In the current study, MIL-101(Cr)-SO3H[HCl] as metal-organic frameworks (MOFs) was fabricated via a hydrothermal method. The physicochemical properties of the synthesized material were characterized using XRD, FT-IR, FE-SEM, TEM, and BET surface area analysis. The XRD diffraction pattern of the prepared MIL-101(Cr)-SO3H[HCl] was similar to previously reported patterns of MIL-101(Cr) type materials, indicating successful synthesis of MIL-101(Cr)-SO3H[HCl]. The FT-IR spectrum revealed the molecular structure and functional groups of the synthesized MIL-101(Cr)-SO3H[HCl]. FE-SEM and TEM images indicated the formation of rectangular parallelopiped structures in the prepared MIL-101(Cr)-SO3H[HCl]. Furthermore, the EDS spectrum showed that the synthesized material consisted of the elements of Cr, O, S, and C. The fabricated MIL-101(Cr)-SO3H[HCl] was then employed as an adsorbent for the removal of Sr2+ and Cs+ from aqueous solutions. The adsorption kinetics and adsorption isotherm models were studied in detail. The maximum adsorption capacities of MIL-101(Cr)-SO3H[HCl] for Sr2+ and Cs+ according to pH (3, 5.3∼5.8, 10) were 35.05, 43.35, and 79.72 mg/g and 78.58, 74.58, and 169.74 mg/g, respectively. These results demonstrate the potential of the synthesized MOFs, which can be effectively applied as an adsorbent for the removal of Sr2+ and Cs+ ions from aqueous solutions and other diverse applications.

The impact of sound speed variability in the sea is the very important on acoustic propagation for the underwater acoustic systems. Understanding of the temporal and spatial variability of ocean sound speed in the sea around the Ieodo were obtained using oceanographic data (temperature, salinity). from the Korea Oceanographic Data Center, collected by season for 17 years. The vertical distributions of sound speed are mainly related to seasonal variations and various current such as Chinese coastal water, Yellow Sea Cold Water (YSCW), Kuroshio source water. The standard deviations show that great variations of sound speed exist in the upper layer and observation station between 16 and 18. In order to quantitatively explain the reason for sound speed variations, Empirical Orthogonal Function (EOF) analysis was performed on sound speed data at the Line 316 covering 68 cruises between 2002 and 2018. Three main modes of EOFs respectively revealed 55, 29, and 5% the total variance of sound speed. The first mode of the EOFs was associated with influence of surface heating. The second EOFs pattern shows that contributions of YSCW and surface heating. The first and second modes had seasonal and inter-annul variations.

This paper presents a control and operation system for a remotely operated vehicle (ROV). The ROV used in the study was equipped with a manipulator and is being developed for underwater exploration and autonomous underwater working. Precision position and attitude control ability is essential for underwater operation using a manipulator. For propulsion, the ROV is equipped with eight thrusters, the number of those are more than six degrees-of-freedom. Four of them are in charge of surge, sway, and yaw motion, and the other four are responsible for heave, roll, and pitch motion. Therefore, it is more efficient to integrate the management of the thrusters rather than control them individually. In this paper, a thrust allocation method for thruster management is presented, and the design of a feedback controller using sensor data is described. The software for the ROV operation consists of a robot operating system that can efficiently process data between multiple hardware platforms. Through experimental analysis, the validity of the control system performance was verified.

This paper describes a method for tracking attitude and position of underwater robots. Underwater work with underwater robots is subject to differences in work efficiency depending on the skill of the operator and the utilization of additional sensors. Therefore, this study developed an underwater robot that can operate autonomously and maintain a certain attitude when working underwater to reduce difference of work efficiency. The developed underwater robot uses 8 thrusters to control 6 degrees of freedom motion, IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and PS (Pressure Sensor) to measure attitude and position. In addition, the thruster allocation algorithm was designed to follow the control desired value using 8 thrusters, and the motion control experiments were performed in the engineering water basin using the thruster allocation method.

