The railroad facilities are intended for long-term operation as the initial acquisition costs necessary for infrastructure construction are high. Therefore, regular maintenance of railroad facilities is essential, and furthermore, system reliability through systematic performance evaluation is required. In this study, the signal control system of railroad electrical equipment was selected as the subject of research and the performance evaluation target facility selection study was conducted using AHP. The results of the study can contribute to the reliability of the signal control system as well as to the reliability of the railroad system, which is a higher system.

수경재배 시스템에서 이온선택성전극(ISE)를 이용하여 배액 내 칼륨, 칼슘, 질소 이온농도를 측정하고 배양액 조제알고리즘을 통해 부족농도를 보충하는 시스템을 개발하였다. 또한, ISE로 실시간 측정이 어려운 다량원소 중 미측정 이온에 대한 농도는 배액 내 다량원소 간 상관관계를 통해 예측하였다. 회수된 배액을 재사용하기 위해서는 배액의 이온농도 측정도 중요하지만 부족한 양을 어떻게 정확하게 공급해 줄 것인지도 중요하다. 부족 농도를 보충하기 위해 비료농축액을 사용하였으며, 회수된 배액 내 미측정된 다량원소 이온들의 농도를 예측하기 위해 상추 재배실험 을 통해 이온 크로마토그래피로 측정한 다량원소 간 관계를 분석하였다. PO4의 경우 전극을 이용하여 측정 가능한 다량원소 간의 상관관계는 결정계수 K=0.91, NO3=0.96, Ca=0.87로 모두 높은 관계를 나타내었다. 이 중 결정계수가 가장 높은 질산을 조제 알고리즘에 사용하였다. Mg의 경우 K=0.93, NO3=0.93, Ca=0.99로 셋 중 Ca와 가장 밀접한 관계를 보여 Ca를 조제 알고리즘에 사용하였다. SO4의 경우 K=0.86, NO3=0.97, Ca=0.95를 나타냈으며 결정계수가 가장 높은 NO3를 알고리즘에 적용하여 양액을 조제 하려고 했으나 해당 비료의 과잉공급이 발생하게 되어 Ca을 적용하여 양액을 조제 하였다. 알고리즘을 이용하여 조제한 결과 전체적으로 10% 내의 오차로 나타났지만 비료농축액 공급량 결정 시 투입되는 비료를 순차적으로 결정할 뿐만 아니라 특정 이온의 과잉 또는 부족 농도가 최소화될 수 있는 방향으로 알고리즘을 만들었기 때문에 NO3과 SO4에 대한 공급오차는 발생할 수밖에 없었다. 개발된 시스템의 성능을 평가하고자 재배실험에서 나온 배액과 제조된 양액을 비교하였고 K, Ca, NO3의 공급오차는 평균 ±10%내를 보여 예상치보다 다소 많은 오차를 보였지만 회수된 배액을 재조제하여 공급하였을 때 실제 작물재배에서 목표 농도를 유지할 수 있을 것으로 보였다. 하지만 보다 정밀한 제어를 위해 상추 생육단계별 이온흡수량 데이터베이스를 구축하여 조제알고리즘에 적용시켜 배양액을 공급할 수 있는 연구가 필요하다고 판단되었다.

In this study, a motion control problem for the vessel towed by towing ship on the sea is considered. The towed vessel does not have self-control capabilities such that its course stability totally depends on the towing ship. Especially, in the narrow canal, river and congested harbor area, extreme tension is required during the towing operation. The authors, therefore, propose a new control system design method in which the rudder is activated to provide its maneuverability. Based on the leader following system configuration, a nonlinear mathematical model is derived and a backstepping control is designed. By experiment results with nonlinear control framework, the usefulness and effectiveness of the proposed strategy are presented.

This study was conducted to provide a basis for raising farm income by increasing the yield and extending the cultivation period by creating an environment where crops can be cultivated normally during high temperatures in summer. The maximum cooling load of the multi-span greenhouse with a floor area of 504 m2 was found to be 462,609 W, and keeping the greenhouse under 32°C without shading the greenhouse at a high temperature, it was necessary to fog spray 471.6 L of water per hour. The automatic fog cooling control device was developed to effectively control the fog device, the flow fan, and the light blocking device constituting the fog cooling system. The fog cooling system showed that the temperature of the greenhouse could be lowered by 6°C than the outside temperature. The relative humidity of the fog-cooled greenhouse was 40-80% during the day, about 20% higher than that of the control greenhouse, and this increase in relative humidity contributed to the growth of cucumbers. The relative humidity of the fog cooling greenhouse during the day was 40-80%, which was about 20% higher than that of the control greenhouse, and this increase in relative humidity contributed to the growth of cucumbers. The yield of cucumbers in the fog-cooled greenhouse was 1.8 times higher in the single-span greenhouse and two times higher in the multi-span greenhouse compared to the control greenhouse.

