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Investigation on Pulverized Coal Combustion Behavior by Non-Isothermic Integral Thermogravimetry Method

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Journal of Iron and Steel Research International 2011年第8期18卷 1-8页

作者： QI Cheng-lin ZHANG jian-liang lin Xiang-hai LIU Qin-yuan WANG Xiao-liu School of Metallurgical and Ecological Engineering University of Science and Technology Beijing Beijing 100083 China

The combustion process of pulverized coal was investigated by non-isothermic integral thermogravimetry. The thermogravimetry curves were fitted by the Coats-Redferm approximation function, and kinetic parameters and characteristic temperatures were obtained. The optimal mixing ratio and particle size can be ascertained. The characteristic temperature of pulverized coal can be obtained from the thermogravimetry curve, and the combustion of coal can be divided into homogeneous and heterogeneous combustion according to the differential thermal analysis curve. The activation energy of a single type of coal ranking from low to high is as follows： bituminous coal, meager-lean coal, and anthracite. In the first mixing method, with more low-price meager-lean coal B replacing high price anthracite A, the activation energy slightly decreases; with more bituminous coal replacing meager-lean coal, total tendency makes a declining of activation. In the later mixing method, with an increase in particle size, a declining activation energy can be seen in total tendency.

关键词： pulverized coal combustion themogravimetry kinetics mixed-coal granularity coal combustion

Microstructure evolution and mechanical properties of high-boron steel with different ratios of boron and carbon

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China Foundry 2022年第2期19卷 169-176页

作者： Ming-chen Ma Chao-qing Luo Si-min Chen Hong-qun Tang Shan-shan Hu Yu-mei Zhou jian-lin liang Guangxi Key Laboratory of Processing for Nonferrous Metals and Featured Materials Center of Ecological Collaborative Innovation for Aluminium Industry in GuangxiSchool of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China School of Mechanical Engineering Guangxi UniversityNanning 530004China School of Mechatronic Engineering Guangdong Polytechnic Normal UniversityGuangzhou 510665China

Boron and carbon contents are the main factors influencing the properties of high-boron *** this study,experimental samples with different boron-to-carbon ratios(%B/%C)were *** microstructures of the different samples were observed,and their hardness,bending strength,and impact toughness were *** show that the main microstructures in the investigated high-boron steel samples are the eutectic Fe_(2)B structure with a fishbone shape and the ternary peritectic Fe_(3)(C,B)structure with a chrysanthemum *** the boron content is 2.5wt.%and the carbon content is 0.43wt.%(i.e.,%B/%C=5.82),the overall mechanical properties of the alloy are the *** alloy's hardness,bending strength and impact toughness reach their maximums,which are 67.3 HRC,1,267.36 MPa and 6.19 J·cm^(-2),*** optimized alloy is compared with conventional materials exhibiting excellent wear resistance(namely,high-manganese steel and high-chromium cast iron)through two-body and three-body abrasion *** wear resistance of this high-boron steelinvestigated in this work is found to be superior to those of the more common materials.

关键词： high-boron steel boron and carbon contents wear resistance microstructure mechanical properties

Pressureless Sintered 3Y-TZP/20%Al_2O_3 Composite Ceramic

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Journal of Central South University 2000年第1期12卷 12-14页

作者： YIN Bang yao,WANG ling sen,lin jian liang,ZHANG Jing shen,FAN Yi (State Key Laboratory for Powder Metallurgy, Central South University of Technology, Changsha 410083, China) 1. State Key Laboratory for Powder Metallurgy Central South University of Technology 410083 Changsha China

Nanometer 3Y TZP/20%Al 2O 3 (mass fraction) composite powders prepared by the chemical coprecipitation method were pressureless sintered at 1550 ℃ for 2 h. Effects of calcining temperatures at 800 ℃, 1 000 ℃, and 1 200 ℃ on phase structure, relative density, and Vicker′s hardness of the sintered bodies were studied. The results show that 1 000 ℃ was the optimal calcining temperature,and the powder calcined was composed of tetragonal zirconia with the Scherrer crystalline size of 6.3 nm. The relative density was up to 98.5% under pressureless sintering, and the sintered body was t ZrO 2(without m ZrO 2)+α Al 2O 3 with the average size of 0.4 μm.

