• Smart Structures and Systems
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• v.18 no.5
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.245-252
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• 2020

Unexpected equipment defects can cause a huge economic losses in the society at large. Although condition monitoring can provide solutions, the signal processing algorithms must be developed to predict mechanical failures using data acquired from various sensors attached to the equipment. The signal processing algorithms used in a condition monitoring requires high computing efficiency and resolution. To improve condition monitoring on a wireless sensor network(WSN), data visualization can maximize the expressions of the data characteristics. Thus, this paper proposes the extraction of visual feature from temperature data over time using condition monitoring based on a WSN to identify environmental conditions of equipment in a large-scale infrastructure. Our results show that time-frequency analysis can visually track temperature changes over time and extract the characteristics of temperature data changes.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.91-105
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• 2010

A wireless sensor network communication technique has been broadly studied with continuous advances in ubiquitous computing environment. Especially, because the resource of the sensor node is limited, it is important to reduce the communication energy by using an energy-efficient routing protocol. The existing cluster-based routing protocols have a problem that they cannot select a cluster head efficiently by randomly choosing a head. In addition, because the existing cluster-based routing protocols do not support the large scale of network, they cannot be used for various applications. To solve the above problems, we, in this paper, propose a new cluster-based routing protocol using representative paths. The proposed protocol constructs an efficient cluster with distributed cluster heads by creating representative paths based on hop count. In addition, a new routing protocol supports multi-hop routing for data communication between a cluster member node and a cluster head as well as between cluster heads. Finally, we show that our protocol outperforms LEACH and Multihop-LEACH in terms of reliability and scalability.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.156-162
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• 2020

Wireless Sensor Network (WSN) field is mainly studied to monitor and characterize large-scale physical environments to track various environmental or physical conditions, such as temperature, pressure, wind speed and humidity. WSN can be used in various applications such as wild surveillance, military target tracking and monitoring, dangerous environmental exploration and natural disaster relief. We design probabilistic mobile models that apply to mobile ad hoc network mobile environments. A probabilistic shift model proposed by dividing the number of moving nodes and the distance of travel into two categories to express node movement characteristics. The proposed model of movement through simulation was compared with the existing random movement model, ensuring that the width and variation rate of the first node node node node (FND) was stable regardless of the node movement rate. In addition, when the proposed mobile model is applied to the routing protocol, the superiority of network life can be verified from measured FND values. We overcame the limitations of the existing random movement model, showing excellent characteristics in terms of energy efficiency and stable in terms of changes in node movement.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.102-110
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• 1998

The horizontal fillet welding is prevalently used in heavy and ship building industries to fabricate the large scale structures. A deep understanding of the horizontal fillet welding process is restricted, because the phenomena occurring in welding are very complex and highly non-linear characteristics. To achieve the satisfactory weld bead geometry in robot welding system, the seam tracking algorithm should be reliable. The number of seam tracker was developed for arc welding automation by now. Among these seam tracker, the arc sensor is prevalently used in industrial robot welding system because of its low cost and flexibility. However, the accuracy of arc sensor would be decreased due to the electrical noise and metal transfer. In this study, the signal processing algorithm based on the neural network was implemented to enhance the reliability of measured welding current signals. Moreover, the seam tracking algorithm in conjunction with the signal processing algorithm was implemented to trace the center of weld line. It was revealed that the neural network could be effectively used to predict the welding current signal at the end of weaving.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.846-850
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• 2009

