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축소기법을 이용한 구조 시스템 식별 기법에 대한 연구 및 검증
성희준(Heejun Sung),장성민(Seongmin Chang),조맹효(Maenghyo Cho) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
The objective of system identification method is to match numerical model and real model with experimental data from sensor. In this study, measured modal data from sensor is applied for numerical model based system identification. Dynamic measurements from experiments are carried out from a limited number of accessible nodes, therefore condensation method is applied to construct full model. Method for system identification of real model is introduced and validated with experimental data. Vibration test for system identification will be applied and data from experiment will be used as primary degree of freedom information when constructing full matrices. Experimental validation demonstrates that the proposed method improves the accuracy and efficiency in structural system identification.
인공 신경 회로망을 이용한 구조 시스템 식별 기법 개발
성희준(Heejun Sung),조맹효(Maenghyo Cho) 대한기계학회 2017 대한기계학회 춘추학술대회 Vol.2017 No.11
Various system identification methods have been introduced through many manners by using numerical techniques to validate a complicated structures which have been described in FEM by comparing measured modal data. The objection of this work is to propose a method to identify a structure by comparing measured modal data to the numerical FEM data. Identified structures will improve the accuracy to the numerical model by minimizing the differences between those two models. Numerical base-line model is constructed by using FEM and will be compared to perturbed model by solving inverse problem. Measured modal responses, which are eigenvalues and eigenvectors, will be applied to satisfy the equilibrium and to minimize the differences of modal responses between the original model and the perturbed model. In this study, a neural networks-based detection method using modal properties is presented as a method for the identification which can effectively consider the modeling errors. Due to lack of number of the sensors, degrees of freedom-based reduction method has been applied to restore full model. As neural network has been applied for identification method, efficiency in calculation time is expected to improve.
Azobenzene liquid-crystalline polymer의 S-motion을 이용한 톱니바퀴 작동 메카니즘
김홍석(Hongseok Kim),성희준(Heejun Sung),김현수(Hyunsu Kim),조맹효(Maenghyo Cho) 대한기계학회 2018 대한기계학회 춘추학술대회 Vol.2018 No.12
Azobenzene liquid-crystal networks(LCNs) shrink under ultraviolet(UV) light irradiation and return to its original shape under visible light irradiation. We experimented one-way gear mechanism by using the LCN films. Generally used bending motions can not operate gear in one direction because the LCN film can be blocked by the teeth of the gear when returning to original position after it pushes the gear. Therefore, we attached an articulated device to the LCN film and separate the LCN film into the top part and the bottom part. First, the LCN film pushes the gear and become S shape by irradiating the top part of the LCN film when returning to the original position. By applying the proposed S motion, the LCN films can operate the gear in one direction without being jammed by the teeth of the gear. We have implemented the gear operating experiments and verified the proposed mechanism. We expect that the motion proposed in this study can be applied to various fields of the soft robot requiring precise fabrication or to the movement optimization fields to avoid obstacles.