• Smart Structures and Systems
• /
• 제26권5호
• /
• pp.591-603
• /
• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• 한국정밀공학회지
• /
• 제22권6호
• /
• pp.144-151
• /
• 2005

Spin coater is regarded as a major module rotating at high speed to be used build up polymer resin thin film layer fur bonding process of GaAs wafer. This module is consisted of spin unit for spreading uniformly, align device, resin spreading nozzle and et. al. Specially, spin unit which is a component of module can cause to vibrate and finally affect to the uniformity of polymer resin film layer. For the stability prediction of rotation velocity and uniformity of polymer resin film layer, it is very important to understand the dynamic characteristics of assembled spin coater module and the dynamic response mode resulted from rotation behavior of spin chuck. In this paper, stress concentration mode and the deformed shape of spin chuck generated due to angular acceleration process are presented using analytical method for evaluation of structural safety according to the revolution speed variation of spin unit. And also, deformation form of GaAs wafer due to dynamic behavior of spin chuck is presented fur the comparison of former simulated results.

• Water Engineering Research
• /
• 제5권2호
• /
• pp.101-109
• /
• 2004

Aggregating information by combining forecasts from two or more forecasting methods is an alternative to using forecasts from just a single method to improve forecast accuracy. This paper describes the development and use of a monthly inflow forecast model based on an optimal linear combination (OLC) of forecasts derived from naive, persistence, and Ensemble Streamflow Prediction (ESP) forecasts. Using the cross-validation technique, the OLC model made 1-month ahead probabilistic forecasts for the Chungju multi-purpose dam inflows for 15 years. For most of the verification months, the skill associated with the OLC forecast was superior to those drawn from the individual forecast techniques. Therefore this study demonstrates that OLC can improve the accuracy of the ESP forecast, especially during the dry season. This study also examined the value of the OLC forecasts in reservoir operations. Stochastic Dynamic Programming (SDP) derived the optimal operating policy for the Chungju multi-purpose dam operation and the derived policy was simulated using the 15-year observed inflows. The simulation results showed the SDP model that updated its probability from the new OLC forecast provided more efficient operation decisions than the conventional SDP model.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2004년도 춘계학술대회
• /
• pp.114-119
• /
• 2004

Endbeam is an important structural member of freight bogie for the support of service loading. In general, more than 25 years' durability is necessary. However, endbeam occur fatigue fracture in dynamic stress concentration location because comparatively strength and stiffness are low. Therefore, structure analysis is performed to evaluate structural problem of endbeam and local strain range as durability analysis. The number of cycles is extracted concerning the bogie in operation by measurement dynamic stress time history on critical part which is crack initiation in actual fact. At this time rainflow cycle counting is used to consider change of stress for operating condition. Based on the fatigue life curves and the stress analysis, the fatigue life of the endbeam is predicted and compared with the experimentally determined fatigue life, resulting in a fairly good correlation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권10호
• /
• pp.3851-3866
• /
• 2015

The dynamic nature of opportunistic networks results in long delays, low rates of success for deliveries, etc. As such user experience is limited, and the further development of opportunistic networks is constrained. This paper proposes a prediction-based routing method for opportunistic networks (PB-OppNet). Firstly, using an ARIMA model, PB-OppNet describes the historical contact information between a node pair as a time series to predict the average encounter time interval of the node pair. Secondly, using an optimal stopping rule, PB-OppNet obtains a threshold for encounter time intervals as forwarding utility. Based on this threshold, a node can easily make decisions of stopping observing, or delivering messages when potential forwarding nodes enter its communication range. It can also report different encounter time intervals to the destination node. With the threshold, PB-OppNet can achieve a better compromise of forwarding utility and waiting delay, so that delivery delay is minimized. The simulation experiment result presented here shows that PB-OppNet is better than existing methods in prediction accuracy for links, delivery delays, delivery success rates, etc.

• Geomechanics and Engineering
• /
• 제13권6호
• /
• pp.997-1010
• /
• 2017

The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권4호
• /
• pp.1193-1215
• /
• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• 한국항해항만학회지
• /
• 제48권2호
• /
• pp.116-124
• /
• 2024

Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

• 한국강구조학회 논문집
• /
• 제21권3호
• /
• pp.267-275
• /
• 2009

본 논문에서는 기둥이 손실된 철골모멘트골조의 2경간 보의 동적거동 특성을 고찰하고 철골모멘트골조의 연쇄붕괴 예비평가를 위한 비선형 동적 근사해석법을 제안하였다. 기둥이 손실된 2경간 부분골조 모델의 동적거동의 분석을 통하여, 2경간 보의 중력하중과 보스팬-대-보춤 비가 최대 동적 변형요구의 지배적인 요소임을 확인하였다. 이를 토대로 2경간 보의 중력하중 변수와 최대 현회전각과의 관계를 기술하는 붕괴스펙트럼 개념을 새로이 제안하고 이의 활용법을 예시하였다. 3차원 비선형 동적 유한요소해석결과와 비교하여, 본 연구에서 제안한 방안이 용접 철골모멘트골조의 비선형 연쇄붕괴거동을 신속히 평가하는데 정확하면서도 매우 효율적임을 입증하였다.

• 대한교통학회지
• /
• 제29권1호
• /
• pp.71-79
• /
• 2011

전통적으로 동적 교통망 모형들은 실시간 교통운영 문제를 위한 도구로 인식되어 왔다. 이와 같은 모형들을 활용하는 방안 중 하나는 예측통행시간을 생성하는 것이다. 예측통행시간 정보는 통행자들이 혼잡한 지역에서 덜 혼잡한 지역으로 경로를 전환할 수 있도록 해 주는데 이는 교통망의 용량을 효과적으로 활용하게 한다. 이러한 접근 방법은 돌발상황이 발생했을 때 매우 효과적일 것으로 예상된다. 이 때 고려해야 할 사항은 통행시간정보가 미래 통행여건 자체에 영향을 준다는 점이다. 이로 인해 예기치 못한 과잉반응(over-reaction)을 야기할 수 있으며 예측정보의 신뢰도를 떨어뜨리는 요인으로 작용할 수도 있다. 본 연구에서는 돌발상황 발생 시를 대상으로 교통망 차원의 통행시간 예측모형을 제시한다. 이 모형에서는 모든 운전자가 개인 차내 단말기를 통해 상세한 교통정보를 이용할 수 있으며 이러한 정보를 바탕으로 경로선택에 관한 의사결정을 할 수 있다고 가정하였다. 경로기반(route-based)의 확률론적 변등부등식(stochastic variational inequality)을 통행시간예측의 기본모형으로 사용하였으며 운전자의 경로전환의사를 반영하기 위해 경로전환함수를 적용하였다. 컴퓨터 프로그램과 간단한 교통망 분석을 통해 제안된 모형의 특성을 살펴보았다.