人工砂混凝土性能试验研究

采用正交试验方法配制了不同人工砂取代率、石粉含量、粉煤灰含量的混凝土, 对比了每组混凝土的坍落度, 研究了3 d、28 d龄期混凝土的抗压性能。结果表明: 最优配比的人工砂取代率、石粉含量和粉煤灰含量分别为10%、3%和5%, 此时28 d抗压强度为40.1 MPa, 满足30 MPa的混凝土设计强度。     

Identification of digital technologies and digitalisation trends in the mining industry

Digitalisation in mining refers to the use of computerised or digital devices or systems and digitised data that are to reduce costs, improve business productivity, and transform mining practices. However, it remains increasingly difficult for mining companies to decide which digital technologies are most relevant to their needs and individual mines. This paper provides an overview of digital technologies currently relevant to mining companies as presented and discussed by mining journals, the media and insight reports of leading consultancy agencies. Relevant technologies were systematically identified using text-mining techniques, and network analyses established the relations between significant technologies. Results demonstrated that currently 107 different digital technologies are pursued in the mining sector. Also, an analysis of the actual implementation of digital technologies in 158 active surface and underground mines reveals a limited uptake of digital technologies in general and that the uptake increases with the run-of-mine production. Large-scale mining operations appear to select and apply digital technologies suitable to their needs, whereas operations with lower production rates do not implement the currently available digital technologies to the same extent. These minor producers may require other digital transformation solutions tailored to their capabilities and needs and applicable to their scale of operations.     

基于人工神经网络的柴油机失火故障诊断

车载诊断系统在诊断失火故障时,采用基于曲轴段角加速度和阈值规则相结合的方法,该方法在内燃机高速轻载运行时诊断单缸完全失火工况存在一定的局限性。通过对比分析失火和正常工况下曲轴瞬时转速的幅频和相频特征,提取不同谐次的幅值和相位信息,结合人工神经网络作为故障模式识别工具,得到了一种改善方法。通过台架实验,对此改善方法进行了单缸完全失火、两缸完全失火和单缸一定程度失火的故障诊断测试。结果表明,在实验条件下该方法可以有效识别不同的失火模式,并可在单缸失火模式下实现失火程度判别。同时,该方法通过少量工况数据训练神经网络,即可实现一定转速范围内的失火诊断,可行性强,可用于发动机失火故障在线诊断。     

基于高斯混合隐马尔科夫模型与人工神经网络的紧急换道行为预测方法

为了有效降低因驾驶员紧急换道行为而诱发的交通事故，提高道路交通事故链阻断效率，提出一种基于高斯混合隐马尔科夫模型（GMM-HMM）和人工神经网络（ANN）的紧急换道行为预测方法。首先利用GMM-HMM对车辆行驶状态以及驾驶行为连续观察序列进行换道意图辨识，采用ANN预测下一时段的驾驶行为，再预测换道过程中的横向加速度变化率，从而判断紧急换道的危险程度。驾驶员在环仿真实验及实车实验结果表明，该方法预测避险成功率达92.83%，实验避险成功率达90.32%。该方法能有效地对紧急换道行为进行提前警告与干预。     

SFEP文本因果关系提取及其与SFN转化研究

为将系统故障演化过程(system fault evolution process，SFEP)的文本描述转化为空间故障网络(space fault network，SFN)结构，用于故障分析，本文提出SFEP文本因果关系提取方法，及其与SFN基本结构的转化方法。首先给出SFEP中事件的几种典型因果关系。随后提出因果关系与SFN基本结构的转化流程。本文方法围绕着关键字和因果关系组模式展开，通过模型的不断学习补充和丰富关键字和组模式。最终使方法具备将SFEP文本转化为SFN结构的能力。以飞机起落架故障发生过程文本为例进行了应用，实验结果表明该方法可用于SFEP文本中的因果关系分析，并得到了理想的SFN。完善的关键字和组模式有利于使用计算机智能处理SFEP的SFN。     

