• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.803-807
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• 2003

Tele-operation and remote monitoring techniques are essential and important technologies for performing the inspection and repair tasks effectively in nuclear power plants. This paper presents the application of a mobile robot for the remote monitoring and inspection of the Calandria faces, where human access is limited because of the high-level radioactive environments during full power operation. The mobile robot was designed with reconfigurable crawler type of wheels attached on the front and rear side in order to pass through the ditch. The extendable mast, mounted on the mobile robot, can be extended up to 8 m vertically. This robot was also equipped a visible CCD/thermal infrared inspection head module and a stereo camera module for the enhancement of visual inspection.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• Smart Structures and Systems
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• v.21 no.2
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• pp.139-149
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• 2018

Understanding the current status of a construction project is necessary to achieve successful on-site management. Real-time information delivery is a major concern for construction industry practitioners in order to expedite decisions and discussions. We propose the use of a first personal view (FPV) system of a quadcopter drone as a tool for monitoring on-site status and communicating between construction participants. The most important function of the drone FPV system is its ability to visually monitor construction site situations in real time. An on-site management system process is developed, verified, and applied to several construction work tasks after determining factors that affect efficient construction management. The proposed system is expected to assist the construction manager in achieving high efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.199-206
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• 1991

As the development of modern technology, human works shift whose roll from physical conditions to the system monitoring tasks. In this paper, safety-presentation configuration is discussed instead of well-known fault-warning configuration. Safety-presentation configuration is verified as superior to the fault-warning configuration in hazard prevention. The estimation of system states involves the decision making environments which lack of required in formations and most of all the informations are not precise too. And the limitation of human information processing show doubtful results. So the estimation of system states is regardes as fuzzy number, and its operation produces the parameter that explain the discriminability(d), decision criterion ($\beta$) of system operator's behaviors. These two values served as performance indices. Especially the $\beta$ is a good milestone of the operator's altitude degree of caution.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.165-166
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• 2023

Construction inspection and monitoring are key activities in construction projects. Automation of inspection tasks improves the limitations and inefficiencies of manual construction inspections, enabling systematic and consistent construction inspections. In this paper, an RTSP (Real-Time Streaming Protocol) system is used to remotely manage and supervise the construction site without having to visit the construction site by deploying a robot on site on behalf of four construction stakeholders (owner, supervisor, constructor, and designer). I would like to propose. The proposed system can contribute to identifying and monitoring the process process and work results at the construction site in real time.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.1
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• pp.91-99
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• 2012

The main objective of this study is to examine the feasibility of using lead zirconate titanate (PZT)'s direct piezoelectric response as vibrational feature for damage monitoring in beam structures. For the purpose, modal strain energy (MSE)-based damage monitoring in beam structures using dynamic strain response based on the direct piezoelectric effect of PZT sensor is proposed in this paper. The following approaches are used to achieve the objective. First, the theoretical background of PZT's direct piezoelectric effect for dynamic strain response is presented. Next, the damage monitoring method that utilizes the change in MSE to locate of damage in beam structures is outlined. For validation, forced vibration tests are carried out on lab-scale cantilever beam. For several damage scenarios, dynamic responses are measured by three different sensor types (accelerometer, PZT sensor and electrical strain gage) and damage monitoring tasks are performed thereafter. The performance of PZT's direct piezoelectric response for MSE-based damage monitoring is evaluated by comparing the damage localization results from the three sensor types.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.224-232
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• 2009

Power plant start-up is a complicate process involving hundreds of operations that should be performed either automatically or manually. Several major operations should be proceeded in parallel and each major operation is again broken down into detailed operations that must be carried out in a strict sequence. Even though most of the operations are automated, still substantial portions of the operations are carried out manually and the operational status should be monitored by the crew members, which are quite stressful tasks to be performed in real time. In this paper, a data structure called an Event Sequence Monitoring Graph(ESMG) is proposed for monitoring a sequence of events involved in the power plant start-up process. The ESMG is currently being applied to a thermal power plant with a rated output of 500MW. An application example is shown with the boiler feed water pump system start-up process, which exhibits a good potential for future applications.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.2
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• pp.217-225
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• 2019

Objectives: The aim of this study is to evaluate the quality management systems of domestic asbestos survey and monitoring service providers and the relationships with the number of licenses or designations and sales performances. Methods: Data on quality management systems were collected by assessors who were assigned by the Korea Occupational Safety and Health Agency(KOSHA) during a pilot evaluation program for designated asbestos survey and monitoring service providers in 2016 using evaluation criteria developed by KOSHA. Basic characteristics, evaluated scores, and sales performance were gathered and statistically analyzed. Results: The median and arithmetic mean of the total scores were 0.64 and 0.66. Evaluation fields that scored highly with the highest percentages were sales performance, installation and availability of equipment, compliance with the mandatory minimum number of airborne samples, laboratory independence, and results of proficiency analytical testing, in that order. Evaluation fields that received low marks with the highest percentages were the training of personnel, blank field samples, calibration of flow rates, preliminary check and visual inspection of the work area prior to the clearance test, and review and approval of final reports, in that order. Comparison of normalized scores between service providers registered for asbestos and other tasks and those designated for only asbestos showed significant differences in their evaluated scores. Sales performance did not show a positive correlation with evaluated scores. Conclusions: The quality management systems of domestic asbestos survey and monitoring service providers were poor. High scores were recorded mostly in evaluation fields related to regulatory requirements. Low scores were recorded mostly in evaluation fields related to documentation and recordkeeping. Considering the low influence of quality on sales performance, the government needs to evaluate the quality management of asbestos survey and monitoring service providers and provide the results to public in order to address their low levels of quality management.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.9
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• pp.413-422
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• 2002

In a power plant, disturbance detection and diagnosis are massive and complex problems. Once a disturbance occurs, it can be either persistent, self cleared, cleared by the automatic controllers or propagated into another disturbance until it subsides in a new equilibrium or a stable state. In addition to the Physical complexity of the power plant structure itself, these dynamic behaviors of the disturbances further complicate the fault monitoring and diagnosis tasks. A data structure called a disturbance interrelation analysis graph(DIAG) is proposed in this paper, trying to capture, organize and better utilize the vast and interrelated knowledge required for power plant disturbance detection and diagnosis. The DIAG is a multi-layer directed AND/OR graph composed of 4 layers. Each layer includes vertices that represent components, disturbances, conditions and sensors respectively With the implementation of the DIAG, disturbances and their relationships can be conveniently represented and traced with modularized operations. All the cascaded disturbances following an initial triggering disturbance can be diagnosed in the context of that initial disturbance instead of diagnosing each of them as an individual disturbance. DIAG is applied to a typical cooling water system of a thermal power plant and its effectiveness is also demonstrated.