power source that can drive a smart liquid crystal window (SLW) that selectively blocks sunlight when electricity is applied. In order to save energy and increase the functionality of buildings, SLW operation was supplied directly from DSSC submodule, rather than connecting to the existing power system and external power sources. It was confirmed that the SLW can control light transmittance through self-generation using the DSSC submodule composed of 6 cells at low light of 2,500 lux. These results imply that there is a high possibility of combining smart windows and DSSCs suitable for window-type building-integrated photovoltaic (BIPV) systems. DSSCs, which can self-generate power in low light, are expected to increase their usability in urban BIPV systems through combination with smart window technology.

• Composites Research
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• v.35 no.6
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• pp.378-393
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• 2022

As an emerging power generation technology, triboelectric nanogenerators (TENGs) have received increasing attention due to their boundless promise in energy harvesting and self-powered sensing applications. The recent rise of soft robotics has sparked widespread enthusiasm for developing flexible and soft sensors and actuators. TENGs have been regarded as promising power sources for driving actuators and self-powered sensors, providing a unique approach for the development of soft robots with soft sensors and actuators. In this review, TENG-based soft robots with different morphologies and different functions are introduced. Among them, the design of biomimetic soft robots that imitate the structure, surface morphology, material properties, and sensing/generating mechanisms of nature has greatly benefited in improving the performance of TENGs. In addition, various bionic soft robots have been well improved compared to previous driving methods due to the simple structure, self-powering characteristics, and tunable output of TENGs. Furthermore, we provide a comprehensive review of various studies within specific areas of TENG-enabled soft robotics applications. We first explore various recently developed TENG-based soft robots and a comparative analysis of various device structures, surface morphologies, and nature-inspired materials, and the resulting improvements in TENG performance. Various ubiquitous sensing principles and generation mechanisms used in nature and their analogous artificial TENG designs are demonstrated. Finally, biomimetic applications of TENG enabled in tactile displays as well as in wearable devices, artificial electronic skin and other devices are discussed. System designs, challenges and prospects of TENGs-based sensing and actuation devices in the practical application of soft robotics are analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1574-1579
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• 2016

This paper presents a self-powered sensor-node scheme using a RF wireless power harvesting techniques for improve drone time of flight. Sensor-node that is proposed is turned when two conditions satisfy: The one is input RF ID data from master-node should be same with sensor-node's ID, and the other one is RF wireless power harvesting system is turned on by hysteresis switch. In this paper, master-node's output is 26 dBm at 263 MHz. Maximum RF to DC power conversion efficiency is about 55% at 4-6 dBm input power condition (2 meter from master-node). The maximum RF wireless power harvesting range is about 13 meter form master-node. And power consumption of the sensor-node's load elements such as transmitter, MCU and temperature sensors is approximately average 15 mA at 5.0 V for 10 msec.

• Smart Structures and Systems
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• v.5 no.2
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• pp.139-152
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• 2009

Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as a fundamentally new approach for the development of a structural health monitoring and diagnostic system that utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to date results of our research, including the design and analysis of the structural nervous system.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.249-254
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• 2022

With the rapid advance of the semiconductor and Information and communication technologies, remote environment monitoring technology, which can detect and analyze surrounding environmental conditions with various types of sensors and wireless communication technologies, is also drawing attention. However, since the conventional remote environmental monitoring systems require external power supplies, it causes time and space limitations on comfortable usage. In this study, we proposed the concept of the self-powered remote environmental monitoring system by supplying the power with the levitation-electromagnetic generator (L-EMG), which is rationally designed to effectively harvest biomechanical energy in consideration of the mechanical characteristics of biomechanical energy. In this regard, the proposed L-EMG is designed to effectively respond to the external vibration with the movable center magnet considering the mechanical characteristics of the biomechanical energy, such as relatively low-frequency and high amplitude of vibration. Hence the L-EMG based on the fragile force equilibrium can generate high-quality electrical energy to supply power. Additionally, the environmental detective sensor and wireless transmission module are composed of the micro control unit (MCU) to minimize the required power for electronic device operation by applying the sleep mode, resulting in the extension of operation time. Finally, in order to maximize user convenience, a mobile phone application was built to enable easy monitoring of the surrounding environment. Thus, the proposed concept not only verifies the possibility of establishing the self-powered remote environmental monitoring system using biomechanical energy but further suggests a design guideline.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1435-1443
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• 2009

In this paper, an energy harvesting sensor network system is modeled and simulated by using the DEVS (Discrete Event System Specification) formalism. The system is composed of a sink (master) node, which is battery or mains powered, and a set of sensor (slave) nodes, each of which harvests ambient energy and converts it into electrical energy. For simulation, (i) the behavior of energy harvesting and storing circuits of the slave node is partitioned into a set of piecewise continuous segments and then each segment is represented as a discrete state; (ii) the interaction among the master node and components of the slave node is investigated preciously; and (iii) the investigated result is modeled and simulated by using the DEVS formalism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1321-1332
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• 2016

Wireless sensor networks (WSN) are self-organized networks that typically consist of thousands of low-cost, low-powered sensor nodes. The reliability and availability of WSNs can be affected by faults, including those from radio interference, battery exhaustion, hardware and software failures, communication link errors, malicious attacks, and so on. Thus, we propose a novel multi-agent fault tolerant system for wireless sensor networks. Since a major requirement of WSNs is to reduce energy consumption, we use multi-agent and mobile agent configurations to manage WSNs that provide energy-efficient services. Mobile agent architecture have inherent advantages in that they provide energy awareness, scalability, reliability, and extensibility. Our multi-agent system consists of a resource manager, a fault tolerance manager and a load balancing manager, and we also propose fault-tolerant protocols that use multi-agent and mobile agent setups.

• Journal of electromagnetic engineering and science
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• v.8 no.1
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• pp.6-11
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• 2008

Advances in low power design open the possibility to harvest energy from the environment to power electronic circuits. Electrical energy can be harvested from piezoelectric transducer. Piezoelectric materials can be used as mechanisms to transfer mechanical energy usually vibrating system into electrical energy that can be stored and used to power other devices. Micro- to milli-watts power can be generated from vibrating system. We developed definitive and analytical models to predict the power generated from a cantilever beam attached with piezoelectric transducer. Analytical models are pin-force method, enhanced pin-force method and Euler-Bernoulli method. Harmonic oscillations and random noise will be the two different forcing functions used to drive each system. It has been selected the best model for generating electric power based upon the analytical results obtained.