This research is a case study of underwater object tracking based on real-time recurrent regression networks (Re3). Re3 has the concept of generic object tracking. Because of these characteristics, it is very effective to apply this model to unclear underwater sonar images. The model also an pursues object tracking method, thus it solves the problem of calculating load that may be limited when object detection models are used, unlike the tracking models. The model is also highly intuitive, so it has excellent continuity of tracking even if the object being tracked temporarily becomes partially occluded or faded. There are 4 types of the dataset using multi-beam sonar images: including (a) dummy object floated at the testbed; (b) dummy object settled at the bottom of the sea; (c) tire object settled at the bottom of the testbed; (d) multi-objects settled at the bottom of the testbed. For this study, the experiments were conducted to obtain underwater sonar images from the sea and underwater testbed, and the validity of using noisy underwater sonar images was tested to be able to track objects robustly.

In this paper, we introduce the methodology that utilizes deep learning-based front-end to enhance underwater feature matching. Both optical camera and sonar are widely applicable sensors in underwater research, however, each sensor has its own weaknesses, such as light condition and turbidity for the optic camera, and noise for sonar. To overcome the problems, we proposed the opti-acoustic transformation method. Since feature detection in sonar image is challenging, we converted the sonar image to an optic style image. Maintaining the main contents in the sonar image, CNN-based style transfer method changed the style of the image that facilitates feature detection. Finally, we verified our result using cosine similarity comparison and feature matching against the original optic image.

현재 K-water의 관리하고 있는 시설물은 그 중요도에 따라서 정밀안전진단 등 법적인 점검뿐만 아니라 자체점검 등을 수행하며 안전관리에 만전을 기하고 있다. 현재는 수중조사장비의 기술적 한계로 육안 조사를 위한 인력잠수에 의존하고 있어 인명사고 위험 및 조사범위의 한계 등의 문제점을 안고 있다. 미국, 일본 등의 해외에서는 이러한 문제점을 극복하기 위해 수중 ROV를 이용한 수중조사 및 점검 기술의 도입을 적극적으로 추진하고 있으며 K-water에서도 수중 ROV를 활용한 댐체 및 보 구조물에 대한 수중점검기술을 도입하고자 연구를 현재 수행 중에 있다.

In this paper, we present auto-annotation tool and synthetic dataset using 3D CAD model for deep learning based object detection. To be used as training data for deep learning methods, class, segmentation, bounding-box, contour, and pose annotations of the object are needed. We propose an automated annotation tool and synthetic image generation. Our resulting synthetic dataset reflects occlusion between objects and applicable for both underwater and in-air environments. To verify our synthetic dataset, we use MASK R-CNN as a state-of-the-art method among object detection model using deep learning. For experiment, we make the experimental environment reflecting the actual underwater environment. We show that object detection model trained via our dataset show significantly accurate results and robustness for the underwater environment. Lastly, we verify that our synthetic dataset is suitable for deep learning model for the underwater environments.

The purpose of underwater survey is to provide basic data for proper maintenance and reinforcement to detect waterborne defects as early as possible, to prolong the life of bridges and to ensure safety. This study suggests an underwater investigation item and method to be observed by the inspector in checking the substructure of the marine bridge. However, due to the limit that can not deal with the characteristics of the area where maritime bridges are installed in detail, it is considered desirable to use this point as a minimum safety and performance standard in underwater survey sites and management bodies.

In the ground environment, mobile robot research uses sensors such as GPS and optical cameras to localize surrounding landmarks and to estimate the position of the robot. However, an underwater environment restricts the use of sensors such as optical cameras and GPS. Also, unlike the ground environment, it is difficult to make a continuous observation of landmarks for location estimation. So, in underwater research, artificial markers are installed to generate a strong and lasting landmark. When artificial markers are acquired with an underwater sonar sensor, different types of noise are caused in the underwater sonar image. This noise is one of the factors that reduces object detection performance. This paper aims to improve object detection performance through distortion and rotation augmentation of training data. Object detection is detected using a Faster R-CNN.

