• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.39-40
• /
• 2008

본 논문은 네트워크 기반 제어시스템(NCS: Networked Control Systems)모델매칭 제어기법을 적용한 효율적인 제어알고리즘을 제안한다. 비선형의 특징을 가지는 제어기 및 관측기의 시간지연을 Pade 근사법으로 선형화하여 선형시스템 이론을 적용한 모델매칭 제어기를 설계하였다. 또한, 제어기의 차수를 줄이기 위하여 저차시스템으로 근사화하여 그 타당성을 검증하였다. 제안한 제어알고리즘의 타당성 및 신뢰성을 검증하기 위하여 컴퓨터 시뮬레이션을 실시하였으며 기존의 PID 제어기법과 비교분석하였다.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.4
• /
• pp.221-232
• /
• 2023

This paper presents a novel convolutional neural network (CNN)-based approach for predicting bolt clamping force in the early bolt loosening state of bolted structures. The approach entails tightening eight bolts with different clamping forces and generating frequency responses, which are then used to create a similarity map. This map quantifies the magnitude and shape similarity between the frequency responses and the initial model in a fully fastened state. Krylov subspace-based model order reduction is employed to efficiently handle the large amount of frequency response data. The CNN model incorporates a regression output layer to predict the clamping forces of the bolts. Its performance is evaluated by training the network by using various amounts of training data and convolutional layers. The input data for the model are derived from the magnitude and shape similarity map obtained from the frequency responses. The results demonstrate the diagnostic potential and effectiveness of the proposed approach in detecting early bolt loosening. Accurate bolt clamping force predictions in the early loosening state can thus be achieved by utilizing the frequency response data and CNN model. The findings afford valuable insights into the application of CNNs for assessing the integrity of bolted structures.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.10a
• /
• pp.764-765
• /
• 2011

In this paper, rotordynamic analyses of the Campbell diagram, critical speeds, and harmonic responses for a TMP rotor system are performed. Since the finite element model of the TMP rotor system has a very large number of degrees of freedom because of its complex geometry, and dynamic analyses for investigating the critical speeds, stability, and harmonic response are repeated for various design parameters, model order reduction (MOR) is necessary to reduce the computational cost. The Krylov-based model order reduction via moment matching significantly speeds up the rotordynamic analyses for the TMP rotor system.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.1
• /
• pp.19-26
• /
• 2023

Because of the development of computational resources, an entire structure in which many components are combined can be analyzed. To do so, the calculation time and number of data points are increased. In many practical industry structures, there are many parts with repeated patterns. To analyze the repetitive structures effectively, a homogenization method is usually employed. In a homogenization module, including commercial programs, it is generally assumed that a unit cell is repeated in all directions. However, the practical industry structures usually have complicated, repeated patterns or structures. Complicated patterns are difficult to address using the conventional homogenization method. Therefore, in this study, a multilevel homogenization method was devised to consider complex regularities. The proposed homogenization method divides the structure into several areas and performs multiple homogenizations, resulting in a more accurate analysis than that provided by the previous method.