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조정호,이중재,배승환,이용기,박경배,김용준,이준경,Cho, Jungho,Lee, Jungjae,Bae, Seunghwan,Lee, Yongki,Park, Kyungbae,Kim, Yongjun,Lee, Junkyung 대한용접접합학회 2015 대한용접·접합학회지 Vol.33 No.2
Cleaning effect is well known mechanism of oxide layer removal in DCEP polarity. It is also known that DCEN has higher heat input efficiency than DCEP in GTAW process. Based on these two renowned arc theories, conventional variable polarity arc for aluminum welding was set up to have minimum DCEP and maximum DCEN duty ratio to achieve the highest heat input efficiency and weldability increase. However, recent several variable polarity GTA research papers reported unexpected result of proportional relationship between DCEP duty ratio and heat input. The authors also observed the same result then suggested combination of tunneling effect and random walk of cathode spot to fill up the gap between experiment and conventional arc theory. In this research, suggested combinational work of tunneling effect and rapid cathode spot changing is applied to another unexpected phenomena of variable polarity aluminum arc welding. From previous research, it is reported that wider oxide removal range, narrower bead width and shallower penetration depth are observed in thin oxide layered aluminum compared to the case of thick oxide. This result was reported for the first time and it was hard to explain the reason at that time therefore the inference by the authors was hardly acceptable. However, the suggested combinational theory successfully explains the result of the previous report in logical way.
조정호,이중재,배승환,이용기,박경배,김용준,문세민,Cho, Jungho,Lee, Jungjae,Bae, Seunghwan,Lee, Yongki,Park, Kyungbae,Kim, Yongjun,Moon, Semin 대한용접접합학회 2015 대한용접·접합학회지 Vol.33 No.2
The importance of emotional quality of car is getting higher in these days. Noise takes great portion in emotional quality because it is detectable problem with just a few rides. The sources of car noise during operation are various and the related technical issues are vast. Sometimes weldments of auto body are referred as the source of noise and the suspicious weldment shows unsatisfactory welding quality in most cases. In this research, cases of noise making weldments are investigated to figure out the solution for welding quality improvement. They are categorized into several groups in according to the inferred types of the error source then appropriate solutions are suggested. Auto body has weldments of resistance spot welding and gas metal arc welding in general. Therefore the solutions are suggested as adjustment of welding process variables and related machineries. Inevitable error source is also referred which is originated from thermal expansion rate difference between ultra high strength steel and mild steel. This new approach is validated through simple calculation then more concrete investigation with numerical analysis is remained as further works to be done.
신경망 알고리즘을 이용한 차체용 강판 아크 용접 조건 도출
조정호,Cho, Jungho 대한용접접합학회 2014 대한용접·접합학회지 Vol.32 No.2
Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.
조정호,Cho, Jungho 대한용접접합학회 2014 대한용접·접합학회지 Vol.32 No.1
Low arc weldability of aluminum alloy is enhanced by applying variable polarity TIG and the result is theoretically investigated to figure out the mechanism. Conventionally, it is well known fact that DCEP (reverse polarity) arc is effective on aluminum welding. The reason is due to oxide layer removal by plasma ion bombardment and therefore it is named as cleaning effect. Another fact of polarity characteristic is that DCEN shows higher heat input efficiency therefore conventional variable polarity arc used to apply DCEP portion as small as possible. However, higher DCEP portion shows bigger weldment in this research and it is explained by adopting a theory of arc concentration on oxide layer with tunneling effect which was not clearly mentioned before in several variable polarity TIG welding research. Disagreement between variable polarity TIG welding result and conventional arc polarity theory is rationally explained for the first time with help of electron emission theory.
조정호,Cho, Jungho 대한용접접합학회 2013 대한용접·접합학회지 Vol.31 No.3
Artificial neural network (ANN) model is applied to predict arc welding process window for automotive steel plate. Target weldment was various automotive steel plate combination with lap fillet joint. The accuracy of prediction was evaluated through comparison experimental result to ANN simulation. The effect of ANN variables on the accuracy is investigated such as number of hidden layers, perceptrons and transfer function type. A static back propagation model is established and tested. The result shows comparatively accurate predictability of the suggested ANN model. However, it restricts to use nonlinear transfer function instead of linear type and suggests only one single hidden layer rather than multiple ones to get better accuracy. In addition to this, obvious fact is affirmed again that the more perceptrons guarantee the better accuracy under the precondition that there are enough experimental database to train the neural network.
한국 국방 연구개발 프로젝트 일정 관리 및 예측을 위한 Earned Schedule 기법의 적용 효과와 한계 분석
조정호,임재성,Cho, Jungho,Lim, Jaesung 한국군사과학기술학회 2018 한국군사과학기술학회지 Vol.21 No.3
Earned Value Management(EVM) has been used to manage and forecast defense project schedule and cost over the last two decades in the world. However to support the lacking ability of schedule analysis in traditional EVM, earned schedule(ES) has been introduced as a tool to more accurately estimate schedule performance. This paper compares which method EVM or ES, provides more accurate schedule predictors in 32 Korean defense research and development projects. As a result of comparison, the ES method can predict the future schedule more reliably than the EVM method. We also analyze early warning function of schedule performance index considering project duration extension point. Through the analysis results, we confirm that both the EVM and the ES method lack the ability of the early warning in terms of the current schedule management criterion.