본 논문에서는 볼트로 체결된 구조체에 대하여 초기 볼트풀림 상태에서의 볼트 체결력 예측 합성곱 신경망 훈련 방법을 제시한다. 8개의 볼트의 체결력이 변경된 상태에서 계산한 주파수응답들을 완전 체결된 상태의 초기 모델과의 크기 및 모양 유사성을 표현하는 유사성 지도로 생성한다. 주파수응답 데이터들의 생성에는 크리로프 부공간법 기반의 모델차수축소법을 적용하여 효율적인 방법으 로 수행할 수 있도록 한다. 합성곱 신경망 모델은 회귀 출력 계층을 사용하여 볼트의 체결력을 예측하도록 하였으며, 훈련 데이터의 개 수와 합성곱 신경망 계층의 개수를 다르게 준비하여 훈련시킨 네트워크들을 비교하여 그 성능을 평가하였다. 주파수응답에서 파생되 는 유사성 지도를 입력 데이터로 사용하여 초기 볼트풀림 영역에서 볼트 체결력의 진단 가능성과 유효성을 제시하였다.

Controller modeling is essential for the design. It allows various control techniques to be simulated in advance, and various interpretations can be performed. If this is not the case, we need to reverse engineering in the real system developed by others. In this paper, controller modeling was reversely designed using the frequency test results of the target system. First, the characteristic equation of the target equipment was based on and a block diagram was assumed. Thereafter, controller variables were estimated using the frequency test results for each of the four control loops. In addition, time response simulations were performed using the estimated controller modeling. This method is thought to be of great help to reverse engineering in situations where there is completed equipment but no controller modeling.

In September and October 2020, combined acoustic and trawl surveys were conducted in the northwestern sea of Jeju Island. In the survey area, a region, so called Jeju region, was designated to esimate the biomass of chub mackerel and jack mackerel using a trawl survey method and frequency difference method. In the September survey, the weight ratios of jack mackerel and chub mackerel to the total catch were 24.6% and 2.8%, respectively, and in the October survey, those ratios were 24.9% and 20.7%, which were used to calculate their biomass (trawl survey). Using the frequency difference range (–8 to –3dB) corresponding to two species in 120 and 200 kHz, their biomass was estimated (frequency difference method). As a result, the biomass of two species from the trawl method was 3252.3 tons in September and 5777.0 tons in October. The estimated biomass by the frequency difference method was 4926.6 tons in September and 7521.5 tons in October. It was the first trial to estimate the biomass of two species using the trawl and frequency differencing methods in South Korea although there were some differences between two methods. In addition, horizontal distributions of acoustic backscattering strength over the entire survey area were mapped.

PURPOSES : The purpose of this study is to identify the dynamic behavior of a cement concrete paving machine (paver) by measuring its response using accelerometers. This is because the dynamic behavior of pavers affects the quality of data from various applications of IoT sensors, such as laser, ultrasonic, optical sensors and so on. Therefore, it is believed that the understanding of dynamic behaviors can contribute to the effective use of various IoT sensors for the acquisition of real-time quality control data in pavement construction. METHODS : Dynamic signals are obtained using accelerometer sensors to identify the dynamic characteristics of paving machines. The main parameters for acquiring dynamic signals are the status of the machine’s operating or standby conditions, and available locations for attaching various IoT sensors. Time domain data are logged at a particular sampling speed using a low-pass filter, subsequently, they are converted to digital data, which are analyzed on three rectangular axes. In addition frequency analysis is conducted on the measured data for identifying the peak frequencies, via FFT (Fast-Fourier-Transform) using MATLAB. RESULTS : The magnitude of the x-directional vibration is higher than that of any other direction under the paver’s operating or standby condition. However, signals from the smoother beam show that the z-directional vibration is more significant in the operating status. It means that the primary vibration depends on the location. Furthermore, the peak frequencies are quite various depending on the status of a paver and its sensing location. CONCLUSIONS : The magnitude of machine vibration and peak frequencies at each status or location are identified from time- and frequency-domain data. When using IoT sensors for quality control or monitoring pavements in construction, the dynamic characteristics of a paver should be considered to mitigate the interference of signals from the paver body or its elements.

The governing equation for a dome-type shallow spatial truss subjected to a transverse load is expressed in the form of the Duffing equation, and it can be derived by considering geometrical non-linearity. When this model under constant load exceeds the critical level, unstable behavior is appeared. This phenomenon changes sensitively as the number of free-nodes increases or depends on the imperfection of the system. When the load is a periodic function, more complex behavior and low critical levels can be expected. Thus, the dynamic unstable behavior and the change in the critical point of the 3-free-nodes space truss system were analyzed in this work. The 4-th order Runge-Kutta method was used in the system analysis, while the change in the frequency domain was analyzed through FFT. The sinusoidal wave and the beating wave were utilized as the periodic load function. This unstable situation was observed by the case when all nodes had same load vector as well as by the case that the load vector had slight difference. The results showed the critical buckling level of the periodic load was lower than that of the constant load. The value is greatly influenced by the period of the load, while a lower critical point was observed when it was closer to the natural frequency in the case of a linear system. The beating wave, which is attributed to the interference of the two frequencies, exhibits slightly more behavior than the sinusoidal wave. And the changing of critical level could be observed even with slight changes in the load vector.