Geomagnetic field signals have potential for use in underwater navigation and geophysical surveys. To map underwater geomagnetic fields, we propose a method that exploits an autonomous surface vehicle. In our system, a magnetometer is rigidly attached to the vehicle and not towed by a cable, minimizing the system’s size and complexity but requiring a dedicated calibration procedure due to magnetic distortion caused by the vehicle. Conventional 2D methods can be employed for the calibration by assuming the horizontal movement of the magnetometer, whereas the proposed 3D approach can correct for horizontal misalignment of the sensor. Our method does not require a supporting crane system to rotate the vehicle, and calibrates and maps simultaneously by exploiting data obtained from field operation. The proposed method has been verified experimentally in inland waters, generating a magnetic field map of the test area that is of much higher resolution than the public magnetic field data.

수중에서 로봇으로 사석 고르기 작업을 실시할 경우 로봇 주위의 지형 정보를 실시간으로 제공해야 원격조종이 가능하다. 현 위치로 부터 주변지형의 높낮이를 보여줘야 운전자가 작업 계획을 수립하고, 전복과 같은 사고도 예방할 수 있다. 지금까지 지형인식은 멀티 빔 소나에 의해 이뤄졌는데 이는 작업 전후의 품질을 평가하는 용도만 사용되었지 원격조종에서 필요한 실시간 정보로는 사용될 수 없었다. 본 연구는 수중 사석 고르기 작업을 위한 실시간 지형인식 방법을 개발한다. 버킷이 지면을 누를 때 전달되는 힘을 측정해 접촉여부를 판단하고, 실린더의 길이를 읽어 접촉위치를 계산한다. 버킷의 위치제어를 위해 가변 뱅뱅제어 알고리즘을 적용하고 숙련된 굴삭기 운전자의 작업패턴을 프로 그램화해 지형인식, 긁기, 밀기, 전진 등의 작업을 자동으로 수행하도록 한다. 개발된 방법은 로봇 몸체로부터 버킷의 거리에 따라 3차원 격자 지형을 상대적으로 보여줌으로써 작업자가 쉽게 지형을 인식하고 지형에 따라 작업계획을 세우도록 한다.

In this paper, a high performance underwater vehicle which can be manufactured at low cost is designed and fabricated, and its performance is verified through experiments. To improve efficiency, the Myring equation is used to design the appearance and the duct structure including the thruster is planned to increase the propulsion efficiency while reducing the drag force. Through various methods, it is secured stable waterproof performance, and also is devised to have high speed movement and turning performance. The developed underwater vehicle is equipped with a high output BLDC motor to achieve a linear speed of up to 2 m/s and can change direction rapidly with stability through four rudders. The rudders are driven by coupling a timing belt and a pulley by extending the axis of a servo motor, and are equipped at the end of the body to turn heading. In addition, for stable posture control, the roll keeps its internal center of gravity low and maintains its stability due to restoring force. By controlling the four rudders, pitch and yaw are handled by the PID controller and show stable performance. To investigate the horizontal turning performance, it is confirmed that the yaw rate controller is designed and stable yaw rate control is performed.

This study focuses on autonomous exploration based on map expansion for an underwater robot equipped with acoustic sonars. Map expansion is applicable to large-area mapping, but it may affect localization accuracy. Thus, as the key contribution of this paper, we propose a method for underwater autonomous exploration wherein the robot determines the trade-off between map expansion ratio and position accuracy, selects which of the two has higher priority, and then moves to a mission step. An occupancy grid map is synthesized by utilizing the measurements of an acoustic range sonar that determines the probability of occupancy. This information is then used to determine a path to the frontier, which becomes the new search point. During area searching and map building, the robot revisits artificial landmarks to improve its position accuracy as based on imaging sonar-based recognition and EKF-SLAM if the position accuracy is above the predetermined threshold. Additionally, real-time experiments were conducted by using an underwater robot, yShark, to validate the proposed method, and the analysis of the results is discussed herein.