关键词： pressureless sintering 3Y-TZP/20%Al_2O_3 composite phase structure

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一维下料问题的AB分类法

计算机应用 2009年第5期29卷 1461-1463,1466页

作者：林健良华南理工大学理学院广州510640

为了解决大规模的一维下料问题的计算困难,根据一维下料问题的特点,把贪心算法和随机搜索技术有机地结合起来,利用随机搜索技术对贪心算法进行了有效的改进,提出了一种简单实用的AB分类法。实验表明,该算法对规模较大的问题也能较快地... 详细信息

为了解决大规模的一维下料问题的计算困难,根据一维下料问题的特点,把贪心算法和随机搜索技术有机地结合起来,利用随机搜索技术对贪心算法进行了有效的改进,提出了一种简单实用的AB分类法。实验表明,该算法对规模较大的问题也能较快地获得问题最优解或精度较高的近似最优解。

关键词：一维下料问题贪心算法优化随机搜索

改进的最大-最小蚂蚁算法在有时间窗车辆路径问题中的应用

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计算机集成制造系统 2005年第4期11卷 572-576页

作者：万旭林健良杨晓伟华南理工大学应用数学系广东广州510640

利用最大-最小策略,最大最小蚂蚁算法减小了蚂蚁算法陷入局部陷阱的可能性。基于对最大最小信息素策略和信息素更新方式的改进,结合快速产生初始解的算法,提出了一种新方法。把该方法应用于有时间窗车辆路径问题,试验结果表明该算法是... 详细信息

利用最大-最小策略,最大最小蚂蚁算法减小了蚂蚁算法陷入局部陷阱的可能性。基于对最大最小信息素策略和信息素更新方式的改进,结合快速产生初始解的算法,提出了一种新方法。把该方法应用于有时间窗车辆路径问题,试验结果表明该算法是有效的。

关键词：蚂蚁算法车辆路径问题时间窗

Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping lin Jun Xu Delong jiang Jiayang Hou Ying liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

基于带收缩因子的粒子群优化算法的二重数值积分

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计算机应用 2011年第11期31卷 3094-3096页

作者：施美珍林健良华南理工大学理学院广州510640

提出了基于带收缩因子的粒子群优化(PSO-CF)算法求解二重数值积分的方法。PSO-CF算法初始时在积分区域内随机选取一定的分割点,粒子的速度采用收缩因子进行更新,粒子将朝着更好的位置移动。该算法基于分割后的每一个小矩形的4顶点和4内... 详细信息

提出了基于带收缩因子的粒子群优化(PSO-CF)算法求解二重数值积分的方法。PSO-CF算法初始时在积分区域内随机选取一定的分割点,粒子的速度采用收缩因子进行更新,粒子将朝着更好的位置移动。该算法基于分割后的每一个小矩形的4顶点和4内点及中心点定义适应值,用来评价粒子的优劣,通过反复迭代优化粒子。PSO-CF算法对最优粒子采用复化4内点公式计算二重数值积分。仿真实例表明,该算法积分精度较高,效果良好。

关键词：二重数值积分优化粒子群优化算法收缩因子代数精度

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新的决策树构造方法

计算机工程与应用 2009年第10期45卷 141-143页

作者：张凤莲林健良华南理工大学数学科学学院广州510640

决策树算法是数据挖掘中的一个比较活跃的研究领域,是对分类问题进行深入分析的一种方法。但构造最优决策树是一个NP难问题。首先介绍了ID3算法的基本思想,然后针对算法中存在的不足,引入了广义相关函数的概念,提出了一种以条件属性和... 详细信息

决策树算法是数据挖掘中的一个比较活跃的研究领域,是对分类问题进行深入分析的一种方法。但构造最优决策树是一个NP难问题。首先介绍了ID3算法的基本思想,然后针对算法中存在的不足,引入了广义相关函数的概念,提出了一种以条件属性和决策属性之间的广义相关函数作为属性选择标准的决策树构造方法,并且与ID3算法进行了实验比较。实验表明,这种方法不但可以优化决策树模型,而且用该方法构造的决策树的预测精度也得到明显改善。

关键词：决策树广义相关函数 ID3算法

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基于改进的GRNN的销量预测

计算机工程与科学 2010年第1期32卷 153-155页

作者：王红卫林健良华南理工大学理学院广东广州510641

根据灯具销量具有增长趋势和周期性二者合成的非线性特点,本文利用相空间重构理论确定GRNN的输入节点数,以加权误差代价函数代替传统误差代价函数为目标训练网络,采用粒子群优化算法优化平滑参数,并在此基础上将GRNN用于灯具销量的短期... 详细信息

根据灯具销量具有增长趋势和周期性二者合成的非线性特点,本文利用相空间重构理论确定GRNN的输入节点数,以加权误差代价函数代替传统误差代价函数为目标训练网络,采用粒子群优化算法优化平滑参数,并在此基础上将GRNN用于灯具销量的短期预测。与传统的BPNN相比,改进后的GRNN预测精度更高,抗噪声能力更强,模型更稳健。

关键词：相空间重构广义回归神经网络加权误差代价函数