• Wind and Structures
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• v.37 no.5
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• pp.383-397
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• 2023

In the Structural Health Monitoring (SHM) system of civil engineering, data missing inevitably occurs during the data acquisition and transmission process, which brings great difficulties to data analysis and poses challenges to structural health monitoring. In this paper, Convolution Neural Network (CNN) is used to recover the nonstationary wind speed data missing randomly at sampling points. Given the technical constraints and financial implications, field monitoring data samples are often insufficient to train a deep learning model for the task at hand. Thus, simulation combined transfer learning strategy is proposed to address issues of overfitting and instability of the deep learning model caused by the paucity of training samples. According to a portion of target data samples, a substantial quantity of simulated data consistent with the characteristics of target data can be obtained by nonstationary wind-field simulation and are subsequently deployed for training an auxiliary CNN model. Afterwards, parameters of the pretrained auxiliary model are transferred to the target model as initial parameters, greatly enhancing training efficiency for the target task. Simulation synergy strategy effectively promotes the accuracy and stability of the target model to a great extent. Finally, the structural dynamic response analysis verifies the efficiency of the simulation synergy strategy.

• Atmosphere
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• v.15 no.1
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• pp.59-68
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• 2005

United Nations Development Programme (UNDP) introduced the Adaptation Policy Framework (APF) to support the developing countries in order to help to make adaptation policy and strategy to climate change. This study provides the summary of the APF and will help for preparing policy regarding the impact of climate change and its adaptation. APF consists of five basic and two cross-cutting steps. Five basic steps are made of (a) defining project scope and design, (b) assessing current vulnerability and adaptation, (c) assessing future climate-related risks, (d) developing an adaptation strategy, and (e) continuing the adaptation process. Cross-cutting steps consist of engaging stakeholder and enhancing adaptive capacity. The project scope and design process includes four major tasks: scope the project and define its objectives, establish the project team, review and synthesize existing information on vulnerability and adaptation, and design the APF project. The main purpose of assessing current vulnerability and adaptation is to understand the characteristics of current climate-related vulnerability in priority systems and the scope of adaptive responses. Future climate-related risks are assessed in order to characterize future climate-related risks, so that adaptation policies and measures can be designed to reduce the system's exposure to future climate hazard. In developing an adaptation strategy, all of the preceding APF-related work is synthesized into a well-considered strategy that can direct real adaptation action. Continuing the adaptation process is in order to implement and sustain the APF-strategy, polices, and measure. The purpose of involvement of stakeholders is to communicate between individuals and groups about projects. Finally, enhancing adaptive capacity provides guidance on how adaptive capacity can be assessed and enhanced.

• Journal of the Korean Dietetic Association
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• v.19 no.3
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• pp.253-264
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• 2013

The principal objective of this study was to examine the quality characteristics of yanggaeng supplemented with powder derived from Sanghwang mushroom (Phellinus linteus) mycelia. We analyzed the potential of utilizing Phellinus linteus mycelia as a functional food material by estimating total polyphenol and flavonoid contents, electron-donating abilities, as well as antioxidative activities of the water and ethanol extracts of Sanghwang mushroom mycelia. The total phenol and flavonoid contents of ethanol extracts from Phellinus linteus mycelia were 0.69 mg/ml and 0.16 mg/ml, respectively, while the contents from the water extract of Phellinus linteus mycelia were 0.66 mg/ml and 0.22 mg/ml, respectively. The electron-donating abilities of ethanol and water extracts from Phellinus linteus mycelia were 88.64 and 90.29%, respectively. The ABTS radical scavenging activities of ethanol and water extracts from Phellinus linteus mycelia were 89.74 and 71.35%, respectively. In terms of color values, as the level of powder increased, the value of L (lightness) decreased, whereas those of a (redness) and b (yellowness) increased. In regard to the mechanical properties of the samples, we noted significant differences in hardness, springiness, chewiness, and gumminess (P<0.05). The results of the sensory evaluation showed that the score from SHM (Sanghwang mushroom mycelia) with 4% powder was significantly higher than other samples in terms of sweetness, color, taste, texture and overall quality (P<0.05). Taken together, the recommended level of Phellinus linteus mycelia powder in yanggaeng is 4% for optimal sensory characteristics.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.315-333
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• 2016