암모니아성 질소는 생활하수, 축산폐수, 산업폐수 등의 점오염원과 화학적 비료 남용에 의한 유출 등의 비점오염원으로부터 수계로 방류되어 부영양화 등의 수질 오염을 유발할 수 있다. 생활하수 등에서 암모니아성 질소를 제거하기 위해 생물학적 처리공정이 주로 적용되고 있으나 운영상의 어려움, 비점오염원 저감의 어려움으로 인하여 대체방안이 요구된다. 바이오차를 흡착제로 활용하는 방안은 적용이 간단하며 효율적으로 수중 암모니아를 제거하는 방안으로 주목받고 있다. 선행 연구에서는 대부분 암모니아성 질소 흡착을 NH4+ 양이온 흡착으로 설명하고 있으나 수중의 암모니아성 질소는 pH에 따라 NH4+와 NH3(aq)로 분배될 수 있어 적용 조건에 따라 두 화학종이 모두 흡착에 참여할 가능성이 있다. 따라서 본 연구에서는 이러한 화학종 분배를 함께 고려하는 것의 필요성을 검증하고자 하였다. 바이오차는 발생량이 많은 농업부산물인 볏짚을 300, 400, 500, 600℃ 네 가지 최고온도로 열분해하여 얻었다. 암모니아성 질소 용액은 NH4Cl을 이용하여 준비하였다. 이후 20℃에서 바이오차 투여량 5 g/L 조건으로 초기농도 10 ~ 500 mg/L 용액에 대하여 등온흡착실험을 진행하였다. 흡착반응속도실험은 20℃에서 투여량 5 g/L 조건으로 초기농도 50 mg/L에서 진행하였다. 바이오차 투여 이후 pH는 NH4+의 pKa인 9.25 부근까지 증가하여 NH3(aq)가 액상에 존재할 수 있음을 확인하였다. 등온흡착곡선은 BET 모형에 의해 설명되었기에 응축에 의한 다층 흡착이 진행되는 것을 확인하였다. NH4+만이 흡착에 참여할 경우 쿨롱 반발력에 의해 응축이 일어날 수 없다. NH3(aq)가 흡착에 참여한다면 극성 분자의 쌍극자모멘트 또는 약한 수소결합으로 부터 응축에 의한 다층 흡착을 설명할 수 있다. 반응속도 실험결과 300℃에서 제조한 바이오차에 의한 암모니아성 질소 흡착은 유사 1차 반응속도 모형으로부터 설명할 수 있어 NH4+ 흡착이 주요한 것으로 생각된다. 300℃보다 높은 온도에서 제조한 바이오차의 경우 Elovich’s Equation이 암모니아성 질소의 흡착반응속도를 더 잘 설명하여 흡착 메커니즘을 NH4+ 흡착으로 설명할 수 없었다. Elovich’s Equation은 분자 상 물질의 화학적 흡착을 설명하는 모형이므로 NH3(aq)이 흡착에 참여하는 것으로 해석할 수 있다. 따라서 본 연구에서는 바이오차에 의한 암모니아성 질소 흡착은 NH4+ 이온의 흡착뿐만 아니라 NH3(aq)의 흡착도 함께 고려해야 함을 확인하였다.

This paper describes a study on posture control of the multi-legged biomimetic underwater robot (CALEB10). Because the underwater environment has a feature that all degrees of freedom are coupled to each other, we designed the posture control algorithm by separating each degree of freedom. Not only should the research on posture control of underwater robots be a precedent study for position control, but it is also necessary to compensate disturbance in each direction. In the research on the yaw directional posture control, we made the drag force generated by the stroke of the left leg and the right leg occur asymmetrically, in order that a rotational moment is generated along the yaw direction. In the composite swimming controller in which the controllers in each direction are combined, we designed the algorithm to determine the control weights in each direction according to the error angle along the yaw direction. The performance of the proposed posture control method is verified by a dynamical simulator and underwater experiments.

