• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.511-523
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• 2023

Research on the integration of unmanned aerial vehicles and deep learning for reinforced concrete damage detection is actively underway. Convolutional neural networks have a high impact on the performance of image classification, detection, and segmentation as backbones. The MobileNet, a pre-trained convolutional neural network, is efficient as a backbone for an unmanned aerial vehicle-based damage detection model because it can achieve sufficient accuracy with low computational complexity. Analyzing vanilla convolutional neural networks and MobileNet under various conditions, MobileNet was evaluated to have a verification accuracy 6.0~9.0% higher than vanilla convolutional neural networks with 15.9~22.9% lower computational complexity. MobileNetV2, MobileNetV3Large and MobileNetV3Small showed almost identical maximum verification accuracy, and the optimal conditions for MobileNet's reinforced concrete damage image feature extraction were analyzed to be the optimizer RMSprop, no dropout, and average pooling. The maximum validation accuracy of 75.49% for 7 types of damage detection based on MobilenetV2 derived in this study can be improved by image accumulation and continuous learning.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.3
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• pp.171-177
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• 2011

The feasibility of using low cost, unpowered, unshielded dynamic microphones is investigated for cost effective contactless sensing of impact-echo signals in concrete structures. Impact-echo tests on a delaminated concrete slab specimen were conducted and the results were used to assess the damage detection capability of the low cost system. Results showed that the dynamic microphone successfully captured impact-echo signals with a contactless manner and the delaminations in concrete structures were clearly detected as good as expensive high-end air pressure sensor based non-contact impact-echo testing.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.393-396
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• 2022

Recently, rapid climate change has had a significant impact on the ecosystem of honeybees. In addition, the problem of Vespa Hornets invasion of colonies has a fatal impact on the bee ecosystem, independent of climate change. Especially in late summer. This study relates to a method for preventing Vespa Hornets attack. In this study, we developed a Vespa Hornets sound detection device was developed by collecting and analyzing the sound of a Vespa Hornets and applying IoT technology. The developed device detects the sound of a Vespa Hornets when Vespa Hornets appears around the hive of the bees and sends a signal to automatically close the door of the beehive. The device that receives the signal drives the motor that controls the honeycomb door to close the beehive door. The Vespa Hornets sound detection device operates until no Vespa Hornets sound is detected. The system developed by us is expected to be installed in the beehives of actual beekeeping farms to dramatically reduce the damage caused by by Vespa Hornets.

• Smart Structures and Systems
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• v.18 no.6
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• pp.1189-1202
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• 2016

This paper describes an application of wavelet analysis for damage detection of a steel frame structure with bolted connections. The wavelet coefficients of the acceleration response for the healthy and loosened connection structure were calculated at each measurement point. The difference of the wavelet coefficients of the response of the healthy and loosened connection structure is selected as an indicator of the damage. At each node of structure the norm of the difference of the wavelet coefficients matrix is then calculated. The point for which the norm has the higher value is a candidate for location of the damage. The above procedure was experimentally verified on a laboratory-scale 2-meter-long steel frame. The structure consists of 11 steel beams forming a four-bay frame, which is subjected to impact loads using a modal hammer. The accelerations are measured at 20 different locations on the frame, including joints and beam elements. Two states of the structure are considered: healthy and damaged one. The damage is introduced by means of loosening two out of three bolts at one of the frame connections. Calculating the norm of the difference of the wavelet coefficients matrix at each node the higher value was found to be at the same location where the bolts were loosened. The presented experiment showed the effectiveness of the wavelet approach to damage detection of frame structures assembled using bolted connections.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.11
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• pp.1089-1095
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• 2009

