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Digital Image Correlation: Advanced Methods and Applications PDF

125 Pages·2017·7.042 MB·English
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MATERIALS SCIENCE AND TECHNOLOGIES D I C IGITAL MAGE ORRELATION A M DVANCED ETHODS A AND PPLICATIONS No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services. M S ATERIALS CIENCE T AND ECHNOLOGIES Additional books in this series can be found on Nova’s website under the Series tab. Additional e-books in this series can be found on Nova’s website under the e-book tab. MATERIALS SCIENCE AND TECHNOLOGIES D I C IGITAL MAGE ORRELATION A M DVANCED ETHODS A AND PPLICATIONS DAVID CHAMBERS EDITOR Copyright © 2017 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. We have partnered with Copyright Clearance Center to make it easy for you to obtain permissions to reuse content from this publication. Simply navigate to this publication’s page on Nova’s website and locate the “Get Permission” button below the title description. This button is linked directly to the title’s permission page on copyright.com. Alternatively, you can visit copyright.com and search by title, ISBN, or ISSN. For further questions about using the service on copyright.com, please contact: Copyright Clearance Center Phone: +1-(978) 750-8400 Fax: +1-(978) 750-4470 E-mail: [email protected]. NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. Library of Congress Cataloging-in-Publication Data ISBN: (cid:28)(cid:26)(cid:27)(cid:16)(cid:20)(cid:16)(cid:24)(cid:22)(cid:25)(cid:20)(cid:20)(cid:16)(cid:27)(cid:28)(cid:20)(cid:16)(cid:28)(cid:3)(cid:11)(cid:72)(cid:37)(cid:82)(cid:82)(cid:78)(cid:12) Published by Nova Science Publishers, Inc. † New York CONTENTS Preface vii Chapter 1 Improving the Reliability of 2D DIC by Using Fourier-Mellin Transform 1 Oleksandr P. Maksymenko and Oleksandr M. Sakharuk Chapter 2 Incipient Necking Criteria for the Determination of Forming Limit Curves Using Digital Image Correlation 37 Gang Huang and Sriram Sadagopan Chapter 3 A Robust Optical Method for Tracking Mechanism Components 65 A. A. Cruz-Cabrera, M. Herzberg, M. Palaviccini, D. Z. Turner and S. Walkington vi Contents Chapter 4 Digital Image Correlation Applied to Analyze the Stress-Strain Evolution of Structural Materials under Compression 85 Alonso Saldaña Heredia, Pedro A. Márquez Aguilar and Arturo Molina Ocampo Index 111 PREFACE During surface deformations measurements in objects, materials or structural element samples, which move in the space, recorded speckle images are transformed by these displacements. In Chapter One, an algorithm for speckle image relative geometrical transformations parameters determination is proposed on the basis of Fourier-Mellin transform. Usage of this algorithm will allow increasing reliability of deformation fields’ determination for constructional materials after appropriate correction of speckle-images, which are used during calculations. In Chapter Two, methods are presented to determine forming limit curves (FLCs) for sheets of advanced high strength steels (AHSS) using digital image correlation (DIC). FLC is a valuable tool for failure prediction in forming simulation at design stage and die try-out in press shops. Chapter Three presents a novel algorithm for recovering the trajectories of mechanism components from high speed video by means of multidimensional simplex optimization and conformal templates. The focus of this chapter is on a simplex-based approach to digital image correlation (DIC) with arbitrarily shaped subsets that provides a number of advantages over the traditional gradient based approach with strictly square subsets. Finally, Chapter Four aims to develop a different technique that allows the obtention of the stress-strain evolution of materials while they are under axial loads. viii David Chambers Chapter 1 - During surface deformation measurements in objects, material or structural element samples, that move in space, recorded speckle images are transformed by such displacements. During measurement, relative rotations of a studied surface and change in distance between a video camera and lens typically occur. They cause recorded images relative rotations and scale changes. An algorithm for determining speckle image relative geometrical transformations parameters is proposed on the basis of the Fourier-Mellin transform. An image transformation parameter determined by this algorithm, can be used further to analyze spatial displacements of a control surface in relation to the recording system and to correct the speckle-images. Using this algorithm will improve the reliability of deformation field determination for constructional materials, after appropriate correction of the speckle-images used during calculations. Corrective parameter errors determination by the proposed algorithm was analyzed and their influence on the accuracy of real deformation field determination was demonstrated. Analytical error equations for determining speckle-image geometric transformation parameters were derived. According to these expressions, the errors depend on the image size and precision of sub-pixel accuracy algorithm used for determining cross-correlation peak coordinates. Computer simulation and experimental measurements were utilized for demonstrating the validity of the analytical estimations. The obtained results show that usage of a simple, inexpensive video camera with a resolution of 1280 × 1024 pixels and the developed algorithm can provide accurate parameters of speckle-image relative geometrical transformation. It was proven by experiment that errors of speckle-image relative rotation angle determination are linearly and inversely proportional to image size and are less than 0.01 degrees for the relative speckle-images rotation within a range of ± 5 degrees. The errors of scale detrmination do not exceed 0.1% for the speckle-image scale changes within ±0.5%. For unambiguous cross- correlation peak detection during the proposed algorithm realization, high- frequency filtering of speckle images spectrum amplitudes prior to log- polar transformations is recommended. A Hann spatial filter was used for this purpose. The conducted experiments also indicated that the developed Preface ix algorithm can be used successfully for determining the change in distance to an object control surface with a relative error of tenths of a percent. The optical system should be adjusted before measurement in order to establish the relationship between speckle-image scale change and distance. Chapter 2 - Forming limit curve (FLC) is a valuable tool for failure prediction in forming simulation at design stage and die try-out in press shops. In this chapter, methods are presented to determine FLCs for sheets of advanced high strength steels (AHSS) using digital image correlation (DIC). Dome tests were conducted on AHSS specimens using DIC system for strain measurement. Two incipient necking criteria are developed to determine the onset of localized necking by analyzing the strain history at critical locations. The first criterion is based on the time dependent characteristic of the incipient necking formation, and the second criterion uses the time and position relationship during the course of necking development of AHSS. The second incipient necking criterion has been implemented into the commercial DIC software Vic-3D (Correlated Solution Inc.). The measured FLCs for several AHSS were compared to the FLCs using ISO 12004-2, the conventional North American experimental measurements and empirical equations. The results of comparison revealed that FLCs using DIC are in good correlation with other existing data, thus validating the presented methodologies. Chapter 3 - This work presents a novel algorithm for recovering the trajectories of mechanism components from high speed video by means of multidimensional simplex optimization and conformal templates. The proposed method is robust in that it can be used for patterned or unpatterned components, parts with oblong shapes, and mechanisms that involve moving obstructions that block the camera’s field of view. The focus of this work is on a simplex-based approach to digital image correlation (DIC) with arbitrarily shaped subsets that provides a number of advantages over the traditional gradient-based approach with strictly square subsets. The authors demonstrate the effectiveness of the proposed approach for a number of complex problems that cannot be surmounted by traditional methods.

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