直流电对7B04铝合金固溶与时效组织和性能的影响

本文采用拉伸试验、扫描电子显微镜(SEM)和透射电子显微镜(TEM)等手段,研究了7B04铝合金在施加和不施加直流电条件下,经470℃固溶和100-140℃时效处理后的组织和力学性能。与传统的T6处理(470 oC/30 min+120 oC/24h)相比,固溶和/或时效处理时施加500A的电流,可显著提高GPII区的析出密度,进而提高峰时效状态下的拉伸强度和延伸率。固溶过程中施加直流电可将随后时效合金达到峰值强度的时间明显缩短12h。     

Using hybridized ANN-GA prediction method for DOE performed drying experiments

Abstract

Coal is an important component in the energy industry and plays a key role in energy-producing facilities. Moisture is a common condition that has a considerable impact on coal. Coal drying has long been a question of great interest in a wide range of fields. Defining parameters in the coal drying is obtained by experiments. High costs, time constraints, and repetition of an experiment are one of the most frequently stated problems with experimental works. Using qualitative methods with experiments can be more useful for identifying and characterizing the coal drying process. The purpose of this article is finding the effective parameters in the coal drying process by using a hybridized prediction method. Genetic Algorithm (GA) and Artificial Neural Network (ANN) are hybridized with each other to identify and characterize the coal drying process. GA-ANN algorithm is applied to the coal drying process to predict the moisture of coal, but it does not provide a decent result at first. Later, the Design of Experiment (DoE) methodology is performed to determine the main effects of six parameters. Two scenarios are generated because two parameters are not statistically significant. The first scenario excludes the air relative humidity parameter, and the second scenario excludes the air relative humidity and the velocity of air parameters. Following the application of the DoE method, GA-ANN reaches decent results in scenario-2.     

回转窑人工智能专家系统的应用实践

根据水泥熟料煅烧过程操作控制原理研发的"回转窑人工智能专家系统"采用了人工智能模拟技术、实时数据清洗技术、控制数据关联匹配技术。该系统由分解炉出口温度自动控制系统、篦速自动控制系统和氨水用量自动控制系统三个模块组成。该系统投运后,分解炉出口温度控制有效率由之前人工控制的平均60%~70%提高至平均80%~95%;篦下压力和二次风温稳定性提高;氨水消耗量下降显著;窑系统投料量增加10 t/h左右,熟料标准煤耗降低2.85 kg/t,熟料强度均有提高。     

地外人工光合成材料研究进展

太空探索已成为人类共同目标,重返月球、载人火星等人类历史上的重大里程碑任务已逐步实施。如何实现地外极端环境下人类生存和发展已成为载人太空探索的基本能力和基础技术。由南京大学和钱学森空间技术实验室提出的地外人工光合成技术,模拟地球绿色植物的自然光合作用,利用密闭空间废弃资源或地外天体环境中丰富的资源,通过光电催化方法原位、加速、可控地将二氧化碳转化成为氧气和含碳燃料,大幅度降低载人航天器的物资供应需求,支撑可承受、可持续的载人深空探索。本文回顾了近年来国际航空航天领域利用二氧化碳转换生成氧气和碳氢燃料的现有方法,并深入探讨面向地外原位资源利用的人工光合成材料研究进展,期望深化对地外人工光合成材料与技术的认知,有力支撑载人航天发展。     

Invasion and Defense Interactions between Enzyme‐Active Liquid Coacervate Protocells and Living Cells

The design and construction of mutual interaction models between artificial microsystems and living cells have the potential to open a wide range of novel applications in biomedical and biomimetic technologies. In this study, an artificial form of invasion‐defense mutual interactions is established in a community of glucose oxidase (GOx)‐containing liquid coacervate microdroplets and living cells, which interact via enzyme‐mediated reactive oxygen species (ROS) damage. The enzyme‐containing coacervate microdroplets, formed via liquid–liquid phase separation, act as invader protocells to electrostatically bind with the host HepG2 cell, resulting in assimilation. Subsequently, the glucose oxidation in the liquid coacervates initiates the generation of H₂O₂, which serves as an ROS resource to block cell proliferation. As a defense strategy, introduction of catalase (CAT) into the host cells is exploited to resist the ROS damage. CAT‐mediated decomposition of H₂O₂ leads to the ROS scavenging and results in the recovery of cell viability. The results obtained in the current study highlight the remarkable opportunities for the development of mutual interacting communities on the interface of artificial protocells/living cells. They also provide a new approach for engineering cellular behaviors through exploiting artificial nonliving microsystems.