不同干密度尾矿料压缩特性探究

为研究不同干密度尾矿料的压缩特性,采用筛分法将尾矿料分别配制成不同干密度的尾矿砂及尾矿土,进行渗透、压缩试验。试验表明:尾矿砂的沉降主要发生在施加荷载的早期阶段,且沉降量较大。压缩模量随着干密度的增大而增大,压缩系数随着干密度的增大而减小,在相同压力增量下,尾矿土的压缩性更强。     

A tutorial on the segmentation of metallographic images: Taxonomy,new MetalDAM dataset,deep learning-based ensemble model,experimental analysis and challenges

Image segmentation is an important issue in many industrial processes, with high potential to enhance the manufacturing process derived from raw material imaging. For example, metal phases contained in microstructures yield information on the physical properties of the steel. Existing prior literature has been devoted to develop specific computer vision techniques able to tackle a single problem involving a particular type of metallographic image. However, the field lacks a comprehensive tutorial on the different types of techniques, methodologies, their generalizations and the algorithms that can be applied in each scenario. This paper aims to fill this gap. First, the typologies of computer vision techniques to perform the segmentation of metallographic images are reviewed and categorized in a taxonomy. Second, the potential utilization of pixel similarity is discussed by introducing novel deep learning-based ensemble techniques that exploit this information. Third, a thorough comparison of the reviewed techniques is carried out in two openly available real-world datasets, one of them being a newly published dataset directly provided by ArcelorMittal, which opens up the discussion on the strengths and weaknesses of each technique and the appropriate application framework for each one. Finally, the open challenges in the topic are discussed, aiming to provide guidance in future research to cover the existing gaps.     

Formation mechanism of maze-like open macropores in Mn3O4 microspheres by heating in water vapor and their single-particle compressive behavior

Thermal decomposition of inorganic salts, such as carbonates, oxalates, and nitrates, is a facile method for synthesizing porous oxides; however, it typically produces either micropores or mesopores with sizes below 50 nm. Macropores larger than 50 nm can capture fine particles from a liquid or gas flow and thus be employed not only for environmental purification but also for the preparation of functional composites. In this study, we investigate the role of water vapor in the formation of macroporous Mn₃O₄ by the thermal decomposition of MnCO₃. It is found that water vapor accelerates the decomposition of MnCO₃ and subsequent particle growth as well as the conversion of manganese oxides at lower temperatures than in air. As a result, maze-like open macropores are formed by the randomly growing primary particle walls. Single-particle compressive tests reveal that small microspheres with sizes of 3 µm are easily deformed to relieve compressive stress. The macropore formation through the thermal decomposition of MnCO₃ in water vapor and microstructural tuning of the pore size, particle size ratio, and degree of curvature of interior walls can potentially expand the application range of porous oxide materials.     

An enhancement algorithm based on adaptive updating template with Gaussian model for Si3N4 ceramic bearing roller surface defects detection

The method based on machine vision image processing is used to detect the surface defects of Si₃N₄ bearing roller. Owing to the variety of defects, small area and low contrast, it is easy to miss or error detection. In this paper, an adaptive update template defect enhancement algorithm based on Gaussian model is proposed. First, a large number of surface images of Si₃N₄ bearing roller are collected to obtain the non-defect background statistical feature, and the background characteristic curve is fitted by Gaussian model. Further, the initial background template is gained according to the Gaussian curve. Then, combined with the gray distribute of defect images and initial background template, unique adaptive update template can be established. Finally, subtraction operation and nonlinear enhancement are used to improve the comparison of defect information and background. Through inverse sorting, adaptive threshold segmentation and Canny operation, the precise positioning of defects is realized. The enhancement algorithm can effectively enhance the contrast and eliminate the influence of noise. The average detection time is 0.84s, and the detection accuracy is 96.2%.     