Recently, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics such as environmental monitoring, smart spaces, medical applications, and precision agriculture. The sensor nodes are battery powered. Therefore, the energy is the most precious resource of a wireless sensor network since periodically replacing the battery of the nodes in large scale deployments is infeasible. Energy efficient mechanisms for gathering sensor readings are indispensable to prolong the lifetime of a sensor network as long as possible. There are two energy-efficient approaches to prolong the network lifetime in sensor networks. One is the compression scheme to reduce the size of sensor readings. When the communication conflict is occurred between two sensor nodes, the sender must try to retransmit its reading. The other is the MAC protocol to prevent the communication conflict. In this paper, we propose a novel approaches to reduce the size of the sensor readings in the MAC layer. The proposed scheme compresses sensor readings by allocating the time slots of the TDMA schedule to them dynamically. We also present a mathematical model to predict latency from collecting the sensor readings as the compression ratio is changed. In the simulation result, our proposed scheme reduces the communication cost by about 52% over the existing scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.15-21
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• 2009

The goal of wireless sensor networks is to collect sensing data on specific region over wireless communication. Sink node gathers all local sensing data, processes and transmits them to users who use sensor networks. Generally, senor nodes are low-cost, low power devices with limited sensing, computation and wireless communication capabilities. And sensor network applies to multi-hop communication on large-scale network. As neighboring sensor nodes have similar data, clustering is more effective technique for 'data-aggregation'. In cluster formation technique based on multi-hop, it is necessary that the number of cluster member nodes should be distributed equally because of the balance of cluster formation To achieve this, we propose a method to customize cluster member nodes for energy-efficiency in wireless sensor networks.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.641-659
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• 2010

Structural Health Monitoring (SHM) gradually becomes a technique for ensuring the health and safety of civil infrastructures and is also an important approach for the research of the damage accumulation and disaster evolving characteristics of civil infrastructures. It is attracting prodigious research interests and the active development interests of scientists and engineers because a great number of civil infrastructures are planned and built every year in mainland China. In a SHM system the sheer number of accompanying wires, fiber optic cables, and other physical transmission medium is usually prohibitive, particularly for such structures as offshore platforms and long-span structures. Fortunately, with recent advances in technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensor technique has been developing rapidly and is being used gradually in the SHM of civil engineering structures. In this paper, some recent advances in the research, development, and implementation of wireless sensors for the SHM of civil infrastructures in mainland China, especially in Dalian University of Technology (DUT) and Harbin Institute of Technology (HIT), are introduced. Firstly, a kind of wireless digital acceleration sensors for structural global monitoring is designed and validated in an offshore structure model. Secondly, wireless inclination sensor systems based on Frequency-hopping techniques are developed and applied successfully to swing monitoring of large-scale hook structures. Thirdly, wireless acquisition systems integrating with different sensing materials, such as Polyvinylidene Fluoride(PVDF), strain gauge, piezoresistive stress/strain sensors fabricated by using the nickel powder-filled cement-based composite, are proposed for structural local monitoring, and validating the characteristics of the above materials. Finally, solutions to the key problem of finite energy for wireless sensors networks are discussed, with future works also being introduced, for example, the wireless sensor networks powered by corrosion signal for corrosion monitoring and rapid diagnosis for large structures.

• Smart Structures and Systems
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• v.6 no.8
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• pp.939-951
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• 2010

A low-cost wireless sensor network (WSN) solution with highly expandable super and simple nodes was developed. The super node was designed as a sensing unit as well as a receiving terminal with low energy consumption. The simple node was designed to serve as a cheaper alternative for large-scale deployment. A 12-bit ADC inputs and DAC outputs were reserved for sensor boards to ease the sensing integration. Vibration and thermal field tests of the Chi-Lu Bridge were conducted to evaluate the WSN's performance. Integral acceleration, temperature and tilt sensing modules were constructed to simplify the task of long-term environmental monitoring on this bridge, while a star topology was used to avoid collisions and reduce power consumption. We showed that, given sufficient power and additional power amplifier, the WSN can successfully be active for more than 7 days and satisfy the half bridge 120-meter transmission requirement. The time and frequency responses of cables shocked by external force and temperature variations around cables in one day were recorded and analyzed. Finally, guidelines on power characterization of the WSN platform and selection of acceleration sensors for structural health monitoring applications were given.