The National Institute of Fisheries Science is developing a vibration-based anomaly detection system for small fishing vessel engine rooms. Since the fault types that can occur in such engines are highly diverse and fault-labeled data are difficult to collect for every type, the system is designed to learn the range of normal operating signals and flag deviations from that range as anomalies rather than learning each fault type individually. This normal-data-based approach requires a reliable way to define and measure the normal operating state, and engine speed (RPM) is the most basic such variable. As part of this effort, this study proposes a deep-learning method that estimates RPM directly from engine-room vibration and simultaneously classifies the accelerometer mounting position, using only magnet-mounted accelerometers that require no engine modification, and quantifies which mounting position most clearly captures this normal signal. Four-channel vibration signals were measured on a 9.77-ton coastal purse seiner with an inline-six marine diesel engine whose speed ranged 447-1,444 RPM during the sea trial off Tongyeong, Korea. Hilbert-envelope spectrograms (0-100 Hz) of the four channels were fed into an attention-branch convolutional network with approximately 0.39 M parameters, trained in two stages for RPM regression and position classification. The proposed method achieved a mean absolute error of 42.9 ± 2.1 RPM (about 5% relative error; RMSE 66.3 RPM,  = 0.935 for the representative model) and a position classification accuracy of 99.6% on the time-sequential test set. Ablation experiments showed that the envelope demodulation and the 100-Hz bandwidth, which covers the firing frequency and up to the 13th rotational harmonic, were the dominant factors. The learned attention weights were highest for the channel near the power-transmission end of the engine and varied with the operating range, indicating which position most reliably captures the normal signal under each condition and demonstrating the benefit of adaptive multi-channel fusion.

This study investigates the global hull vibration characteristics of a 2,000-ton fisheries training vessel and evaluates its habitability based on the ISO 6954:2000(E) standards. A three-dimensional finite element model, developed using MSC Patran/Nastran, was validated against sea trial measurement data. The results indicate that natural frequencies are generally below 10 Hz and decrease with increasing load. The habitability assessment shows that vibration levels remain at 5-8% of the ISO criteria for the FEA model and 4-10% for the measured data, confirming that the vessel satisfies the regulatory limits. The methodology, validated by these measurements, provides a quantitative technical basis for the design verification and operational management of similar vessels.

This study evaluates ground-motion (GM) acceleration conversion methods by applying them to strain-rate data from a horizontal Distributed Acoustic Sensing (DAS) array under both idealized and real-world conditions. We test four conversion methods—1) slant-stacking, 2) Lior’s method, 3) Lindsey’s method, and 4) Curvelet transform—through numerical modeling and by applying them to a publicly available 9 km horizontal DAS array dataset. Numerical simulations reveal critical calculation factors specific to each method and show that numerically derived apparent ground velocity can deviate from theoretical values when multiple elastic waves arrive simultaneously. In real-world applications, the slant-stacking and Lior’s methods are relatively insensitive to the measurement length of the straight DAS array. By contrast, the Curvelet method exhibits strong sensitivity to this factor, whereas Lindsey’s method shows weaker dependence. Implementing Lior’s method in the frequency-wavenumber domain also requires pre-determining water-levels by comparing adjacent seismograms. Additionally, we find that Lior’s method generates excessively high spectral levels above 13 Hz, which may lead to underestimation of the high-frequency spectral attenuation parameter (κ0), a key parameter in GM simulation. Collectively, these findings provide a technical guideline for the use of horizontal DAS arrays in future observational earthquake seismology.

