There is a large risk of damage, triggered by harsh ocean environments, associated with offshore structures, so structural health monitoring plays an important role in preventing the occurrence of critical and global structural failure from such damage. However, obstacles, such as applicability in the field and increasing calculation costs with increasing structural complexity, remain for real-time structure monitoring offshore. Therefore, this study proposes the comparison of cosine similarity with sensor data to overcome such challenges. As the comparison target, this method uses the rate of changes of natural frequencies before and after the occurrence of various damage scenarios, including not only single but multiple damages, which are organized by the experiment technique design. The comparison method alerts to the occurrence of damage using a normalized warning index, which enables workers to manage the risk of damage. By comparison, moreover, the case most similar with the current status is directly figured out without any additional analysis between monitoring and damage identification, which renders the damage identification process simpler. Plus, the averaged rate of errors in detection is suggested to evaluate the damage level more precisely, if needed. Therefore, this method contributes to the application of real-time structural health monitoring for offshore structures by providing an approach to improve the usability of the proposed technique.

The driving performance of an off-road vehicle is closely related to soil strength. A bevameter is used to measure the soil strength, and it usually consists of two independent devices: a pressure–sinkage test device and a shear test device. However, its development and measurement processes have not been standardized; thus, researchers apply it in various fields according to their own discretion. In this study, a new bevameter was developed, and experiments were conducted to clarify the factors that affect the measurement performance of the bevameter. The pressure–sinkage test device was tested with circular plates of different sizes, and the results confirmed that the pressure–sinkage parameters decreased with the plate size. For the shear-test device, normal pressure was applied using a dead load to prevent normal-pressure variation due to displacement and speed. In addition, a spline was installed on top of the shaft connected to the shear ring to measure slip sinkage during the shear test. The results showed that the slip sinkage increased in proportion to the normal pressure and slip displacement, but the increase gradually decreased and converged to a certain point.

In order to utilize wave energy, various wave power systems are being actively researched and developed and interest in them is increasing. To maximize the operational efficiency, it is very important to monitor and maintain the fault of components of the system. In recent years, interest in the management cost, high reliability and facility utilization of such systems has increased. In this regard, fault diagnosis technology including fault factor analysis and fault reproduction is drawing attention as an important main technology. Therefore, in this study, to reproduce and monitor the faults of a wave power system, firstly, the failure mode of the system was analyzed using FMEA analysis. Secondly, according to the derived failure mode and effect, the thrust bearing was selected as a target for fault reproduction and a test equipment bench was constructed. Finally, with the vibration data obtained by conducting the tests, the vibration spectrum was analyzed to extract the features of the data for each operating status; the data was classified by applying the three machine learning algorithms: naïve Bayes (NB), k-nearest neighbor (k-NN), and multi-layer perceptron (MLP). The criteria for determining the fault were derived. It is estimated that a more efficient fault diagnosis is possible by using the standard and fault monitoring method of this study.

The deep-seabed mining system for mining resources consists of a mining vessel, lifting riser, lifting pump, buffer system, flexible riser, and mining robot. Because this system is exposed to extreme environments such as fluid resistance, high water pressure, and deep water, a considerable amount of time and cost is consumed in the design and test evaluation of equipment. To tackle these problems, the deep-seabed mining system in an extreme environment requires simulation-based technology. In particular, due to the large movement caused by marine energy, vibration caused by the operation of the mechanical system, and driving resistance of mining robot by the subsea soft soil, it is very important in the mining system design to analyze the dynamic effects of the various elements that constitute the deep-seabed mining system in a single integrated environment. This paper introduces the development of an integrated dynamic simulation method for deep-seabed mining systems and discusses the results.