HYDRIDE4MOBILITY: An EU HORIZON 2020 project on hydrogen powered fuel cell utility vehicles using metal hydrides in hydrogen storage and refuelling systems

The goal of the EU Horizon 2020 RISE project 778307 “Hydrogen fuelled utility vehicles and their support systems utilising metal hydrides” (HYDRIDE4MOBILITY), is in addressing critical issues towards a commercial implementation of hydrogen powered forklifts using metal hydride (MH) based hydrogen storage and PEM fuel cells, together with the systems for their refuelling at industrial customers facilities. For these applications, high specific weight of the metallic hydrides has an added value, as it allows counterbalancing of a vehicle with no extra cost. Improving the rates of H₂ charge/discharge in MH on the materials and system level, simplification of the design and reducing the system cost, together with improvement of the efficiency of system “MH store-FC”, is in the focus of this work as a joint effort of consortium uniting academic teams and industrial partners from two EU and associated countries Member States (Norway, Germany, Croatia), and two partner countries (South Africa and Indonesia).The work within the project is focused on the validation of various efficient and cost-competitive solutions including (i) advanced MH materials for hydrogen storage and compression, (ii) advanced MH containers characterised by improved charge-discharge dynamic performance and ability to be mass produced, (iii) integrated hydrogen storage and compression/refuelling systems which are developed and tested together with PEM fuel cells during the collaborative efforts of the consortium.This article gives an overview of HYDRIDE4MOBILITY project focused on the results generated during its first phase (2017–2019).     

Online Detection of Ellipsoidal Bubbles by an Innovative Optical Approach

Bubble and droplet size distribution influence chemical processes markedly. In order to enable an in‐line analysis of these distributions, a new single‐sided endoscopic version of the Optical Multimode Online Probe (OMOP) was developed. The acquired images are analyzed to gain bubble size distributions (BSDs) and main diagonals. A specific workflow was developed to detect and analyze overlapping bubbles based on standard image processing techniques. It can handle overlapping bubbles of both circular and elliptical shapes. Results confirmed that the combination of OMOP and the image processing workflow leads to robust detection of bubbles from two‐dimensional images. The new single‐sided OMOP proved to be a suitable tool for the acquisition of a BSD at industrial scale within a reasonable computing time.     

Bottom-up image detection of water channel slope damages based on superpixel segmentation and support vector machine

The operation of water supply channels is threatened by the occasionally occurred slope damages. Timely detection of their occurrence is critical for the rapid enforcement of mitigation measures. However, current practices based on routine inspection and structural heath monitoring are inefficient, laborious and tend to be biased. As an attempt to address the limitations, this paper proposes a bottom-up image detection approach for slope damages, which includes four steps, i.e. superpixel segmentation, feature handcrafting, superpixel classification based on support vector machine (SVM), and slope damage recognition. The approach employs a bottom-up strategy to infer the upper-level slope condition from the classification results of individual superpixels in the bottom level. Experiments were conducted to demonstrate the effectiveness of the approach. The handcrafted feature “LBP + HSV” was demonstrated to be effective in characterizing the image features of slope damages. An SVM model with “LBP + HSV” as input can reliably identify the slope condition in superpixels. Based on the SVM model, the bottom-up strategy achieved high recognition performance, of which the overall accuracy can be up to 91.7%. The proposed approach has potential to facilitate the early and comprehensive awareness of slope damages along the entire route of water channel by the integration with unmanned aerial vehicles.     

Modified OFS-RDS bat algorithm for IFS encoding of bitmap fractal binary images

This work is an extension of a previous paper (presented at the Cyberworlds 2019 conference) introducing a new method for fractal compression of bitmap binary images. That work is now extended and enhanced through three new valuable features: (1) the bat algorithm is replaced by an improved version based on optimal forage strategy (OFS) and random disturbance strategy (RDS); (2) the inclusion of new similarity metrics; and (3) the consideration of a variable number of contractive maps, whose value can change dynamically over the population and over the iterations. The first feature improves the search capability of the method, the second one improves the reconstruction accuracy, and the third one computes the optimal number of contractive maps automatically. This new scheme is applied to a benchmark of two binary fractal images exhibiting a complex and irregular fractal shape. The graphical and numerical results show that the method performs very well, being able to reconstruct the input images with high accuracy. It also computes the optimal number of contractive maps in a fully automatic way. A comparative work with other alternative methods described in the literature is also carried out. It shows that the presented method outperforms the previous approaches significantly.     