이 논문에서는 강화학습 기반 제어기와 전통적인 제어기를 동일한 조건에서 비교함으로써 구조 진동 제어 문제에서 강화학습 제 어기의 성능 특성과 한계를 규명하는 것을 목적으로 한다. 가장 단순한 비선형 제어로서 단자유도 가변 강성 시스템을 대상으로 심층 결정적 정책 경사(DDPG) 기반의 강화 학습 제어기를 설계하고, bang-bang 제어 및 제한 최적 제어와의 성능 비교를 수행하였다. 자유 진동 및 El Centro 지진 가속도에 의한 강제 진동 조건에서 공칭 성능과 센서 잡음이 존재하는 경우의 강인 성능을 분석하였다. 그 결 과, 강화학습 제어기는 자유 진동 조건에서 우수한 강인 성능을 보였으나, 강제 진동 제어에서는 기존 제어기를 일관되게 상회하지는 못하였다. 이 연구는 동일한 보상 함수와 시스템 조건 하에서 강화학습 기반 진동 제어의 실질적 기여와 적용상의 한계를 기초적으로 제시하였다.

본 논문에서는 경사기능재료(Functionally Graded Material, FGM) 개념과 위상최적설계 방법을 통해 3차원 경사기능복합재 구조 (Functionally Graded Composite Structure, FGCS)의 설계 방법을 제안한다. 다중 스케일 복합재 구조 설계 시 이방성 재료 물성치의 계 산은 RVE 기반 ML 모듈과 단위 사원수를 활용한 회전 행렬 계산을 통해 수행된다. 또한, 본 연구에서는 다양한 물리적 환경을 설계 에 반영하기 위해 구조물의 강성과 함께 고유진동수를 목적함수로 설정한 다중 목적함수 최적설계를 수행하여 구조물의 최적화 형 상과 성능을 분석한다.

When tube bundles submerged in water vibrate, their dynamic behavior is affected by the surrounding fluid. In particular, the added mass of the fluid leads to changes in the vibration characteristics of the structure. In nuclear power plants, steam generator heat transfer tubes are arranged in dense bundles and operate under submerged conditions, making fluid–structure interaction an important consideration. In this study, a fluid–structure interaction analysis is performed for a submerged group of tube bundles representative of nuclear power plant steam generator heat transfer tubes. Using a finite element–based coupled fluid– structural analysis, the vibration responses of the tube bundle are numerically investigated. The effects of the surrounding fluid on the vibration characteristics of the tube bundle are examined. The results indicate that the presence of the fluid significantly influences the vibration behavior of the tube bundle.

This study applied ultrasonic cutting technology to solve the problem of lowering the cutting efficiency in the manufacturing process of transparent orthodontic braces, and in particular, used conical blades to improve cutting quality and efficiency. The existing process relied on manual work, resulting in problems such as quality deviation, labor strength, and shortening the tool life. Laser cutting technology was also attempted, but there was a limitation due to the generation of heat-affected parts and the generation of harmful by-products. Accordingly, in this study, a no-pressure cutting method using ultrasonic vibration (20~40 kHz) was introduced, and optimal process conditions were established based on the experimental planning method. Ultrasonic cutting using a conical blade minimized heat generation and improved the quality of the cutting surface, and secured stability in continuous processing. As a result of the experiment, the cutting efficiency and surface quality were superior to those of existing scissors cutting and CO₂ laser cutting, and the applicability of the automation process was confirmed. This study is a core technology that can realize the automation and high efficiency of manufacturing transparent correctors, and is expected to be expanded to the dental industry and precision processing industry in the future.

본 논문에서는 상반회전 추진 프로펠러 이중축계의 회전 동특성을 정밀하게 분석하기 위한 수치해석 방법을 제안하였다. 제안된 해석 기법은 티모쉔코 보 이론 기반의 유한요소법을 이용하여 자이로스코픽 효과와 베어링 감쇠를 포함한 운동방정식을 정식화하였 다. 개발된 해석 코드는 기존 동축 회전체 모델과의 비교를 통해 검증되었으며, 고유진동수와 캠벨선도 결과가 매우 잘 일치함을 확인 하였다. CRP 축계의 시뮬레이션 결과 1차 공진모드에서 내축의 변위가 외축보다 커 축간 충돌 가능성이 높은 것으로 나타났다. 베어 링 강성 증가 시 고유진동수가 상승하여 공진영역을 회피할 수 있었으며, 축 직경 변화는 상대적으로 영향이 작았다. 제안된 해석 기 법은 상반회전 추진 이중축계의 설계 평가 및 진동 안정성 분석에 유용하게 활용될 수 있으며, 향후에는 비선형 베어링 특성 및 유체– 구조 연성효과를 포함한 확장 연구로 발전시킬 수 있을 것이다.