This paper examined the dynamic instability of a shallow arch according to the response characteristics when nearing critical loads. The frequency changing feathers of the time-domain increasing the loads are analyzed using Fast Fourier Transformation (FFT), while the response signal around the critical loads are analyzed using Hilbert-Huang Transformation (HHT). This study reveals that the models with an arch shape of h = 3 or higher exhibit buckling, which is very sensitive to the asymmetric initial conditions. Also, the critical buckling load increases as the shape increases, with its feather varying depending on the asymmetric initial conditions. Decomposition results show the decrease in predominant frequency before the threshold as the load increases, and the predominant period doubles at the critical level. In the vicinity of the critical level, sections rapidly manifest the displacement increase, with the changes in Instantaneous Frequency (IF) and Instant Energy (IE) becoming apparent.

PartI of this paper identified the location and size of the noise sources from the axial flow fans, and partII based on that, identified the magnitude of sound pressure from the case and the blade according to frequency in the range of 2200 Hz to 5000 Hz. The equation of Lighthill was used for calculation. Generally, when measuring noise, the analytical area was extended more than 1m from the outlet of the fan. To eliminate the effects of backflow coming from the rear of the fan, the analytical area was extended a little longer than 1m. From the results of the analysis, high noise occurs in the low frequency area, and the lower noise becomes in the high frequency area. The maximum sound pressure generated in the range of 2000Hz~5000Hz is 65dB at a distance of 1m and 82dB at the outlet of the fan. Noise of the fan mainly occurred around the blade and guide, and the noise decreased as the frequency increased between 2200Hz and 3400Hz, but the noise increased as the frequency increased between 3800Hz and 5000Hz.

선체구조의 품질검사 중 가장 일반적인 방법의 하나는 비파괴검사이다. 하지만 복합소재 선체는 강화재와 수지로 구성된 여러가지 재료가 섞여 있고 또 생산환경과 작업자에 따라 FRP(Fiber-Reinforced Plastics) 제작품질에 차이가 발생할 가능성이 크기 때문에 정확한 검사평가는 쉽지 않은 일이다. 특히 FRP 선박의 경우에는 다른 구조물보다 두께가 매우 두껍고 주로 수척층 공법을 이용하기 때문에 더욱 그렇다. 초음파 탐상의 조건 중 검사체의 밀도가 매우 중요하기 때문에 본 연구에서는 FRP 선박 제작에 널리 사용되고 있는 소재와 유리섬유강화재 중량 비율로 제작된 선박의 외판을 검사체로 선정하고, Pulse-Echo 초음파 탐상기를 활용하여 GFRP(Glass Fiber-Reinforced Plastics) 선체 외판의 초음파 탐상을 위한 적정 조건을 조사하였다. 1.00 MHz, 2.25 MHz, 5.00 MHz 세 종류 탐촉자로 A-Scan 을 실시하였으며 선체 외판의 두께 검사결과와 비교분석함으로써 적정 초음파 탐상 조건을 찾고자 하였다. 연구결과 탐촉자의 초음파 주파수가 높아질수록 수신자의 반사파 음향 속력을 감소시켜야 더 정도 높은 두께 측정 결과를 얻을 수 있었으며, 상대적으로 낮은 초음파 주파수 탐촉자에서 더 적은 오차가 발생함을 확인할 수 있었다.

본 연구의 목적은 원자로 1400(APR 1400) 원자력 발전소(NPP)의 원자로 격납건물(RCB) 내진성능에 대해 상이한 수치모델과 지진 주파수 성분의 영향을 평가하는 것이다. 집중 질량 막대 모델(lumped-mass stick model, LMSM)과 3차원 유한요소모델(threedimensional finite element model, 3D FEM)의 두 가지 수치 모델이 시간이력해석을 수행하기 위해 개발되었다. LMSM은 기존의 집중 질량 보-요소를 사용하여 SAP2000으로 구성하였으며, 3D FEM은 각기둥 입체-요소를 사용하여 ANSYS로 작성되었다. 저주파수 및 고주파수 성분을 고려한 두 그룹의 지진파를 시간이력해석에 적용하였다. 저주파수 지진파의 응답스펙트럼을 NRC 1.60의 설계 스펙트럼과 일치되도록 조정하여 작성하였으며, 고주파수 지진파는 10Hz ~ 100Hz의 고주파수 범위를 갖도록 생성하였다. RCB의 지진응 답은 다양한 높이에서 층응답스펙트럼으로 검토하였다. 수치해석 결과, 저주파수 지진에 의한 구조물의 FRS 결과는 두 수치 모델에 서 매우 유사한 결과를 보였다. 하지만, 고주파수 지진에 의한 LMSM의 FRS 결과는 고차 고유 주파수 영역에서 3D FEM과 큰 차이를 보였으며, RCB의 낮은 높이에서 명확한 차이를 보였다. 3D FEM이 정확한 구조물의 응답을 나타내는 것으로 가정한다면, RCB의 LMSM은 고주파수 지진에 의한 FRS 결과의 고차 고유 주파수 영역에서 일정 수준의 불일치성을 내포하고 있다.