• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.281-286
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• 2011

Station structures, one of important infrastructures, which have been being operated since the 1970s, are especially vulnerable to even the medium-level earthquake and they could be damaged by long-term internal or external vibrations such as ambient vibrations. Recently, much attention has been paid to real-time monitoring of the fatal defect or long-term deterioration of civil infrastructures to ensure their safety and adequate performance throughout their life span. In this study, a structural health monitoring methodology using acceleration responses is proposed to evaluate the health-state of the station structures and to detect initial damage-stage. A damage index is developed using the acceleration data and it is applied to outlier analysis, one of unsupervised learning based pattern recognition methods. A threshold value for the outlier analysis is determined based on confidence level of the probabilistic distribution of the acceleration data. The probabilistic distribution is selected according to the feature of the collected data.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1205-1210
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• 2004

The 4-20mA analog signal used in the various industrial fields to interface sensor in distributed process control has been replaced with relatively simple digital networks, called "fieldbus, and recently by Ethernet. Significant advances in Internet and computer technology have made it possible to develop an Internet based control, monitoring, and operation scheduling system for heating, ventilation and air-conditioning (HVAC) systems. The seamless integration of data networks with control networks allows access to any control point from anywhere. Field compatible field devices become so-called "smart" devices, capable of executing simple control, diagnostic and maintenance functions and providing bidirectional serial communication to higher level controller. The most important HVAC of BAS has received nationwide attention because of higher portion of more than 40% in building sector energy use and limited resources. This paper presents the Internet-based monitoring and control architecture and development of LonWorks control modules for AHU (air handling units) of HVAC in viewpoint of configuring BAS network. This article addresses issues in architecture section, electronics, embedded processors and software, and internet technologies.

• Smart Structures and Systems
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• v.20 no.1
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• pp.43-52
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• 2017

Structural health monitoring has drawn great attention in the field of civil engineering in past two decades. These structural health monitoring methods evaluate structural integrity through high-quality sensor measurements of structures. Due to electronic deterioration or aging problems, sensors may yield biased signals. Therefore, the objective of this study is to develop a fault detection method that identifies malfunctioning sensors in a sensor network. This method exploits the autoregressive modeling technique to generate a bank of Kalman estimators, and the faulty sensors are then recognized by comparing the measurements with these estimated signals. Three types of faults are considered in this study including the additive, multiplicative, and slowly drifting faults. To assess the effectiveness of detecting faulty sensors, a numerical example is provided, while an experimental investigation with faults added artificially is studied. As a result, the proposed method is capable of determining the faulty occurrences and types.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.5-8
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• 2006

The Alternative energy has lately attracted considerable attention due to the high oil price and environment problem. In this study, pilot test facility for using the geothermal energy source from riverbank filtration was constructed and monitoring devices are installed to estimate the efficiency of this system. Initial installation cost can be saved efficiently by connect ing a heat pump system into the exist ing pumping well in Changwon riverbank filtration site. One set of monitoring results during summer was presented and analyzed.

• Tribology and Lubricants
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• v.10 no.4
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• pp.51-58
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• 1994

Condition monitoring technology has recently been received much attention in the light of its significance on the maintenance of complex machineries such as turbines in power plants. Currently, turbines in power plants are maintained by scheduled overhaul based on the manufacturer's recommendations and the utility's experience. Although this preventive maintenance is known to be very effective, operators have less access to identify failure of elements when it happens between overhaul period. Therefore, in this study, a development of a on-line condition monitoring system through wear debris analysis of lubricating oils is aimed with a view to detecting abnormal wear behaviour of bearings and other wet-components at an early stage, allowing better outage scheduling and minimizing forced outages. For field application purposes, the on-line system developed was installed on the turbine of the No.4 unit at Ulsan Power Plant and its performance has been evaluated on site.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.266-284
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• 2010

Piezoelectric materials have become the most attractive functional materials for sensors and actuators in smart structures because they can directly convert mechanical energy to electrical energy and vise versa. They have excellent electromechanical coupling characteristics and excellent frequency response. In this article, the research activities and achievements on the applications of piezoelectric materials in smart structures in China, including vibration control, noise control, energy harvesting, structural health monitoring, and hysteresis control, are introduced. Special attention is given to the introduction of semi-active vibration suppression based on a synchronized switching technique and piezoelectric fibers with metal cores for health monitoring. Such mechanisms are relatively new and possess great potential for future applications in aerospace engineering.

• Hwankyungkyoyuk
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• v.11 no.2
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• pp.252-261
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• 1998

Since 1980's during which environmental pollution became serious enough to urge various types of environmental educations in many areas. But, most emphasis has been put on theoretical education. Even field education training mostly focused on water pollution. Therefore, simple air pollution monitoring system was needed for better field education in air pollution. In this study, we evaluated Passive Sampler as an useful tool for teaching air pollution in field. Students have found passive sampler very effective tool. Recent comparative study of auto-monitoring and passive sampler networks suggested a potential use of passive sampler as an useful tool for environmental education. In this study, the correlation between two sets of values appears very high judging from the regression slope of 0.92 and correlation coefficient of 0.91 However, inexpensive Passive sampler with easy-to-operate colorimeter, has not been used in environmental education partially because large scale fluctuation in time and space characteristic to air pollution has been overlooked so that the sampler has not been tested for an effective educational tool. Passive sampler certainly deserves further in depth research as an effective air monitoring system, and better attention to its usefulness to teach students and public.

• Proceedings of the KIEE Conference
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• 2004.11a
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• pp.223-226
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• 2004

Many extensive researches in the area of sensor's technology for corrosion monitoring in concrete structures have increasingly been carried out in recent years. This paper gives a brief discussion on the principles and usage of the role of sensors involved in both corrosion initiation and propagation steps of reinforcement corrosion monitoring in concrete structures. Special attention was given to the review of various sensing devices, selection of reliable sensing devices for detecting reinforcement corrosion at the particular environment and at the efficiency of the devices used. Various sensing operations in new and existing concrete structures are also described.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.108-125
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• 1998

The EWMA(Exponentially Weighted Moving Average) has recently received a great deal of attention in the quality control literature as a process monitoring tool on the shop floor of manufacturing industires, since it is easy to plot, to interpret, and its control limits are easy to obtain. Most a, pp.ications of the EWMA for process monitoring have concentrated on the problem of detecting shifts of a process mean and a process standard deviation with ARL(Average Run Length) properties. But there may be the necessity of controlling linearity on product quality such as the correlation coefficient to the process operator. Control managers may want to protect the increase of a process correlation coefficient value, such as 0, between two variables of interest. However, there are few studies concerned on this part. Therefore, we propose EWMA models for a process correlation coefficient using two transformed statistics, T-statistic and (Fisher's) Z-statistic. We also present some results of simulation by SAS/IML and compare two models.