• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.667-676
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• 2014

Connectivity is a crucial quality of service measure in wireless sensor networks. However, the network is always at risk of being split into several disconnected components owing to the sensor failures caused by various factors. To handle the connectivity problem, this paper introduces an in-advance mechanism to prevent network partitioning in the initial deployment phase. The approach is implemented in a distributed manner, and every node only needs to know local information of its 1-hop neighbors, which makes the approach scalable to large networks. The goal of the proposed mechanism is twofold. First, critical nodes are locally detected by the critical node detection (CND) algorithm based on the concept of maximal simplicial complex, and backups are arranged to tolerate their failures. Second, under a greedy rule, topological holes within the maximal simplicial complex as another potential risk to the network connectivity are patched step by step. Finally, we demonstrate the effectiveness of the proposed algorithm through simulation experiments.

• The KIPS Transactions:PartA
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• v.16A no.1
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• pp.17-26
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• 2009

Large-scale wireless sensor network are expected to play an increasingly important role for the data collection in harmful area. However, the physical fragility of sensor node makes reliable routing in harmful area a challenging problem. Since several sensor nodes in harmful area could be damaged all at once, the network should have the availability to recover routing from node failures in large area. Many routing protocols take accounts of failure recovery of single node but it is very hard these protocols to recover routing from large scale failures. In this paper, we propose a routing protocol, which we refer to as LSFA, to recover network fast from failures in large area. LSFA detects the failure by counting the packet loss from parent node and in case of failure detection LSFAdecreases the routing interval to notify the failure to the neighbor nodes. Our experimental results indicate clearly that LSFA could recover large area failures fast with less packets than previous protocols.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.1-14
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• 1996

Design of a reliable control systems is investigated for a class of uncertain linear plants. The uncertainty considered here is for the ase of uncertainty in the system matrix. A decentralized control scheme with two observer-based feedback controllers is developed, and it is shown that the resulting closed-loop system is reliable in the sense that the control scheme provides guaranteed stability and $H_{\infty}$-norm bounded performance in the event of sensor and/or actuator failures as well as in the presence of parameter uncertainties. We observed that soft-type failures were additional exogenous inputs to the closed-loop system. As a results, the sensor and/or actuator failures can be tolerated in the design, which is achieved by extending the methodology developed in.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.87-93
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• 2009

In this paper, we propose and evaluate the availability of single sensor node using a hierarchial modeling approach. We divides a sensor node into a software and hardware and analyze failures of each component. We construct Markov chains to represent the components of a sensor node, and then we construct a hierarchical model which use fault tree in upper level and Markov chains in lower level. We evaluate the availability and down of single sensor node.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1961-1968
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• 2004

The design of a reliable and failsafe control system requires that sensor failures be detected and identified within acceptable time limit so that system malfunction can be prevented. This paper presents a model-based approach to sensor fault detection with applications to vehicle stability control systems. The effectiveness of the proposed method is illustrated through test data-based evaluation. Vehicle test data-based evaluation results show that the proposed fault management scheme can be used for the design of a failsafe VSCs.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.34.5-34
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• 2001

This paper presents a reliable H$\infty$ controller design for singularly perturbed systems by the delta operator approach that guarantees stability with a known H$\infty$ norm bound in case of failures in some control channels. Prespecified are the control channels that may experience failures. Sensor outage is covered in this paper It is shown that the delta systems have improved finite wort length characteristics in the example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2306-2313
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• 2010

This paper describes a model based fault detection algorithm for an Advanced ESC System which consists of Hydraulic Control Unit (HCU) with built-in wheel pressure sensors. Advanced ESC System can be used for various value-added functions such as Stop & Go Function and Regenerative Brake Function. Therefore, HCU must have a reliable fault detection. Due to the huge amount of sensor signals, existing specific sensor based fault detection of HCU cannot guarantee the safety of vehicle. However, proposed algorithm dose not require the sensors. When model based fault detection algorithm detects severe failures of the HCU, it warns the driver in advance to prevent accidents due to the failures. For this purpose, a mathematical model is developed and validated in comparison to actual data. Simulation results and data acquired from an actual system are compared with each other to obtain the information needed for the fault detection process.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.45.3-45
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• 2001

This paper deal with a fault detection algorithm for front wheel passenger car systems by using robust $H{\infty}$ control theory. Firstly, we present a unified formulation of vehicle dynamics for front wheel car systems and transform this formulation into state space form. Also, by considering the cornering stiffness which depends on the tyre-road contact conditions, a multiplicative uncertainty for vehicle model is described. Next, the failures of sensor and actuator for vehicle system are defined in which the fault .lter is considered. From the nominal vehicle model, an augmented system includes the multiplicative uncertainty and the model of fault filter is proposed. Lastly by using $H{\infty}$ norm property the fault detect conditions are deefi.ned, and the actuator and sensor failures are detected and isolated by designing the robust $H{\infty}$ controller, respectively.