• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.41-47
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• 2009

Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The power consumption imbalance among sensor nodes may cause a network partition and failures where the transmission from some sensors to the sink node could be blocked. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications and can drastically affect the network's communication energy dissipation. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Our improved cluster head selection method ensures that energy is consumed evenly among the nodes in the network, thereby increasing the network lifetime. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 10.36% and 24.05% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively and also prolongs the network lifetime.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Journal of KSNVE
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• v.8 no.6
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• pp.1181-1192
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• 1998

This paper describes the performance of a full-authority neural network-based fault tolerant system within a flight control system. This fault tolerant flight control system integrates sensor and actuator failure detection, identification, and accommodation (SFDIA and AFDIA), The first task is achieved by incorporating a main neural network (MNN) and a set of n decentralized neural networks (DNNs) to create a system for achieving fault tolerant capabilities for a system with n sensors assumed to be without physical redundancy The second scheme implements the same main neural network integrated with three neural network controllers (NNCs). The function of NNCs is to regain equilibrium and to compensate for the pitching, rolling. and yawing moments induced by the failure. Particular emphasis is placed in this study toward achieving an efficient integration between SFDIA and AFDIA without degradation of performance in terms of false alarm rates and incorrect failure identification. The results of the simulation with different actuator and sensor failures are presented and discussed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.599-602
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• 2011

A propulsion controller for one-time flight vehicles should be designed robustly so that it can complete its missions even in case sensor failures. These vehicles improve their fault tolerance by back-up sensors prepared for the failure of major sensors, which raises the total cost. This paper presents the NARX model which substitutes vehicles' velocity sensors, and detects failure of sensor signals by using model based fault detection. The designed NARX model and fault detection algorithm were optimized and installed in TI's TMS320F2812 so that they were linked to HILS instruments in real-time. The designed propulsion controller made the vehicle to have better fault tolerance with fewer sensors and to complete its missions under a lot of complicated failure situations. The controller's applicability was finally confirmed by tests under the HILS environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.419-428
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• 2015

Multipath routing technique is recognized as one of the effective approaches to improve the reliability of data forwarding. However, the traditional multipath routing focuses only on how many paths are needed to ensure a desired reliability. For this purpose, the protocols construct additional paths and thus cause significant energy consumption. These problems have motivated the study for the energy-efficient and reliable data forwarding. Thus, this paper proposes an energy-efficient cooperative multipath routing protocol with a small number of paths based on an inter path communication. The inter path communication (namely, cooperative multipath routing) in the proposed protocol helps to reinforce the multipath reliability and reduce the use of network resources. In addition, the proposed protocol provides a reliable end-to-end transmission time by using a transmission recovery method based on the local decision for the path or transmission failures.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.155-159
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• 2002

Wire ropes are used in a myriad of various industrial applications such as elevator, mine hoist, construction machinery, lift, and suspension bridge. Especially, wire rope of crane is important component to container transfer. If it happens wire rope failures in operating, it may lead to safety accident, economic power loss by productivity decline, competitive power decline of container terminal and so on. To solve this problem, we developed wire rope fault detecting system as a portable instrument, and this system is consisted of 3 parts that fault detecting part using hall sensor, permanent magnets and analog unit, and digital signal processing part using data acquisition card, monitoring part using wavelet transform, denoising method. In this paper, a wire rope is scanned by this system after makes several broken parts on the surface of wire rope artificially. All detected signal has external noise or disturbance according to circumstances. So, we applied to discrete wavelet transform to extract a signal from noisy data that was used filter. In practical applications of denoising, it is shown that wavelet pursue it with little information loss and smooth signal display. It is verified that the detecting system by denoising has good efficiency for inspecting faults of wire ropes in service. As a result, by developing this system, container terminal could reduce expense because of extension of wire ropes exchange period and could competitive power. Also, this system is possible to apply in several fields like that elevator, lift and so on.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.84-94
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• 2018