출렁다리의 설계 초기에 주요 제원을 결정하기 위하여 진동 특성을 신속하게 파악하는 것이 필요하다. 출렁다리는 케이블 특 성상 비선형성 구조해석이 필요하기에 아주 정확하지 않더라도 간단한 해석 방법이 있으면 설계자에게 도움이 된다. 이에 본 연구에 서는 현수교 해석 이론을 출렁다리에 적용하여 수직 및 비틈 고유 진동수를 예측할 수 있는 해석해를 제시한다. 제시된 해석해는 해밀 턴 원리(Hamilton’s principle) 및 리츠법(Ritz method)을 기반으로 유도하였으며, 대칭 및 비대칭 모드의 고유진동수를 주요 구조 제원 만으로 계산할 수 있다. 제안된 해석해의 타당성을 검증하기 위하여 경간장이 100 m부터 309 m인 4가지 출렁다리의 유한요소해석과 비교하였다. 본 연구의 산정식으로 계산한 고유진동수와 교량 설계서의 유한요소해석 결과는 수직 모드는 잘 일치하나 비틈 모드는 일 부 차이가 있었다. 본 연구에서 제안한 산정식은 복잡한 구조해석을 수행하지 않고도 효율적으로 간단하게 출렁다리의 고유진동수를 산정하여 기본설계에서 활용할 수 있는 실용적인 방법임을 확인하였다.

This study presents the results of compression, drop impact, and vibration durability analyses conducted to evaluate the mechanical reliability of Battery Pack Cases (BPCs) in electric vehicle (EV) systems. BPCs are essential structural components that must endure compressive loads, impact forces, and vibrational fatigue. Finite Element Analysis (FEA) was applied to a representative BPC model to assess deformation, impact resistance, and vibration endurance. The results indicate that the BPC maintained integrity within yield strength limits under compressive loading and effectively absorbed energy under drop impact. Furthermore, Power Spectral Density (PSD) analysis identified stress concentration regions, providing insights for structural optimization. Overall, the findings support the development of lightweight and reliable BPC designs for advanced EV applications.

To improve vibration reduction in the railway vehicle, the semi-active suspension system using MR damper was developed and the vibration performance of the passive suspension system and a semi-active MR suspension system was compared. For the experiment, the MR damper and suspension system were designed and manufactured. Tensile and compression tests were performed on the MR damper while varying the input current. The damping force of the MR damper was measured and analyzed using the Bingham model. The railway vehicle was modeled with 9 degrees of freedom, and the sky hook control algorithm was simulated using the MR damper, using the Bingham model. This verified the effectiveness of the sky hook controller. Furthermore, to compare the vibration performance of the railway vehicle, the driving test was conducted with the MR damper and the passive damper. The lateral acceleration vibration reduction performance of the suspension system with MR dampers and passive dampers was verified, and it was confirmed that the vibration reduction performance of the vehicle with the semi-active suspension system using MR damper was approximately 50% better than that of the vehicle with the passive damper.

A compact vibratory bowl feeder system is proposed to transport lightweight annular film components. Vibration analysis was conducted to calculate its natural frequencies, and the motion characteristics of the bowl and transported parts were analyzed under resonance excitation at varying supply voltage levels. The natural frequencies of the proposed system were found to be 157Hz, 249Hz, and 505Hz. At these resonance frequencies, significant rotational vibrations occurred, while vertical vibrations were relatively small. Especially at 505Hz, bending of the leaf spring caused large rotational motion of the bowl. The part feeding speed increased linearly with the applied voltage, reaching 4mm/sec at 100V and 18mm/sec at 200V. At 157Hz and 249Hz excitation frequencies, large rotational and vertical vibrations were observed, respectively. Under rotational vibration, the parts moved forward via jumping motion when the bowl's velocity amplitude was relatively large, or via slipping when smaller. Minor backward slipping was also observed. Under vertical vibration, parts exhibited forward jumping motion without back-and-forth slipping.

