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image-based quality control - part 2: granulometric properties

BETON- UND STAHLBETONBAU 2023年第8期118卷 556-564页

作者： Schack, Tobias Coenen, Max Haist, Michael Leibniz Univ Hannover Inst Baustoffe Appelstr 9A D-30167 Hannover Germany

The changes in concrete technology necessary to achieve the climate protection targets will lead to a significant change in the concrete mixtures typically used. The raw materials used are becoming more diverse and complex. The use of recycled raw materials will also significantly increase the fluctuations in the properties of the raw materials. An Accurate and time-efficient determination of the granulometric properties of the aggregate is of crucial importance, especially for "eco-concretes", in order to ensure consistent quality characteristics. As a natural raw material, the aggregate is subject to certain fluctuations to which such optimized concrete compositions can react relatively sensitively. In the future, it will be necessary to determine possible quality deviations of the fresh concrete resulting from fluctuations in the raw materials in a time-efficient manner in order to be able to make appropriate adjustments in the production process as quickly as possible. This paper presents an image-based quality control for the digital evaluation of granulometric properties of the aggregate as a part oft he flow table test. Accordingly, the range of properties of the image-based method already presented in Part 1 of this paper is extended to a fully comprehensive digital quality control. This paper presents the image-based determination of the granulometric properties of the aggregate as a part oft he flow table test. The determination is based on the image-based quality control described in part 1 of this paper.

关键词： digital quality control image-based method flow table test consistency granulometry

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image-based quality conctrol-part1: consistency and paste content

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BETON- UND STAHLBETONBAU 2023年第4期118卷 220-228页

作者： Schack, Tobias Coenen, Max Haist, Michael Leibniz Univ Hannover Inst Baustoffe Appelstr 9A D-30167 Hannover Germany

Today, only very simple empirical test methods are available for quality conctrol of fresh concrete on the construction site or in the production plant. Corrective actions in the case of quality deviations are based on a subjective visual inspection and thus on the experience of the inspector. The standard test method in Europe is the flow table test. The consistency of the concrete is derived from the diameter of the spread out fresh concrete. In order to overcome the deficiencies of this subjective fresh concrete testing, an image-based method for determining (fresh) concrete properties was developed and validated. In addition to the diameter, extensive information can be derived from the surface properties of fresh conrete. In this paper, the image-based determination of the consistency and the paste content is explained. The image-based determination of granulometric properties (part 2) and the homogeneity of fresh concrete (part 3) will be presented in planned follow-up articles.

关键词： digital quality control image-based method flow table test consistency

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image-based approximation of derivatives of traditional differential metrics of angular distortion in map projections

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CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE 2023年第1期50卷 44-62页

作者： Yan, Jin Xu, Tiansheng Gao, Jing Li, Ni Gong, Guanghong Capital Univ Econ & Business Sch Management & Engn Beijing Peoples R China Beihang Univ State Key Lab Virtual Real Technol & Syst Beijing Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China

Map projections are imaging procedures used to depict geographic features. We adopt the traditional differential metric and exploit the intrinsic image properties of map projections to establish an image-based differential metric for evaluating distortions in map projections, obtaining an effective, practical, and relatively accurate metric. We use bivariate polynomial functions to approximate the forward and inverse formulae of map projections. Thereafter, the proposed metric is conveniently calculated using the partial derivatives of the approximate forward functions based on polynomial functions, while complicated differential calculations are avoided. Moreover, multiple sampling and image filters mitigate the influence of imaging noise and achieve a high computation precision. Experiments were conducted using the NASA *** mapping software to generate images from more than 200 map projections. Explicit equations of map projections were not required owing to the use of the mapping software. These images were then evaluated using the proposed metric through an implementation in the Julia programming language. The corresponding results confirmed that the proposed metric avoided the drawbacks of the great circle arc metric and provided considerably low errors (1.12 degrees on average) and high consistency (0.999 on average) with respect to the traditional differential metric. Although there were errors, experimental results indicated that feasibility and high usability were achieved by the image-based method for evaluating distortions in small-scale map projections.

