• Smart Structures and Systems
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• v.11 no.4
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• pp.331-348
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• 2013

Effective monitoring, reliable data analysis, and rational data interpretations are challenges for engineers who are specialized in bridge health monitoring. This paper demonstrates how to use the Global Positioning System (GPS) and accelerometer data to accurately extract static and quasi-static displacements of the bridge induced by ambient effects. To eliminate the disadvantages of the two separate units, based on the characteristics of the bias terms derived from the GPS and accelerometer respectively, a wavelet based multi-step filtering method by combining the merits of the continuous wavelet transform (CWT) with the discrete stationary wavelet transform (SWT) is proposed so as to address the GPS deformation monitoring application more efficiently. The field measurements are carried out on an existing suspension bridge under the normal operation without any traffic interference. Experimental results showed that the frequencies and absolute displacements of the bridge can be accurate extracted by the proposed method. The integration of GPS and accelerometer can be used as a reliable tool to characterize the dynamic behavior of large structures such as suspension bridges undergoing environmental loads.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.415-426
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• 1997

Some arguments have been about over the representativeness of government-run air quality monitoring stations among scholars and non-governmental organizations (NGOs). However, it is not a simple problem to move monitoring stations because of continuity of data and high cost. So it is necessary to complement the monitoring data if it do not represent the ambient air quality properly. The purpose of this study was to evaluate the representativeness of some monitoring stations using passive $NO_2$ samplers and to find a complementary method from linear regression. Two stations were chosen for the evaluation: Shinlim Station was one of the most controversial stations in Seoul and Banpo Station had the best reputation. Air qualities were surveyed at seven points around each monitoring station with consideration of land use and distance. The ratios of the average $NO_2$ levels of the areas to these at the monitoring stations were 1.59 for Shinlim Station and 1.03 for Banpo Station. The differences between the average $NO_2$ levels and those at the monitoring stations were 10.75 ppb for Shilim Station and 0.34 ppb for Banpo Station. The correlation coefficients between the two levels were 0.7668 for Shinlim and 0.7662 for Banpo. The average coefficients of determination $(R^2)$ were 0.61 for Shinlim and 0.61 for Banpo. The Shinlim Station could not represent the air quality of Shinlim-Dong good because it is located in a green area at an outskirt of Shinlim-Dong. But the Banpo Station located in a central residential area of Banpo-Dong showed a fair representativeness. However, air quality turned out to be different with land use such as residential area, green area or road: the air quality data from a monitoring station located at a certain land use should not be interpreted as representing the air quality at any sites around the station. Equations to predict the average $NO_2$ levels of each area from the data from the monitoring stations were presented based on linear regression.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.218-225
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• 2000

This paper presents intermediate results of an on-going research for identification of the modal and the stiffness parameters of a bridge based on the ambient vibration data caused by the traffic loadings. The main algorithms consist of the random decrement method incorporating band-pass filters for estimation of the free vibration signals the cross spectral density method for identification of the modal parameters and the neural networks technique for estimation of the element-level stiffness changes. An experimental study is carried out on a scaled bridge model with a composite section subjected to various moving vehicle loadings. Vertical accelerations are measured at several locations on the girder. The estimated frequencies and mode shapes are found to be well-compared with those obtained from the impact tests. The estimated stiffness changes using the neural networks are found to be very good for the case with the simulated data. However the accuracy is found to be not quite satisfactory for the case with the experimental data particularly for the small value of the stiffness changes.

• Journal of Environmental Science International
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• v.3 no.4
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• pp.357-365
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• 1994

Air pollution characteristics and the influence of sea breeze on air pollution concentration were studied using the data measured at 7 air quality continuous monitoring stations in Pusan, 1993. Maximum air pollution concentration in Pusan was Gamjeondong for $SO_2$, Sinpyeongdong for TSP, Daeyeondong for $O_3, Kwangbokdong for $NO_2$, Beomcheondong for CO and all substances were under annual ambient air quality standards. Increased rate of concentration for sea breeze was 24.4% for 502, 31.5% for TSP, 8.0% fort $O_3, 26.7% for $NO_2$, 15.7% for CO. Frequencies distribution of $SO_2$, TSP, $O_3$, $NO_2$, and CO concentration for sea breeze moved toward high concentration class.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• BMB Reports
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• v.35 no.4
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• pp.384-388
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• 2002

A method for the ratiometric pH sensing using LysoSensor DND-192 is presented in this paper. It works in the physiological pH range. It is based on the use of two fluorophores which differ significantly in their lifetimes. As the discrimination of their emissions is performed through two different frequencies, this method can allow significant overlap of the emission spectra. A simple long-pass filter, or a combination of long-and short-pass filters, was used instead of narrow-bandpass devices. Importantly, the measurements were carried out under strong ambient light. The method could be used in a wide variety of applications, such as intracellular measurements, microscopy, bioprocess monitoring, etc.