In recent years, the diminishing of operation and maintenance cost using advanced maintenance technology is attracting many companies' attention. Especially, the heavy machinery industry regards it as a crucial problem since a failure of heavy machinery requires high cost and long downtime. To improve the current maintenance process, the heavy machinery industry tries to develop a methodology to predict failure in advance and to find its causes using usage data. A better analysis of failure causes requires more data so that various kinds of sensor are attached to machines and abundant amount of product usage data is collected through the sensor network. However, the systemic analysis of the collected product usage data is still in its infant stage. Many previous works have focused on failure occurrence as statistical data for reliability analysis. There have been less works to apply product usage data into root cause analysis of product failure. The product usage data collected while failures occur should be considered failure cause analysis. To do this, this study proposes a methodology to apply product usage data into failure cause analysis. The proposed methodology in this study is composed of several steps to transform product usage into failure causes. Various statistical analysis combined with product usage data such as multinomial logistic regression, T-test, and so on are used for the root cause analysis. The proposed methodology is applied to field data coming from operated locomotive and the analysis result shows its effectiveness.

• Journal of Sensor Science and Technology
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• v.10 no.1
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• pp.33-41
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• 2001

Wire ropes have been widely used in industrial applications, wherever heavy weight should be carried safely or mechanical energy should be transmitted fast. Especially, wire rope failures in operating elevator may lead to extensive property damage and serious injury to nearby personnel. Hence, it is very important to inspect wire rope periodically. Failure defection of wire rope requires fundamental knowledge of wire rope construction, rope behavior, properties of fault, sensing and signal processing method. In this research, the development of a new fault detecting system incorporating Hall-effect sensors to detect flaws such as abrasion, broken wire, corrosion and deformation for aged wire ropes in elevator, is described. For using a detector as a portable instrument, several performances for implementing sensing part with Hall-effect sensor, analog signal processing unit and programs are described. Experiments and field testing results for the implemented detecting system are also given. As a result, it is verified that the detecting system has good efficiency for inspecting faults of aged wire ropes in service.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.12
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• pp.455-462
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• 2016

Wireless sensor networks have been researched to gather data about events on sensor fields from sources at sinks. Multipath routing is one of attractive approaches to reliably send data against the problem of frequent breakages on paths from sources to sinks due to node and link failures. As mobile events such as humans, animals, and vehicles are considered, sources may be continuously generated according to the movement of the mobile event. Thus, mobile events provide new challenging issue in multipath routing. However, the research on multipath routing mainly focus on both efficient multipath construction from sources to static sinks and fast multipath reconstruction against path breakages. Accordingly, the previous multipath routing protocols request each source continuously generated by a mobile event to construct individual multipath from the source to sinks. This induces the increase of multipath construction cost in the previous protocols in proportion to the number of source. Therefore, we propose efficient multipath routing protocol for supporting continuous sources generated by mobile events. In the proposed protocol, new source efficiently reconstructs its multipath by exploiting the existing multipath of previous sources. To do this, the proposed protocol selects one among three reconstruction methods: a local reconstruction, a global partial one, and a global full one. For a selection decision, we provide an analytical energy consumption cost model that calculates the summation of both the multipath reconstruction cost and the data forwarding cost. Simulation results show that the proposed protocol has better performance than the previous protocol to provide multipath routing for mobile events.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.12
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• pp.447-454
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• 2016

The research on multipath routing has been studied to solve the problem of frequent path breakages due to node and link failures and to enhance data delivery reliability in wireless sensor networks. In the multipath routing, mobile sinks such as soldiers in battle fields and rescuers in disaster areas bring about new challenge for handling their mobility. The sink mobility requests new multipath construction from sources to mobile sinks according to their movement path. Since mobile sinks have continuous mobility, the existing multipath can be exploited to efficiently reconstruct to new positions of mobile sinks. However, the previous protocols do not address this issue. Thus, we proposed an efficient multipath reconstruction protocol called LGMR for mobile sinks in wireless sensor networks. The LGMR address three multipath reconstruction methods based on movement types of mobile sinks: a single hop movement-based local multipath reconstruction, a multiple hop movement-based local multipath reconstruction, and a multiple hop movement-based global multipath reconstruction. Simulation results showed that the LGMR has better performance than the previous protocol in terms of energy consumption and data delivery delay.