关键词： Map projection distortion differential metric approximation image-based method polynomial function image filter

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Digital Slump Flow: image-based assessment of fresh concrete homogeneity as part of the slump flow test

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CASE STUDIES IN CONSTRUCTION MATERIALS 2024年 21卷

作者： Schack, Tobias Coenen, Max Haist, Michael Leibniz Univ Hannover Inst Bldg Mat Sci Hannover Germany

Worldwide, the standardized flow table test, the slump flow test or likewise methods are applied for the characterization of the workability of fresh concrete. These methods, however, give only very limited insight into the parameters controlling the workability of the concrete and important quality factors, such as e.g. the homogeneity of the concrete, cannot be quantified at all. The paper at hand presents a novel image-based approach for the determination of the homogeneity of fresh concrete as part of the slump flow test. Photogrammetric computer vision and artificial intelligence-based algorithms are proposed for the derivation of three-dimensional and semantic representations of the fresh concrete's slump cake. Characteristic values of the surface determined in this way are correlated with the criteria of the Visual Stability Index (VSI) according to ASTM C1611. Segregation was determined in image data by measuring the aggregate distribution gradient (ADGIA) on the surface and the separation of paste (dPaste) at the peripheral of the fresh concrete as part of the slump flow test. As shown in the results, the image-based method enables an automatic assessment of the homogeneity of fresh concretes during the flow test by deriving digital parameters related to the VSI.

关键词： Slump flow test Homogeneity image-based method Photogrammetric computer vision Digital quality control

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Assessment of the elastic properties of high-fired gypsum using the digital image correlation method

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CONSTRUCTION AND BUILDING MATERIALS 2022年 317卷 125945-125945页

作者： Mayo-Corrochano, Cristina Javier Sanchez-Aparicio, Luis Aira, Jose-Ramon Sanz-Arauz, David Moreno, Esther Pinilla Melo, Javier Univ Politecn Madrid Dept Construct & Technol Architecture DCTA Escuela Tecn Super Arquitectura Madrid ETSAM Av Juan Herrera 4 Madrid 28040 Spain

The main purpose of this work is to analyze the elastic properties (i.e. Young's modulus and Poisson's ratio) of gypsum specimens manufactured by traditional methods (non-industrial kilns). More specifically we have evaluated the Bajo Aragon variant by means of a low-cost digital image correlation approach. The accuracy of the data was contrasted with the press, obtaining an RMSE of 0.008%, corroborating the viability of the method. The results obtained during this experimental campaign revealed a gypsum with an average compressive strength, Young's modulus and Poisson's ratio of 4.01 MPa, 2989 MPa and 0.24 respectively.

关键词： High fired gypsum Elastic properties image-based method Digital image correlation Mechanical tests

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image-based effective medium approximation for fast permeability evaluation of porous media core samples

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COMPUTATIONAL GEOSCIENCES 2021年第1期25卷 105-117页

作者： Franc, Jacques Guibert, Romain Horgue, Pierre Debenest, Gerald Plouraboue, Franck Univ Toulouse Inst Mecan Fluides Toulouse CNRS IMFT Toulouse France

An image-based effective medium approximation (EMA) is developed so as to permit very fast transport properties evaluations of 3D porous media. From an image-based porous network (IBPN) built upon digital image processing of 3D binary images, we focus on throat's local geometrical properties at the pore scale, for being the most sensible structural units which build up the local pressure. This approach is a 3D image-based extension of the critical point approach proposed in 2D fractures. We show, from analyzing various core rock samples available in the literature, that the asymptotic assumptions associated with the preeminence of critical points in throats are indeed geometrically relevant. We then describe how the image-based EMA evaluated from the conductances computed from the discrete IBPN can be reliably evaluated. The proposed method is evaluated upon the estimation of core sample permeability from binarized image obtained using X-ray tomography. Since it combines digital image treatments with statistical data post-processing without the need of computational fluid dynamics (CFD) computation, it is extremely cost efficient. The results are compared with a micro-scale Stokes flow computation in various rock samples. The sensitivity to the pore discretization also is discussed and illustrated.

关键词： Porous media Effective properties image-based method Effective medium approximation Permeability

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Measuring blast fragmentation at Nui Phao open-pit mine, Vietnam using the Mask R-CNN deep learning model

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MINING TECHNOLOGY-TRANSACTIONS OF THE INSTITUTIONS OF MINING AND METALLURGY 2021年第4期130卷 232-243页

作者： Vu, Trong Bao, Tran Hoang, Quoc Viet Drebenstetd, Carsten Hoa, Pham Van Thang, Hoang Hung Quang Ninh Univ Ind Surface Min Dept Dong Trieu Quang Ninh Vietnam Hanoi Univ Min & Geol Surface Min Dept Hanoi Vietnam Cent South Univ Hunan Changsha Sch Resources & Safety Engn Changsha Peoples R China TU Bergakad Freiberg Surface Min Dept Freiberg Germany

Blast fragmentation size distribution is one of the most critical factors in evaluating the blasting results and affecting the downstream mining and processing operations in open-pit mines. image-based methods are widely applied to address the problem but require heavy user interaction and experience. This study deployed a deep learning model Mask R-CNN to develop an automatic measurement method of blast fragmentation. The model was trained using images captured from real blasting sites in Nui Phao open-pit mine in Vietnam. The trained model reported high average precision scores (Intersection over Union, IoU = 0.5) 92% and 83% for bounding box and segmentation masks, respectively. The results lay a solid technical basis for the automated measurement of blast fragmentation in open-pit mines.