• Journal of Biosystems Engineering
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• v.36 no.4
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• pp.279-284
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• 2011

Protected vegetable production area is greater than 26% of the total vegetable production area in Korea, and portion of protected production area is increasing for flowers and fruits. To secure stable productivity and profitability, continuous and intensive monitoring and control of protected crop production environment is critical, which is labor- and time-consuming. Failure to maintain proper environmental conditions (e.g., light, temperature, humidity) leads to significant damage to crop growth and quality, therefore farmers should visit or be present close to the production area. To overcome these problems, application of remote monitoring and control of crop production environment has been increasing. Wireless monitoring and control systems have used CDMA, internet, and smart phone communications. Levels of technology adoption are different for farmers' needs for their cropping systems. In this paper, potential of wireless remote monitoring of protected agricultural environment using CDMA SMS text messages was reported. Monitoring variables were outside weather (precipitation, wind direction and velocity, temperature, and humidity), inside ambient condition (temperature, humidity, $CO_2$ level, and light intensity), irrigation status (irrigation flow rate and pressure), and soil condition (volumetric water content and matric potential). Scenarios and data formats for environment monitoring were devised, tested, and compared. Results of this study would provide useful information for adoption of wireless remote monitoring techniques by farmers.

• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.680-688
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• 2017

Water quality monitoring for flow rates and BOD/COD/T-N/T-P/SS/TOC concentrations has been conducted in Nakdong river tributaries since 2011. In this study concentrations and loading rates of BOD, T-P, and TOC were analyzed to evaluate water quality monitoring stations using accumulated data at 206 tributary monitoring stations in Nakdong river 2012 ~ 2016. Average concentration ranges for 206 monitoring stations were 0.3 ~ 6.4 mg/L, 0.025 ~ 1.562 mg/L, and 0.6 ~ 10.7 mg/L for BOD, T-P, and TOC, respectively. Additionally, average loading rate ranges were 0.96 ~ 46,040 kg/d, 0.087 ~ 1,834 kg/d, and 1.51 ~ 80,425 kg/d for BOD, T-P, and TOC, respectively. Average concentration for BOD, T-P, and TOC at each monitoring station was evaluated using ambient water quality standards of rivers and water quality regulation level for medium-sized management areas. Average loading rate and specific loading rate (loading rate/drainage basin area) for BOD, T-P, and TOC at each monitoring station was considered to evaluate monitoring stations using suggested classification (BOD, TOC: -1, 1 ~ 10, 10 ~ 100, 100 ~ 1,000, and 1,000 ~ kg/d; T-P: -0.1. 0.1 ~ 1, 1 ~ 10, 10 ~ 100, and 100 ~ kg/d) Using results of this study, various water quality status maps were provided, and three evaluation methods were suggested to determine priority monitoring stations in Nakdong river for rational water quality control and tributaries basin management.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.751-760
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• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.6
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• pp.661-668
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• 2012

Wireless sensor network is one of prospective methods for railway monitoring due to the long-term operation and low-maintenance performances. How to supply power to the wireless sensor nodes has drawn much attention recently. In railway monitoring, the idea of converting ambient vibration energy from vibration of railway track induced by passing trains to electric energy has made it a potential way for powering the wireless sensor nodes. In this paper, a bimorph cantilever piezoelectric energy harvester was designed based on a single degree-of-freedom model. Experimental test was also performed to validate the design. The first natural frequency of the bimorph piezoelectric energy harvester was decreased from 117.1 Hz to 65.2 Hz by adding 4 gram tip mass to the free end of the 8.6 gram energy harvester. In addition, the power generation of the piezoelectric energy harvester with 4 gram tip mass at resonant frequency was increased from 0.14 mW to 0.74 mW from $2.06m/s^2$ base excitation compared to stand-alone piezoelectric energy harvester without tip mass.