• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.116-124
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• 2017

The purpose of this study is to examine the effect of subjective overwork on health and the moderating effect of risk perception in the relationship between subjective overwork and health. The data used in this study are the fourth Korean Working Condition Survey (KWCS) conducted by Korea Occupational Safety and Health Agency (KOSHA) in 2014. The items related to actual working hours, subjective overwork, health, and risk perception were used. A total of 18,508 workers who are 1) waged workers, 2) work more than three days a week, 3) work more than 21 hours a week, 4) work longer than preferred work hours or work as longer as they desired were selected. Hierarchical regression analysis was performed to identify the effect of actual work hours, subjective overwork, prevalence of risk, lethalness of accident damage on health and to determine the moderating effects of prevalence of risk and lethalness of accident damage. As a result, actual work hours, subjective overwork, prevalence of risk, lethalness of accident damage had an effect on worker's health problems. Second, lethalness of accident damage had a moderating effect in the relationship between subjective overwork and health. These results suggest that organizations should manage worker's environmental factors and other threats that could increase the lethalness of accident damage.

• Journal of the Health Care and Life Science
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• v.9 no.2
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• pp.355-361
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• 2021

In the context of COVID-19, the economic downturn affects health as well as concerns about economic damage to individuals. In this study, among a total of 15,047 people who were economically active during the community health survey for those aged 19 and over, health behaviors related to the impact of changes in daily life due to the demographic and social and economic characteristics of COVID-19 were concerned about economic damage. was analyzed to determine whether it had an effect on Factors affecting the fear of economic damage were gender, education level, monthly income level, status, subjective health level, physical activity, and smoking, which had more influence on the fear of economic damage than other characteristics. In this study, males(p=0.024), high school graduates(p<0.001), monthly income level of 1,000,001 to 3,000,000won(p-=0.002), wage workers(p<0.001), subjects who responded that their subjective health level was 'similar'(p=0.009), subjects who responded 'similar' in physical activity(p<0.001), and smoked 'similar'(p=0.016) Those who answered high were more concerned about economic damage. Considering that COVID-19 is highly likely to be prolonged and social distancing cannot be ruled out, which affects health care due to economic damage, it is necessary to reflect it in health program development and economic-related fiscal policies.

• Smart Structures and Systems
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• v.14 no.2
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• pp.85-104
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• 2014

Damage detection is a challenging, complex, and at the same time very important research topic in civil engineering. Identifying the location and severity of damage in a structure, as well as the global effects of local damage on the performance of the structure are fundamental elements of damage detection algorithms. Local damage detection is essential for structural health monitoring since local damages can propagate and become detrimental to the functionality of the entire structure. Existing studies present several methods which utilize sensor data, and track global changes in the structure. The challenging issue for these methods is to be sensitive enough in identifYing local damage. Autoregressive models with exogenous terms (ARX) are a popular class of modeling approaches which are the basis for a large group of local damage detection algorithms. This study presents an algorithm, called Influence-based Damage Detection Algorithm (IDDA), which is developed for identification of local damage based on regression of the vibration responses. The formulation of the algorithm and the post-processing statistical framework is presented and its performance is validated through implementation on an experimental beam-column connection which is instrumented by dense-clustered wired and wireless sensor networks. While implementing the algorithm, two different sensor networks with different sensing qualities are utilized and the results are compared. Based on the comparison of the results, the effect of sensor noise on the performance of the proposed algorithm is observed and discussed in this paper.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.125-128
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• 2003

Low-velocity impact damage is a major concern in the design of structures made of composite materials, because impact damage is hidden inside and cannot be detected by visual inspection. The piezoelectric thin film sensor can be used to detect variations in structural and material properties for structural health monitoring. In this paper, the PVDF and PZT sensors were used for monitoring impact damage initiation in Gr/Ep composite panel to illustrate this potential benefit. A series of impact test at various impact energy by changing impact mass and height is performed on the instrumented drop weight impact tester. The wavelet transform(WT) is used to decompose the piezoelectric sensor signals in this study. Test results show that the particular waveform of sensor signals implying the damage initiation and development are detected above the damage initiation impact energy. And it is found that both PZT and PVDF sensors can be used to detect the impact damage.

• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.539-558
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• 2012

The diagnosis of bridge serviceability is carried out by a combination of in-situ visual inspection, static and dynamic loading tests and analyses. Structural health monitoring (SHM) using information technology and sensors is increasingly being used for providing a better estimate of structural performance characteristics rather than above traditional methods. Because the mechanical behavior of bridges with various kinds of damage can not be made clear, it is very difficult to estimate both the damage mode and degree of damage of existing bridges. In this paper, the sensitivity of both static and dynamic behaviors of bridges are studied as a measure of damage assessment through experiments on model bridges induced with some specified artificial damages. And, a method of damage assessment of bridges based on those behaviors is discussed in detail. Finally, based on the results, a possible application for structural health monitoring systems for existing bridges is also discussed.