An application of metadata-based image retrieval system for facility management

For facility management, photography is an efficient and accurate method of recording the physical state of infrastructure. However, without an effective organizational scheme, the difficulty of retrieving relevant photos from historical databases can become overly burdensome for highly complex or long-lived assets. To make strategic decisions, it is crucial to retrieve the right information from a plurality of sources in a timely manner. The main objective of this paper is to present a method for organizing and retrieving photos from massive facility management photo databases using photo-metadata: photographed location, camera perspective, and image semantic content information. Indoor localization experiments were performed using Bluetooth technology to infer the location information. Perspective is inferred from the device’s on-board inertial measurement unit (IMU). Image semantic content is inferred using a Convolutional Neural Network (CNN)-based deep learning algorithm. Fusing these three features, seven query options were provided for the user when retrieving images. Leveraging Building Information Modeling (BIM) as a process and Geographic Information Systems (GIS) as a framework, this paper also envisions a federated information management by connecting 2D and 3D facility assets with our real-world map which can be smoothly bridged with our image retrieval system. The realization of the integrated application with BIM and GIS is significantly beneficial for the facility management domain by advancing the understanding of projects in a broader view with a federated data platform. In this research, the framework is illustrated with 21 institutional buildings within the University of Texas at Austin’s main campus, and the authors conclude that the proposed metadata-based image retrieval system can ultimately enhance the better-informed decision-making process through rapid information retrieval.     

Application of intensive hydrodynamic cavitation in liquids for synthesis of hydrogen and nanoparticles

In this paper, the results of experimental studies of hydrogen and nanoparticles production using intensive hydrodynamic cavitation in liquids are presented. Physicochemical processes occurring in a cavitation bubble at the last stage of its compression are very similar to processes occurring in the explosion chamber.The values of pressure and temperature achieved in this case ensure the thermodynamic stability of the reaction products and the production of a gaseous hydrogen and nanoclusters as a result of decomposition of molecules of liquid, which is confirmed by theoretical calculations.The controlled addition of hydrogen-containing liquids and the change in the compression conditions of cavitation bubbles make it possible to control the process of hydrogen synthesis, which is an important step in the development of modern high-tech alternative energy methods.The pulsation of a spherical cavity is described by the Kirkwood – Bethe equations, which are one of the most accurate mathematical models of pulsation processes at an arbitrary velocity of the cavity boundary. The model allows to describe the process of pulsations of cavitation cavities, conduct comprehensive parametric studies and evaluate the effect of various process parameters on the collapse of cavities.This work continues with the experiments on cavitation synthesis of carbon nanostructures. With the rapid movement of chemically pure hydrocarbons along the profiled channel in the form of a Venturi nozzle, cavitation bubbles form in the liquid, which are then compressed in the working chamber, in which a sharp pressure surge is created. The pressure in the shock wave, which reaches 80–90 MPa, ensures the collapse of cavitation bubbles close to adiabatic compression. As a result of the number of rapidly occurring physicochemical processes of evaporation, heating, and thermal dissociation of hydrocarbon vapors, a solid carbon phase including graphene oxide nanoparticles and a gaseous hydrogen-containing phase are synthesized in the cavitation, which is then subjected to separation. Synthesized graphene oxide nanoparticles possess activated surface due to the cavitation action and can be subsequently used as substrates for modification with functional nanoparticles, e.g. silver nanoparticles with antibacterial properties.The article is of great help to scientists and design engineers who are engaged in the development of promising hydrogen generating facilities and hydrogen complexes.