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

To enhance the effectiveness of the FMS (flexible manufacturing system), it is necessary for the manufacturing control system to be upgraded by integrating the cyber and the physical manufacturing systems. Using the CPPS (Cyber-Physical Production System) concept, this study proposes a 4-stage vertical integration and control framework for an aircraft parts manufacturing plant. In the proposed framework, the process controller prepares the operations schedule for processing work orders generated from the APS (advanced planning & scheduling) system. The scheduled operations and the related control commands are assigned to equipments by the dispatcher of the line controller. The line monitor is responsible for monitoring the overall status of the FMS including work orders and equipments. Finally the process monitor uses the simulation model to check the performance of the production plan using real time plant status data. The W-FMCS (Wing rib-Flexible Manufacturing Control & Simulation) are developed to implement the proposed 4-stage CPPS based FMS control architecture. The effectiveness of the proposed control architecture is examined by the real plant’s operational data such as utilization and throughput. The performance improvement examined shows the usefulness of the framework in managing the smart factory’s operation by providing a practical approach to integrate cyber and physical production systems.

This paper deals with the dynamic control of redundant robot manipulator. Traditionally, the kinematic control schemes for redundant robot manipulator were developed from the point of speed and used under the assumption that the dynamic control of manipulator is perfect. However, in reality, the precise control of redundant robot manipulator is very difficult due to their dynamics. Therefore, the kinematic controllers for redundant robot manipulator were employed in the acceleration dimension and may be combined with the computed torque method to achieve the accurate control performance. But their control performance is limited by the accuracy of the manipulator parameters such as the link mass, length, moment of inertia and varying payload. Hence in this paper, the proportional and derivative control gains of the computed torque controller are optimized by the genetic algorithm on the typical payloads, and the neural network is applied to obtain the proper control gains for arbitrary loads. The simulation results show that the proposed control method has better performance than the conventional control method for redundant robot manipulator.

구조물의 진동에 의해 유발되는 사용성, 안정성 저하를 방지하고, 성능을 개선하기 위하여 많은 진동제어시스템이 사용되어 왔다. 제어기 설계가 H2-norm, H∞-norm 으로 분리되어 독립적으로 이루어지다가 LMI 기법에 의하여 보다 효율적인 제어기 설계가 가능하게 되었다. 본 연구에서는 관심지점의 구조물 응답을 특정한 값 이하로 보장한 상태에서 제진장치 구동에 필요한 변수를 최소 화하는 제어알고리듬을 개발하여 능동형뿐만 아니라 수동형제진장치에도 적용하는 방안을 제시하였다. 관심지점의 구조물 응답의 제한은 요구 등가감쇠비와 H∞-norm을 연계하여 구속조건으로 설정하고 목적함수는 제진장치의 이송거리 또는 댐퍼 용량은 H2-norm으 로 표현하는 혼합제어를 구성하였다. 본 연구에서 제안된 혼합제어 기법을 능동질량감쇠기와 등가치환 점탄성 댐퍼가 설치된 구조물에 적용하여 수치적으로 검증하였다. 수치해석결과, 혼합제어문제를 LMI표준형으로 전환하면 능동형, 수동형 제진장치 설계를 보다 용이하게 적용 가능함을 알 수 있었다.

This study introduces a newly developed PC non-bearing wall system to prevent the damage of RC wall-type apartments that have been heavily damaged by the 2017 Pohang Earthquake. In order to evaluate the performance of the developed PC non-bearing wall system, a static cyclic test is conducted. The prototype of test specimen is from the RC wall-type apartment which has been severely damaged by the 2017 Pohang Earthquake. The specimen with the conventional non-bearing wall system showed the similar damage of RC wall type apartment suffered from the Pohang Earthquake. In case of the specimen with the developed PC non-bearing wall system, cracks and damages were not transmitted between the walls due to the seismic slit and there were almost no cracks in the non-bearing walls. Therefore, the proposed non-bearing wall system, separated from the structural walls, could prevent spreading cracks to bearing walls and make it possible to effectively control damage due to earthquake loads.

A retractable bollard system has been used for the traffic control and protection of important facilities such as electric power plants, airports and government buildings etc. The power source of the driving unit of the conventional protective bollard system is on hydraulic or pneumatic system which has several disadvantages compared to an electric driven unit. In this research, an electric driven unit for an automatic retractable bollard is designed and developed to replace the conventional hydraulic and pneumatic driven type. For the reliability test of the developed electric driven unit, a field test has been successfully done. A case study was conducted to develop a defensive retractive bollard which the target performance is 9sec. and 7sec. on its raising and descending operation speed respectively with 750mm in stroke. The required time limit was fully satisfied as the time measured from the experiment were 7.5sec and 5.5sec for each operation. The developed unit also passed 364,000 cycles of operation without any serious malfunctions at the load test proving its reliability. The design theory and process of an electric driven unit of the automatic retractable bollard presented in this article is believed to be very useful contribution and design tool in advancing the physical security industry.

The most important role of air defense system is to attack the air target of enemy to defend the important military unit or facilities. In order to attack the target as soon as it is detected, fast and precise fire signal transfer using the fire control stick is very important. However, it was found that firing is not conducted in the test for fire control stick. In order to find the reason of such problem and improve life cycle of fire control stick, the test was conducted and it was found that chattering occurred and this led to malfunction of signal transfer from control stick to fire control unit of air defense system. In order to draw resolution for this problem, two contact plate made of beryllium copper is suggested to add to the control stick to enhance the contact and reduce chattering effect. The four fire switch prototypes were tested for 100,000 times and it showed its reliability of use.