Papers by Keyword: Defect Identification

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Authors: Ivan Gostev
Abstract: Methods of identification of the form of objects based on the signature analysis and invariant to affine transformations are considered. It is shown that these methods can be applied to surface quality assurance. Questions of sensitivity of these methods are considered. Dependences of these methods on noise are brought.
Authors: Ying Yin, G.Y. Tian, Guo Fu Yin, A.M. Luo
Abstract: Radiography inspection (X-ray or gamma ray) is one of the most commonly used Non-destructive Evaluation (NDE) methods. More and more digital X-ray imaging is used for medical diagnosis, security screening, or industrial inspection, which is important for e-manufacturing. In this paper, we firstly introduced an automatic welding defect inspection system for X-ray image evaluation, defect image database and applications of Artificial Neural Networks (ANNs) for NDE. Then, feature extraction and selection methods are used for defect representation. Seven categories of geometric features were defined and selected to represent characteristics of different kinds of welding defect. Finally, a feed-forward backpropagation neural network is implemented for the purpose of defect classification. The performance of the proposed methods are tested and discussed.
Authors: Du Hyung Cho, Seok Lyong Lee
Abstract: The defect inspection is a crucial process for the plasma display panel (PDP) production that significantly influences the quality of final products. In this paper, we propose a defect identification and classification method that extracts and classifies defects using various image analysis techniques. First, we identify defects through binarization of images using Gaussian filter. Then, those defects are classified into seven different types by analyzing geometric characteristics of defects and utilizing a support vector machine (SVM) classifier. The experimental results using separate sets of training and test PDP images obtained from production lines are quite promising. Our method identifies defects effectively enough to be used in the real environment. It also achieves a high correctness in classifying various types of defects.
Authors: Guang Feng Wang
Abstract: With the increasing popularization of the application of steel structure in the construction field of China, quality problem has become a major challenge of steel structure. Therefore, how to better control the quality of steel structure has been a very important issue in China now. In this paper, combined with the characteristics of steel structure engineering technology, how to better control the quality of steel structure installation projects is discussed and analyzed in depth.
Authors: Harshwardhan Pandit, Amrita Mangarulkar, Uday Dabade
Abstract: Each casting produced in a foundry is a research experiment, since no two castings have the exactly same values of their geometric, material and process parameters. By the time, castings are inspected the link to the originating (influencing) parameters is lost, since they are never systematically recorded and correlated with quality characteristics. Thus, a valuable opportunity to improve casting quality is lost. In this work, we present a systematic approach for classifying casting defects by correlating them with the originating parameters; the proposed classification approach is hierarchical and more comprehensive. The defects are classified under geometry, integrity and property related defects. The defects analysis system includes an expandable library of images to facilitate correct identification of a given defect, and presents the various causes and remedies based on the user inputs. The entire system is being implemented in a web-based environment for wide access to practicing foundry engineers.
Authors: M. Kokot, Jan Holnicki-Szulc
Abstract: A methodology of defect identification in linear DC circuits based on so called Virtual Distortion Method (VDM) will be presented. The proposed approach takes adventage of the analogy linking mechanical models of truss structures and electric circuits. In this paper we cover the issue of modelling defects in electric circuits by compatible state of distortions, next we introduce the concept of influence matrix Dij, which describes global sensitivity of the circuit and enables fast recalculation of system response, and we formulate a gradient method of defect identification (inverse problem) based on local current and voltage measurements. In the following analysis we focus on so-called impotent states of distortions, which are the source of ambiguity of solution. We show that these difficulties can be overcome by a proper measuring strategy.
Authors: Shinobu Yoshimura, G. Yagawa, A. Oishi, Kazumasa Yamada
Authors: Xiao Li He, Chong Liu
Abstract: A method used to recognize the inner defects of 3-D braided composite materials is discussed. Firstly, the link between UT signals and the defects of 3-D braided composite material is analyzed. Then, the wavelet packet transform is used to process the ultrasonic scanning pulse signals of the defects. The characteristic quantities of signal are extracted into the BP neural network as samples. Through training the BP neural network, the recognize system of micro-cracks and pores is achieved. Finally, according to the results of experiment this classification system based on wavelet packet transform is proved to be feasible.
Authors: Wen Chao Lv, Shao Ping Zhou, Ai Qiang Cui
Abstract: Because there are many mode transformations when the ultrasonic guided waves run into defects in the pipeline, the reflected signals got by means of the traditional ultrasonic guided wave technique are complex and the amplitudes are small. The time reversal method is a way to intercept the reflected signals in the initial results with a certain bandwidth and excite the time reversal guided waves on the corresponding nodes. In this way, energies of the guided wave are focused in time and space. By comparing the accuracy of defects identification in the straight pipes and the bent pipes with the traditional ultrasonic guided wave method and the time reversal method, this paper proves that the time reversal method has many advantages over the tradition ultrasonic guided wave method. The time reversal method overcomes disadvantages of the traditional guided wave technique and improves the identification degree and accuracy of defects effectively. It lays the foundation for the final defect identification.
Authors: Antonio Forn, Sergi Menargues, Enric Martín, Josep A. Picas
Abstract: This work is a contribution to improve the knowledge of components behavior produced by semi-solid processes particularly the Sub-Liquidus-Casting process. Die design was supported by using the Procast simulation program. The effect of the different variables of the process in structural integrity of the product has been described and analyzed. The components were produced using A356 alloy formed on a pilot plant with a 400 Ton THT press. The components study was made by RX, metallographic analysis and mechanical tests. The effects of T5 and T6 heat treatments were also studied.
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