关键词： Blast fragmentation measurement open-pit mine deep learning image-based method Mask R-CNN

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Real-Time Generation of Reflections in the Optimized image Space

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Chinese Journal of Electronics 2020年第5期29卷 812-818页

作者： ZHANG Yanci YU Hanyou XIE Ruilin MENG Xiaoyou REN Wenjie XIE Kaili LIU Yanli College of Computer Science Sichuan University

This paper proposes a novel imagebased method to generate real-time *** algorithm aims to solve the problem of missing reflections in previous screen space based methods *** of computing reflections in the image space decided by the current eye position,our method conducts most of the reflection calculations in a new image space,which is determined by a carefully chosen camera position at *** major criteria used to choose this optimized camera position is to make its corresponding image space contain as much as possible scene information to generate *** experimental results indicate that most of the missing reflections problems can be fixed by moving the reflection computations to this new image *** also prove that the performance gains achieved by executing computations in the new image space can cancel out most of the overhead to generate it.

关键词： image space time generation Ray marching image space G-buffer image-based method image processing cameras reflection calculations Reflections scene information camera position reflection computations

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Training image selection for development of subsurface geological cross-section by conditional simulations

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ENGINEERING GEOLOGY 2021年 295卷

作者： Shi, Chao Wang, Yu City Univ Hong Kong Dept Architecture & Civil Engn Kowloon Tat Chee Ave Hong Kong Peoples R China

Delineation of a subsurface geological cross-section can be accomplished by conditional simulations, which can effectively combine prior geological knowledge as training images with site-specific measurements for spatial interpolation. Valuable prior geological knowledge may be concisely represented by a single training image, and the evaluation and optimal selection of a representative training image is crucial for a successful application of conditional simulation methods. In this study, a data-driven method based on edge orientation detection is proposed for selection of the optimal training image. The stratigraphic soil boundaries of all candidate training images (CTIs) and site-specific measurements are scanned by an edge detector. The derived edge orientations are quantified and compared between CTIs and site-specific measurements. Among all CTIs, the CTI that has the minimal difference of edge orientation distribution with respect to the site-specific measurements is selected as the optimal one. The proposed method is validated using both an illustrative example and a real case. It is demonstrated that edge orientation successfully differentiates soil stratigraphic patterns between different training images, and the derived edge orientation distribution can be used as a quantitative indicator for selection of the optimal training image.

关键词： image-based method Sparse measurements XGBoost Edge orientation detection Convolutional neural network

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image-based Aspect Ratio Selection

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2019年第1期25卷 840-849页

作者： Wang, Yunhai Wang, Zeyu Fu, Chi-Wing Schmauder, Hansjorq Deussen, Oliver Weiskopf, Daniel Shandong Univ Jinan Shandong Peoples R China SIAT Shenzhen VisuCA Key Lab Shenzhen Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China Konstanz Univ Constance Germany Univ Stuttgart VISUS Stuttgart Germany

Selecting a good aspect ratio is crucial for effective 2D diagrams. There are several aspect ratio selection methods for function plots and line charts, but only few can handle general, discrete diagrams such as 2D scatter plots. However, these methods either lack a perceptual foundation or heavily rely on intermediate isoline representations, which depend on choosing the right isovalues and are time-consuming to compute. This paper introduces a general image-based approach for selecting aspect ratios for a wide variety of 2D diagrams, ranging from scatter plots and density function plots to line charts. Our approach is derived from Federer's co-area formula and a line integral representation that enable us to directly construct image-based versions of existing selection methods using density fields. In contrast to previous methods, our approach bypasses isoline computation, so it is faster to compute, while following the perceptual foundation to select aspect ratios. Furthermore, this approach is complemented by an anisotropic kernel density estimation to construct density fields, allowing us to more faithfully characterize data patterns, such as the subgroups in scatterplots or dense regions in time series. We demonstrate the effectiveness of our approach by quantitatively comparing to previous methods and revisiting a prior user study. Finally, we present extensions for ROI banking, multi-scale banking, and the application to image data.

关键词： Aspect ratio image-based method Federer's co-area formula density field anisotropic kernel density estimation

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