전기추진 선박의 추진축계 이상상태는 심각한 선박 운항 장애를 초래할 수 있으므로, 추진 시스템의 상태를 정확히 진단하고 사전에 예방 유지보수를 수행하는 Prognostics and Health Management(PHM) 기술의 필요성이 증가하고 있다. 본 연구에서는 전기추진 선박 의 추진축 이상상태를 조기에 감지하고 진단하기 위하여 진동 데이터를 기반으로 한 머신러닝 기반 PHM 시스템의 개발과 성능 평가를 수행하였다. Land-Based Testing System(LBTS) 시스템에서 수집된 정상 상태와 축 정렬 이상 상태(0.5 mm, 1.0 mm, 1.5 mm)의 진동 데이터를 활용하여 데이터 전처리 및 특성 추출을 수행하였다. 연구에서는 Fully Connected Neural Network(FCNN) 및 Convolutional Neural Network(CNN)을 적용하여 이상 상태를 진단하는 모델을 개발하고 비교 분석하였다. FCNN 기반 모델은 단순한 구조로 빠른 학습이 가능 하여 실시간 모니터링에 적합한 반면, CNN 모델은 미세한 상태 변화를 효과적으로 탐지하는 데 탁월한 성능을 보였다. 성능 평가 결과 FCNN 모델은 평균 95% 이상의 정확도를 나타냈으며, CNN 모델은 이보다 더욱 향상된 성능을 제공하였다. 본 연구를 통해 개발된 진동 기반 PHM 시스템은 전기추진 선박 추진축 이상상태를 효과적으로 조기에 진단할 수 있는 능력을 입증하였다. 이러한 연구 성과는 전기 추진 선박의 안전하고 효율적인 운항을 위한 신뢰성 높은 유지보수 전략 수립에 중요한 기여를 할 것으로 기대된다. 향후 연구로는 데이 터 품질 개선 및 추가적인 딥러닝 모델 적용을 통한 성능 향상을 목표로 한다.

This study investigates the vibration characteristics of an aluminum subframe for small and high-speed vessels through modal and resonance analysis using the finite element method (FEM). Due to the low stiffness and damping of aluminum, concerns arise over structural resonance and fatigue. A 3D model based on actual design drawings was analyzed to extract six natural frequencies and corresponding mode shapes. Significant deformation was observed in the first and second modes (90.65 Hz, 110.60 Hz), which may overlap with operational frequencies. The fifth mode (263.70 Hz) showed high amplitude with Y-axis concentration, indicating lateral resonance vulnerability. Deformation ratios were used to identify dominant vibrational directions. Based on the findings, design strategies such as structural reinforcement, RPM adjustment, and damping device application were proposed to improve vibration safety in the early design stage.

The purpose of this paper is to investigate the vibration phenomenon occurring in the structure such as a ship with the hemispherical substructure and operating at fixed frequency, and to suggest the active vibration control method using the Fx-LMS algorithm to reduce vibration amplification. In order to study the possibility of reducing vibration in the hemispherical structure, the active vibration control model was developed and a vibration control experimental device for the hemispherical structure was constructed. The narrowband Fx-LMS algorithm was developed to enable precise real-time control at a specific frequency, and the secondary path for dynamic control was modeled with two coefficients per frequency. The experimental device is equipped with three exciters, six 3-axis actuators, and six 3-axis error sensors, which can acquire 18 error sensor signals. Real-time secondary path tracking was possible with the secondary path consisting of two coefficients and the control algorithm, and effective vibration control performance was confirmed through this. And the experimental results of active vibration control of the exciter for three frequencies showed that the exciter vibration was reduced by a minimum of 63.7% and a maximum of 97.7%, which shows the possibility of reducing the vibration of the structure in real time using the proposed method.