This study aims to perform damage identification for Da-Sheng-Guan (DSG) high-speed railway truss arch bridge using fuzzy clustering analysis. Firstly, structural health monitoring (SHM) system is established for the DSG Bridge. Long-term field monitoring strain data in 8 different cases caused by high-speed trains are taken as classification reference for other unknown cases. And finite element model (FEM) of DSG Bridge is established to simulate damage cases of the bridge. Then, effectiveness of one fuzzy clustering analysis method named transitive closure method and FEM results are verified using the monitoring strain data. Three standardization methods at the first step of fuzzy clustering transitive closure method are compared: extreme difference method, maximum method and non-standard method. At last, the fuzzy clustering method is taken to identify damage with different degrees and different locations. The results show that: non-standard method is the best for the data with the same dimension at the first step of fuzzy clustering analysis. Clustering result is the best when 8 carriage and 16 carriage train in the same line are in a category. For DSG Bridge, the damage is identified when the strain mode change caused by damage is more significant than it caused by different carriages. The corresponding critical damage degree called damage threshold varies with damage location and reduces with the increase of damage locations.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.241-247
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• 2015

Deflection and deformation occur easily in structures with long length, such as bridges and pipelines. Shape monitoring is required for ensuring their structural health. A fiber Bragg grating (FBG) sensor can be used for monitoring a large-scale structure because of its advantage of multiplexing. In this study, FBG sensors were used for monitoring a composite beam structure, and its strains were measured at multiple points. Thereafter, a shape estimation technique based on the strains was studied. Particularly, a three-dimensional shape estimation technique was proposed for accurate structural health monitoring. A simple experiment was conducted to verify the performance of the shape estimation technique. The result revealed that the estimated shape of the composite beam structure was in agreement with the actual shape obtained after the deformation of the specimen. Additionally, the deflection at a specific point was verified by comparing the estimated and actual deformations measured using a micrometer.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.68-72
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• 2015

Ultrasonic inspection robot systems have been widely researched and developed for the real-time monitoring of structures such as power plants. However, an inspection robot that is operated in a simple pattern has limitations in its application to various structures in a plant facility because of the diverse and complicated shapes of the inspection objects. Therefore, accurate control of the robot is required to inspect complicated objects with high-precision results. This paper presents the idea that the shape and movement information of an ultrasonic inspector's hand could be profitably utilized for the accurate control of robot. In this study, a polymer flex sensor was applied to monitor the shape of a human hand. This application was designed to intuitively control an ultrasonic inspection robot. The movement and shape of the hand were estimated by applying multiple sensors. Moreover, it was successfully shown that a test robot could be intuitively controlled based on the shape of a human hand estimated using polymer flex sensors.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.39-45
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• 2015

Applications of smart sensors have been extended to safety systems in the aerospace, transportation and civil engineering fields. In particular, structural health monitoring techniques using smart sensors have gradually become necessary and have been developed to prevent dangers to human life and damage to assets. Generally, smart sensors are based on electro-magnets and have several weaknesses, including electro-magnetic interference and distortion. Therefore, fiber optic sensors are an outstanding alternative to overcome the weaknesses of electro-magnetic sensors. However, they require expensive devices and complex systems. This paper proposes a new, affordable and simple sensor system that uses a single fiber to monitor pressures at multiple-points. Moreover, a prototype of the sensor system was manufactured and tested for a feasibility study. Based on the results of this experimental test, a relationship was carefully observed between the bend loss conditions and light-intensity. As a result, it was shown that impacts at multiple-points could be monitored.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.5
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• pp.362-368
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• 2014

Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the musle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.