• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.293-294
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• 2012

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1335-1341
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• 2011

Conserving clean air and removing contaminants and particular matters accumulated in the ventilation system of the subway stations are key issue for green railway environment. There is no national guideline or industrial regulations to sustain clean duct and ventilation system, which requires rapid reformation of cleaning procedure and system. In fact, accumulated various particular matters and dusts can occur secondary air contamination and become a primary health harm factor for subway passengers. This study investigates various duct cleaning technologies and trends. In additon, effective cleaning method with an automated robot device is proposed. In particular, current dust cleaning technologies and duct cleaning robots are analyzed based on their functions and feasibilities. The proposed design of automated device is expected to save the operating cost of subway HVAC system and sustain clean air environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.85-95
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• 2019

This work shows how to design a robot structure and to control to overcome obstacles while traveling through ducts of various diameters and shapes by three-legged robot. Circuits are centered in the body to connect the three wheel bodies that are driven around the center body with the 4-section slider link structure. Also, the springs are used to contract and expand the robot legs so that it can be caparable of various environments. Geared motor, spring, and belt were selected based on the static and dynamic calculation to be suitable to horizontal and vertical travels. The center body is equipped with a camera and the distance sensors, and a control algorithms are implemented so that it can be successfully performed in L-type and T-type ducts. Using UWB modules and trilateration algorithm, the location of the duct-cleaning robot inside the duct could be identified successfully.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.