The radiated sound pressure induced by tapping test is obtained by solving the Rayleigh integral equation. For structurally radiated sound, the sound field is directly coupled to the structural motion. Therefore the impact response should be analyzed. In this paper, the delamination model is used to analyze the impact response of delaminated composite laminates. And efficient spring-mass model has been proposed to model hammer shaped impactor. Predicted sound pressure histories are compared with test data. The influence of damage on the sound pressure and impacted force history of laminates were investigated. The results show that both radiated sound pressure and impact force history are strongly influenced by delamination on laminates. As a result, it is shown that the presented sound based tapping method was found to be reliable for detecting the damage in composite laminate.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.9-16
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• 2018

The purpose of this study is to prevent the malicious user from breaking the door-lock due to physical impact. If it matches the analog displacement value set in the door-lock system, it protects the body and property by transmitting damage information in real time to the manager smart phone. The research suggests a system that transmits damage information in real time to registered users when door-lock is damaged by physical impact. Then compare the impact information sensed by the door lock with the data of the sensitivity control unit. In the web server of the proposed system, after impact information transmitted from Door-Lock is stored in the DB, if the impact information is larger than the shock detection transmission reference value stored in the DB, it is transmitted to the administrator in real time by SMS module so that illegal access information.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.636-637
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• 2010

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.243-248
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• 1999

From the lessons after the Nakhodka oil-spill in Jan. 1997, oil slick detection by using remote sensing data and assimilating the data to the simulation program is important for monitoring the oil-drift pattern. For this object, we are going to construct the oil-spill warning system for estimating the oil-drift pattern using remotesensing/numerical simulation Model. Additionally we plan to use this system for restorating oil-spill damage domestically, such as estimating the ecological damage and making the priority fur restorating the oil-spilled shoreline. This report is intended to summarize the role of geo-informatics in the oil spill accident by not only paying attention to the effect of information provision/information management via the map, but also reporting the interim result in part based on the details discussed in the processes of recovery support and environmental impact assessment during the Nakhodka's accident.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.9 s.102
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• pp.1108-1117
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• 2005

A robust damage detection method using short-time Fourier transform and beating phenomena is presented as an estimating tool of the healthiness of large structures. The present technique makes use of beating phenomena that manifest themselves when two signals of similar frequencies are added or subtracted. Unlike most existing methods based on vibration signals, the present approach does not require an analytic model for target structures. Furthermore, the main advantage of the proposed method compared to the competing diagnostic method using vibration data is its robustness. The proposed method is not affected by the amplitude of exciting signals and the location of exciting points. From a measuring view point. the location of sensing point have no influence on the performance of the present method. With a view to verifying the effectiveness of this method. a series of experiments are made and the results show its possibility as a robust damage diagnostic method.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.731-748
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• 2010

Impact detection and health monitoring are very important tasks for civil infrastructures, such as bridges. Piezoceramic based transducers are widely researched for these tasks due to the piezoceramic material's inherent advantages of dual sensing and actuation ability, which enables the active sensing method for structural health monitoring with a network of piezoceramic transducers. Wireless sensor networks, which are easy for deployment, have great potential in health monitoring systems for large civil infrastructures to identify early-age damages. However, most commercial wireless sensor networks are general purpose and may not be optimized for a network of piezoceramic based transducers. Wireless networks of piezoceramic transducers for active sensing have special requirements, such as relatively high sampling rate (at a few-thousand Hz), incorporation of an amplifier for the piezoceramic element for actuation, and low energy consumption for actuation. In this paper, a wireless network is specially designed for piezoceramic transducers to implement impact detection and active sensing for structural health monitoring. A power efficient embedded system is designed to form the wireless sensor network that is capable of high sampling rate. A 32 bit RISC wireless microcontroller is chosen as the main processor. Detailed design of the hardware system and software system of the wireless sensor network is presented in this paper. To verify the functionality of the wireless sensor network, it is deployed on a two-story concrete frame with embedded piezoceramic transducers, and the active sensing property of piezoceramic material is used to detect the damage in the structure. Experimental results show that the wireless sensor network can effectively implement active sensing and impact detection with high sampling rate while maintaining low power consumption by performing offline data processing and minimizing wireless communication.