• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.777-785
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• 2021

Many utility lines are buried underground to provide various functions of the city. Because historical records are not managed systematically, damage has occurred during excavation. In addition, the demand for an underground facility management system is increasing as the aerial underground project is progressing. By attaching an electronic recognition sensor to an underground facility, such as pipelines, the management history and site conditions can be carefully managed. Therefore, in this study, electronic recognition sensors, such as BLE Beacon, UHF RFID, geomagnetic sensor, and commercial marker, were tested to analyze the strengths, weaknesses, and field applicability through a pilot project. According to the limited research results collected through two pilot projects, the installation depth is most important to demonstrate the performance of the electronic reader. In addition, because it should be used in urban areas, the influence of environmental interference should be minimized, and there should be no performance degradation over time. In the case of the geomagnetic recognizer, the effect of environmental interference was large, and performance degradation occurred over time using the BLE Beacon. In the field situation, where the installation depth can be controlled to less than 40cm, the utility of the battery-free UHF RFID was the best.

• Korean Journal of Construction Engineering and Management
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• v.23 no.6
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• pp.111-118
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• 2022

Recently, as underground facilities buried under roads in Korea are aging, the amount of underground facility maintenance work is rapidly increasing. For the maintenance and management of such underground facilities, the cutting work of the road pavement should be preceded. However, the conventional road pavement cutters used in Korea are not eco-friendly, and the reality is that they generate a lot of noise and cutting sludge (scattering dust). Therefore, in this study, the concept of the cutting sludge recovery device was derived, and an eco-friendly pavement cutter including this function was designed and manufactured. The developed equipment took about 20 to 30 seconds to cut 1m to a depth of 100 to 150mm. Also, the sludge suction performance was good in most sections, and the noise level of the equipment briefly measured at a distance of 2m was 82.7dB on average. However, due to the limitation that the developed equipment was at the level of the first prototype, the driving stability was somewhat low, and equipment abnormalities such as engine shutdown and sludge recovery performance decreased in some cases. The cutting performance and sludge recovery function will be more stable through tuning and improvement of the developed prototype in the future. In addition, we plan to quantitatively compare and analyze productivity by applying the improved prototype to actual field conditions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.575-589
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• 2020

In recent years, Shield TBM construction has been continuously increasing in domestic tunnels. The main excavation tool in the shield TBM construction is a disc cutter which naturally wears during the excavation process and significantly degrades the excavation efficiency. Therefore, it is important to know the appropriate time of the disc cutter replacement. In this study, it is proposed a predictive model that can determine yes/no of disc cutter replacement using machine learning algorithm. To do this, the shield TBM machine data which is highly correlated to the disc cutter wears and the disc cutter replacement from the shield TBM field which is already constructed are used as the input data in the model. Also, the algorithms used in the study were the support vector machine, k-nearest neighbor algorithm, and decision tree algorithm are all classification methods used in machine learning. In order to construct an optimal predictive model and to evaluate the performance of the model, the classification performance evaluation index was compared and analyzed.