• Smart Structures and Systems
• /
• 제23권4호
• /
• pp.359-371
• /
• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
• /
• pp.932-938
• /
• 1987

The dynamic equations of robotic manipulators can be derived from either Newton-Euler equation or Lagrangian equation. Model parameters which appear in the resulting dynamic equation are the nonlinear functions of both the inertial parameters and the geometric parameters of robotic manipulators. The identification of the model parameters is important for advanced robot control. In the previous methods for the identification of the model parameters, the geometric parameters are required to be predetermined, or the robotic manipulators are required to follow some special motions. In this paper, we propose an approach to the identification of the model parameters, in which prior knowledge of the geometric parameters is not necessary. We show that the estimation equation for the model parameters can be formulated in an upper block triangular form. Utilizing the special structures, we obtain a simplified least-square estimation algorithm for the model parameter identification. To illustrate the practical use of our method, a 4DOF SCARA robot is examined.

• Journal of Electrical Engineering and Technology
• /
• 제4권3호
• /
• pp.365-369
• /
• 2009

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov's regularization method is then used to replace the original ill-posed problem with a well-posed problem. The simulation and experimental results are presented and compared.

• 대한기계학회논문집A
• /
• 제24권12호
• /
• pp.2899-2908
• /
• 2000

Methodology of volumetric error identification is presented to improve the accuracy of NC machine tools by using a reference artifact and a touch trigger probe. Homogeneous transformation matrix and kinematic chain are used for modeling the geometric and thermal errors of a three-axis vertical machining center. The reference artifact is designed and fabricated to identify the model parameters by machine tool metrology. Parameters in the error model are able to be identified and updated by direct measurement of the reference artifact on the machine tool under the actual conditions which include the thermal interactions of error sources. The proposed method can speed up and simplify volumetric error identification processes.

• 한국해양공학회지
• /
• 제24권1호
• /
• pp.123-132
• /
• 2010

This paper presents a prestress-loss monitoring technique for prestressed concrete (PSC) girder structures that uses a vibration-based system identification method. First, the theoretical backgrounds of the prestress-loss monitoring technique and the system identification technique are presented. Second, vibration tests are performed on a lab-scaled PSC girder for which the modal parameter was measured for several prestress-force cases. A numerical modal analysis is performed by using an initial finite element (FE) model from the geometric, material, and boundary conditions of the lab-scaled PSC girder. Third, a vibration-based system identification is performed to update the FE model by identifying structural parameters since the natural frequency of the FE model became identical to the experimental results. Finally, the feasibility of the prestress-loss monitoring technique is evaluated for the PSC girder model by using the experimentally measured natural frequency and numerically identified natural frequency for several prestress-force cases.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.2010-2014
• /
• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• Structural Monitoring and Maintenance
• /
• 제11권2호
• /
• pp.101-126
• /
• 2024

To avoid irregularities in buildings, design codes worldwide have introduced detailed guidelines for their check and rectification. However, the criteria used to define and identify each of the plan and vertical irregularities are specific and may vary between codes of different countries, thus making their implementation difficult. This short communication paper proposes a novel approach for quantifying different types of structural irregularities using a common parameter named as unified identification factor, which is exclusively defined for the columns based on their axial loads and tributary areas. The calculation of the identification factor is demonstrated through the analysis of rectangular and circular reinforced concrete models using ETABS v18.0.2, which are further modified to generate plan irregular (torsional irregularity, cut-out in floor slab and non-parallel lateral force system) and vertical irregular (mass irregularity, vertical geometric irregularity and floating columns) models. The identification factor is calculated for all the columns of a building and the range within which the value lies is identified. The results indicate that the range will be very wide for an irregular building when compared to that with a regular configuration, thus implying a strong correlation of the identification factor with the structural irregularity. Further, the identification factor is compared for different columns within a floor and between floors for each building model. The findings suggest that the value will be abnormally high or low for a column in the vicinity of an irregularity. The proposed factor could thus be used in the preliminary structural design phase, so as to eliminate the complications that might arise due to the geometry of the structure when subjected to lateral loads. The unified approach could also be incorporated in future revisions of codes, as a replacement for the numerous criteria currently used for classifying different types of irregularities.

• 한국강구조학회 논문집
• /
• 제24권1호
• /
• pp.119-128
• /
• 2012

본 연구에서는 실험적 모드해석 기법을 이용하여 외부환경에 직접 노출되어 있는 실제 철도판형교의 full-scale 동적 테스트가 수행되었다. 충격해머 모드실험에 의해 얻어진 철도판형교의 모드 매개변수를 유한요소해석으로부터 구한 고유진동수와 모드형상과 비교, 분석하였다. 실험적 모드해석에 의해 측정된 실험 데이터와 해석적 진동분석에서 얻어지는 출력만의 데이터를 교량 부재의 기하학적 특성 및 재료적 특성을 다양하게 고려하여 모델보정 테크닉에 적용하였다. 철도판형교의 실험적 모드해석 결과를 검증하기 위한 유한요소모델이 모드인식 기법을 이용하여 보정되었다. 실험 데이터와 유한요소해석 기준모델의 모델보정과정의 결과와 함께 부재특성의 변화를 통하여 이루질 수 있는 손상평가에 대한 기초적 데이터베이스가 제공된다.