• 한국정밀공학회지
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• 제17권9호
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• pp.32-38
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• 2000

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.124-132
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• 2001

Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2006년 추계학술발표대회 개요집
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• pp.101-103
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• 2006

DSME has developed Sub-assembly Welding Robot System(SWRS) in order to increase the productivity of arc welding and to improve hazard and unclean environments in shipbuilding. DSME's SWRS includes a number of equipments such as four overhanging 6-axis articulated robot manipulators(10kg pay-load), gantry system, vision system detecting the workpiece automatically, and OLP system using the CAD data and a central control system integrating an anti-collision module. The SWRS was installed in CAS(Component Assembly Shop) of DSME's OKPO shipyard in August 2006, and now SWRS is running well in site.

• 한국산업보건학회지
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• 제28권2호
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• pp.200-210
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• 2018

Objectives: The purpose of this study is to assess the exposure to ozone and total volatile organic compounds(TVOCs) generated during welding work at a shipyard and recommend respiratory protective equipment(RPE) adequate against these hazards. Method: Ozone was collected for about 30 minutes at two-minutes intervals using a direct reading instrument, specifically an ozone analyzer(Serinus 10, Ecotech, Australia). TVOCs were collected for about 30 minutes at three-minute intervals using a portable GC (Alpha 115, Synspec BV, the Netherlands), and were determined simultaneously by area sampling at the welding plume closest to the welder's breathing zone. The total measurements were 162 for ozone($CO_2$ welding 47, TIG 60, stick 55), and 136 for TVOCs($CO_2$ 65, TIG 50, stick 21). Based on these measurements, a literature survey was conducted to assess the adequacy of RPE. Results: Relative to Korean OEL, measurements above STEL 0.2 ppm were 23.4% for $CO_2$, 63.3% for TIG and 14.5% for stick welding. There were significant differences(p=<0.0001) among welding types. Compared with ACGIH peak exposure of 0.4 ppm for ozone, which is not applied in Korea, $CO_2$ welding exceeded it by 10.6%, TIG by 40.0% and stick by 7.3%. Although it was not feasible to compare them directly since there are no Korean OEL, TVOCs had very high levels similar to the concentrations before moving into a new apartment and about 10-20 times the indoor air quality recommendations for some individual measurements. Conclusions: As ozone removal RPE has been recommended in welding environments for a long time(Lunau, 1967), this fact was demonstrated based on the results of the on-site work environment measurements(ozone and TVOCs). In conclusion, for all welding at a shipyard, gas/vapor and particulate combination RPE are recommended. If this is not possible, it should at least be present for TIG welding.

• 제어로봇시스템학회논문지
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• 제8권9호
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• pp.776-787
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• 2002

Automation of welding process in shipyards is ultimately necessary, since the welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding mobile robot that can navigate autonomously within the enclosure has been developed. To achieve the welding task in the closed space, the robotic welding system needs a sensor system for the working environment recognition and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with 3D work environmental map. Using this sensor system, a spatial filter based on neural network technology is designed for extracting the center of laser stripe, and evaluated in various situations. An environment modeling algorithm structure is proposed and tested, which is composed of the laser scanning module for 3D voxel modeling and the plane reconstruction module for mobile robot localization. Finally, an environmental recognition strategy for welding mobile robot is developed in order to recognize the work environments efficiently. The design of the sensor system, the algorithm for sensing the partially structured environment with plane segments, and the recognition strategy and tactics for sensing the work environment are described and discussed with a series of experiments in detail.