• Structural Monitoring and Maintenance
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• v.10 no.1
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• pp.63-86
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• 2023

Structural health monitoring and damage detection are essential for assessing, maintaining, and rehabilitating structures. Most of the existing damage detection approaches compare the current state structural response with the undamaged vibrational structural response, which is unsuitable for old and existing structures where undamaged vibrational responses are absent. One of the approaches for existing structures, numerical model updating/inverse modelling, available in the literature, is limited to numerical studies with high-end software. In this study, an attempt is made to study the effectiveness of the model updating technique, simplify modelling complexity, and economize its usability. The optimization-based detection problem is addressed by using programmable open-sourced code, OpenSees^® and a derivative-free optimization code, NOMAD^®. Modal analysis is used for damage identification of beam-like structures with several damage scenarios. The performance of the proposed methodology is validated both numerically and experimentally. The proposed method performs satisfactorily in identifying both locations and intensity of damage in structures.

• Journal of Environmental Policy
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• v.12 no.1
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• pp.75-100
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• 2013

Health damages such as pneumoconiosis and kidney damage, caused by environmental hazardous factors are being reported in health impact assessment conducted on environmentally vulnerable areas, including cement factories and refineries. Current legal system for relieving the environmental victims is not effective enough because the environmental health act does not specify the environmental hazardous factors to be considered for the relief. The aim of this study is to examine the problems of the existing system by making empirical analysis on health damages and afflicted people as well as on cases when afflicted people were able to be covered by remedy system. The results show that, insufficiencies of the relief system are due to the following reasons: First, current Environmental Health Act does not act well as a remedy system. Second, due to its unique nature of environmental health damage, it is hard to identify and prove the cause of health damage and unlawful actions of violators in the process of environmental dispute conciliation and lawsuits against polluters. This paper suggests following solutions on above mentioned problems. First, in defining the range and definition of environmental diseases, negative system should be used alongside with the current positive system. Second, we suggest adding the nature of public law to relief system, in order to ease the legal burden of proof. Third, in case when it is hard to identify the polluters and one cannot expect reliefs for their damage, it is possible to elevate the effectiveness of the relief measure by expanding scope of the search for possible environmental hazardous factors that caused the health damage. It is urgent to improve the relief system so as to secure the environmental rights of Koreans.

• Smart Structures and Systems
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• v.25 no.2
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• pp.169-181
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• 2020

Sensor placement is a crucial aspect of bridge health monitoring (BHM) dedicated to accurately estimate and locate structural damages. In addressing this goal, a sensor placement framework based on the deflection influence line (DIL) analysis is here proposed, for the optimal design of damage detection-oriented BHM system. In order to improve damage detection accuracy, we explore the change of global stiffness matrix, damage coefficient matrix and DIL vector caused by structural damage, and thus develop a novel sensor placement framework based on the Fisher information matrix. Our approach seeks to determine the contribution of each sensing node to damage detection, and adopts a distance correction coefficient to eliminate the information redundancy among sensors. The proposed damage detection-oriented optimal sensor placement (OSP) method is verified by two examples: (1) a numerically simulated three-span continuous beam, and (2) the Pinghu bridge which has existing real damage conditions. These two examples verify the performance of the distance corrected damage sensitivity of influence line (DSIL) method in significantly higher contribution to damage detection and lower information redundancy, and demonstrate the proposed OSP framework can be potentially employed in BHM practices.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.240-247
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• 2006

Piezoelectric sensor-based health monitoring technique using a two-step support vector machine (SYM) classifier is discussed for damage identification of a railroad track. An active sensing system composed of two PZT patches was investigated in conjunction with both impedance and guided wave propagation methods to detect two kinds of damage of the railroad track (one is a hole damage of 0.5cm in diameter at web section and the other is a transverse cut damage of 7.5cm in length and 0.5cm in depth at head section). Two damage-sensitive features were extracted one by one from each method; a) feature I: root mean square deviations (RMSD) of impedance signatures and b) feature II: wavelet coefficients for $A_0$ mode of guided waves. By defining damage indices from those damage-sensitive features, a two-dimensional damage feature (2-D DF) space was made. In order to minimize a false-positive indication of the current active sensing system, a two-step SYM classifier was applied to the 2-D DF space. As a result, optimal separable hyper-planes were successfully established by the two-step SYM classifier: Damage detection was accomplished by the first step-SYM, and damage classification was also carried out by the second step-SYM. Finally, the applicability of the proposed two-step SYM classifier has been verified by thirty test patterns.

• Smart Structures and Systems
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• v.5 no.4
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• pp.483-494
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• 2009

Damage detection has been proven to be a challenging task in structural health monitoring (SHM) due to the fact that damage cannot be measured. The difficulty associated with damage detection is related to electing a feature that is sensitive to damage occurrence and evolution. This difficulty increases as the damage size decreases limiting the ability to detect damage occurrence at the micron and submicron length scale. Damage detection at this length scale is of interest for sensitive structures such as aircrafts and nuclear facilities. In this paper a new photonic sensor based on photonic crystal (PhC) technology that can be synthesized at the nanoscale is introduced. PhCs are synthetic materials that are capable of controlling light propagation by creating a photonic bandgap where light is forbidden to propagate. The interesting feature of PhC is that its photonic signature is strongly tied to its microstructure periodicity. This study demonstrates that when a PhC sensor adhered to polymer substrate experiences micron or submicron damage, it will experience changes in its microstructural periodicity thereby creating a photonic signature that can be related to damage severity. This concept is validated here using a three-dimensional integrated numerical simulation.