본 연구에서는 세장체의 연속적인 거동을 전체 길이에 대하여 측정할 수 있는 계측시스템을 선정하며, 선정된 수중카메라 시스템의 성능평가를 수행한다. 수중카메라의 기초성능평가를 위하여 강체파이프의 강제가진 실험을 수행한다. 파이프의 상단을 강제가진장치에 고정시킨 후, 일정주기와 진폭으로 가진시켜 수중카메라를 이용하여 변위를 측정한다. 강제가진장치에 입력된 신호와 수중카메라에 계측된 신 호를 비교하여 측정 정밀도를 평가한다. 연속체인 세장체 파이프의 강제가진 실험을 수행하여, 수중카메라 시스템의 실시간 3차원적인 측정 가능성을 정성적으로 평가한다. 본 수중카메라 시스템은 향후 국내 심해공학수조에 적용되어, 세장체구조물 및 계류선 등의 거동 측정에 활용 될 것이다.

Acoustic based localization is essential to operate autonomous robotic systems in underwater environment where the use of sensorial data is limited. This paper proposes a localization method using artificial underwater acoustic sources. The proposed method acquires directional angles of acoustic sources using time difference of arrivals of two hydrophones. For this purpose, a probabilistic approach is used for accurate estimation of the time delay. Then, Gaussian sum filter based SLAM technique is used to localize both acoustic sources and underwater vehicle. It is performed by using bearing of acoustic sources as measurement and inertial sensors as prediction model. The proposed method can handle directional ambiguity of time difference based source localization by generating Gaussian models corresponding to possible locations of both front and back sides. Through these processes, the proposed method can provide reliable localization method for underwater vehicles without any prior information of source locations. The performance of the proposed method is verified by experimental results conducted in a real sea environment.

수중음향통신은 다중경로로 인한 신호간의 간섭으로 성능이 열악하므로 채널 부호화의 적용은 필수적이다. 수중 통신에서 데이터 를 전송하기 위한 패킷의 구조는 동기 획득을 위해 데이터 전송 전에 PN 시퀀스를 데이터의 헤드 부분에 첨가하여 전송한다. PN 시퀀스는 송·수신 간에 서로 알고 있는 데이터를 이용하여 동기를 획득하는 기능을 하고 있으므로 PN 시퀀스는 채널 부호화를 하지 않고 전송된다. 이 러한 비부호화 된 PN 시퀀스는 대부분의 연구에서는 동기 획득을 위해 활용되지만 본 논문에서는 동기 획득 뿐 아니라 PN 시퀀스의 성능을 이용하여 데이터 필드의 성능 또한 예측할 수 있어 데이터 필드의 복호부에 정보를 제공할 수 있다. 본 논문에서는 다중 경로 전달 환경인 수중음향통신에서 원활한 통신과 함께 수신 신호의 성능을 향상시키기 위하여 낮은 SNR에서도 우수한 성능을 보이는 컨볼루션 부호화 기법 과 BCJR 복호 방식을 이용하여 다양한 부호화 율에서 비 부호화 된 PN 시퀀스의 오류율과 부호화 된 데이터 필드의 오류율의 상관관계를 시뮬레이션 및 실제 수중 실험을 통해 분석하여 효율적인 수신 구조를 제시하였다.

The removal characteristics of 2,4-dinitrophenol (2,4-DNP) from an aqueous solution by commercial Wood-based Activated Carbon (WAC) have been studied. The effects of various experimental parameters were investigated using a batch adsorption technique. The adsorption capacity of 2,4-DNP by WAC increased with a decrease in the dosage and particle size of WAC, temperature and the initial pH of the solution, and increased with an increase in the initial concentration of the solution. The adsorption equilibrium data were best described by the Redlich-Peterson isotherm model. The maximum adsorption capacities of 2,4-DNP by WAC were 573.07 mg/g at 293 K, 500.00 mg/g at 313 K, and 476.19 mg/g at 333 K, decreasing with increasing temperature. The kinetic data were well fitted to the pseudo-second-order model, and the results of the intra-particle diffusion model suggested that the adsorption process was mainly controlled by particle diffusion. The thermodynamic analysis indicated that the adsorption of 2,4-DNP by WAC was an endothermic and spontaneous process.