• Smart Structures and Systems
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• v.25 no.3
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• pp.265-277
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• 2020

Recently, the concept of "drive-by" bridge monitoring system using indirect measurements from a passing vehicle to extract key parameters of a bridge has been rapidly developed. As one of the most key parameters of a bridge, the natural frequency has been successfully extracted theoretically and in practice using indirect measurements. The frequency of bridge is generally calculated applying Fast Fourier Transform (FFT) directly. However, it has been demonstrated that with the increase in vehicle velocity, the estimated frequency resolution of FFT will be very low causing a great extracted error. Moreover, because of the low frequency resolution, it is hard to detect the frequency drop caused by any damages or degradation of the bridge structural integrity. This paper will introduce a new technique of bridge frequency extraction based on Hilbert Transform (HT) that is not restricted to frequency resolution and can, therefore, improve identification accuracy. In this paper, deriving from the vehicle response, the closed-form solution associated with bridge frequency removing the effect of vehicle velocity is discussed in the analytical study. Then a numerical Vehicle-Bridge Interaction (VBI) model with a quarter car model is adopted to demonstrate the proposed approach. Finally, factors that affect the proposed approach are studied, including vehicle velocity, signal noise, and road roughness profile.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.22-30
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• 2011

In the construction operation, foundation work should be done in advance for the building structure to be installed. This foundation work include a number of activities such as excavation, ground water prevention, piling, wale installation, etc. Caution should be taken in the operation because the dynamics of earth movement can cause a significant failure in the temporary structure. The temporary structure, therefore, should be constantly monitored to understand its behavior. This paper introduces the USN-based monitoring system to automatically identify the behavior of the temporary structure in addition to visual inspection. The autonomous capability of the monitoring system can increase the safety in the construction operation by providing the detailed structural changes of temporary structures.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.22-28
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• 1994

A data acquisition and processing system. using an IBM PC, an AD converter, and a printer, has been developed to monitor rapidly and significantly varying signals. The sister takes live signals and computes and displays the trend of the moving averages of the signals in real time. The system has been applied to monitor the shaft horsepower and revolution and the speed of ships for their speed trial. The reliable interpretation of the measured data using moving average can eliminate unnecessary arguments between the owner and yard on the performance of the newly built ships. Other applications of the system-inspection of engine hunting, providing data for ship maneuvering analysis, vibration data analysis, extending to the ship performance monitoring system-are also demonstrated and discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2145-2152
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• 2013

Paper manufacturing industries have huge facilities with automatic equipments. Especially, in order to improve the efficiency of the paper manufacturing processes, it is necessary to detect the paper cutting defect effectively and to classify the causes correctly. In this paper, we review the problems of web monitoring system and web inspection system that have been traditionally used in industries for defect detection. Then we propose a novel paper cutting defect detection method based on the local binary pattern analysis and its implementation to mitigate the practical problems in industry environment. The proposed algorithm classifies the defects into edge-type and region-type and then it is shown that the proposed system works stably on the real paper cutting defect detection system.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.26-31
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• 2022

Changwon City has the second highest accident rate with 79.6 according to the city bus accident rate. In fact, 250,000 people use the city bus a day in Changwon, The number of accidents is increasing gradually. In addition, a recent fire accident occurred in the engine room of a city bus (CNG) in Changwon, which has gradually expanded the public's anxiety. In the case of business vehicles, the government conducts inspections with a short inspection cycle for the purpose of periodic safety inspections, etc., but it is not in the monitoring stage. In the case of city buses, the operation records are monitored using Digital Tacho Graph (DTG). As such, driving records, methods, etc. are continuously monitored, but inspections are conducted every six months to ascertain the safety and performance of automobiles. It is difficult to identify real-time information on automobile safety. Therefore, in this study, individual automobile management solutions are presented through machine learning techniques of inspection results based on driving records or habits by linking DTG data and Vehicle Inspection Management System (VIMS) data for city buses in Changwon from 2019 to 2020.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.265-272
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• 2014

This study suggests a system for preventing and coping with diverse industrial accidents available for taking place in the industrial field by designing a context-aware system of the solar cell equipment with the use of multi-sensor. It installs multi-sensor in the surrounding and major positions of the solar cell equipment, acquires data on the surrounding situations and solar cell equipment from this device, and then save it into the local memory and transmits it to the server. The saved data recognizes a situation based on the context-aware algorithm and judges depending on the perceived result. An administrator comes to have environment available for monitoring the status on the production field and equipments with real time according to the judged outcome through the context-aware algorithm. The context-aware system in the industrial field, which is put today in the ubiquitous environment, will become a service of offering appropriate information for dealing with industrial accidents through real-time inspection.

• Composites Research
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• v.18 no.2
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• pp.46-51
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• 2005

An active inspection system using Lamb waves for structural health monitoring was considered in this paper. In order to understand the characteristics of the Lamb waves propagating in a composite plate, the experiment was performed for a quasi-isotropic composite plate with thickness variation. Lamb waves were generated and received by the thin PZT transducers bonded on the surface. In this test, a simple new technique was tried for characterizing the Lamb waves propagating across the discontinuity due to the thickness variation. The results showed that Lamb waves were more sensitive to the thinner plate with faster group velocity and that the thickness change in composite plate was detectable. Consequently, the potential of applying this technique to structural health monitoring was verified.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.6
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• pp.134-142
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• 2012

This paper presents a study of system identification on the tilt response of the L-type retaining wall located at Tanhyun 11th ACE Apartment, Ilsan in order to understand mechanism how the structure behaves in operational conditions and to provide a reference tilt values for assessing structural abnormality. The retaining wall was extraordinarily tall (14m) in urban area so the long-term monitoring system had been installed with 3 tilts-meters and 9 temperature sensors operational from Oct 2004 upto Nov 2007. By using 5-months continuous data in which all the 12 channels were up and running, the two prediction models, 1) the linear model, and 2) the state-space equation (SSE) model, have been identified by finding the best fitness model among all possible 511 combinations of input temperatures out of the 9 temperatures. The linear model which was simple in the model structure achieved the validation fittness of 68% due to the fact that the static model wasn't able to represent thermal dynamics. The SSE model achieved the validation fitness of 90% which was quite accurate considering various unexpected noises happening in field measurements.

• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• International Journal of Railway
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• v.1 no.1
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• pp.1-5
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• 2008

The railway system requires safety and reliability of service of all railway vehicles. Suitable technical systems and working methods adapted to it, which meet the requirements on safety and good order of traffic, should be maintained. For detection of defects, non-destructive testing methods-which should be quick, reliable and cost-effective - are most often used. Since failure in railway wheelset can cause a disaster, regular inspection of defects in wheels and axles are mandatory. Ultrasonic testing, acoustic emission and eddy current testing method and so on regularly check railway wheelset in service. However, it is difficult to detect a crack initiation clearly with ultrasonic testing due to noise echoes. It is necessary to develop a non-destructive technique that is superior to conventional NDT techniques in order to ensure the safety of railway wheelset. In the present paper, the new NDT technique is applied to the detection of surface defects for railway wheelset. To detect the defects for railway wheelset, the sensor for defect detection is optimized and the tests are carried out with respect to surface and internal defects each other. The results show that the surface crack depth of 1.5 mm in press fitted axle and internal crack in wheel could be detected by using the new method. The ICFPD method is useful to detect the defect that initiated in railway wheelset.