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Intelligent Material Framework for Data Mining and Performance Prediction of Invar Alloy
Rare Metals, Volume 45, Issue 6, June 2026.ABSTRACT Invar alloys exhibit a low coefficient of thermal expansion (CTE) over a wide temperature range and are regarded as critical materials for precision engineering and aerospace applications. In this work, an integrated OLR‐IMF (an intelligent material framework based on optical character recognition [OCR], large language models [LLMs], and ...
Tongbo Jiang +11 more
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Classifier of silicon content in hot metal based on support vector machines(基于支持向量机的高炉铁水硅含量多类别分类)
Zhejiang Daxue xuebao. Lixue ban, 2007 支持向量机是基于统计学习理论发展而来的一种机器学习算法，本文介绍了非线性软间隔分类机、最小二乘分类机和加权最小二乘分类机的算法.以山东莱钢1号高炉在线采集数据作为应用案例，使用C-均值算法对[Si]做聚类分析将其分成5类，改进M-ary分类方法实现对铁水硅质量分数[Si]的多类别分类，并对各分类机的性能作出评价.
JIANLing(渐令) +2 more
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智能科学与技术学报, 2023 针对具有不确定性四旋翼无人机姿态跟踪问题，提出了基于极值搜索的鲁棒控制方法。首先，建立四旋翼无人机非线性姿态模型，并考虑模型参数的不确定性，设计鲁棒控制器来确保跟踪误差动态的有界性。然后，将鲁棒控制器与无模型学习算法结合，设计基于学习的控制器，从而自动迭代地调整鲁棒控制器的反馈增益，并在线优化期望性能成本函数。最后，通过MATLAB进行数值仿真，所述控制方法的系统稳态跟踪误差相较于经典鲁棒控制方法降低了0.246，证明了所述方法鲁棒性和优越性。
郭大力, 赵中原, 罗子娟
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Rare Metals, Volume 45, Issue 5, May 2026.ABSTRACT With excellent castability and dimensional stability, Zn alloys are widely used in the automotive and electronic industries. However, the inherent trade‐off between strength and ductility remains a key bottleneck limiting their application in high‐performance fields.
Jianxing Zhou +11 more
wiley +1 more source
智能科学与技术学报, 2019 机器学习根据历史数据的模式预测未来，近年来进行了大量研究并得到了应用，但在处理动态、非完整、非结构化信息上与人类相去甚远。为此，引入人的决策，结合机器学习、知识库，构建了一个人在回路的混合增强智能闭环系统。基于 Sawyer 协作机器人搭建了人机融合实验平台，设计了机器人抓取实验。实验结果表明，相比单一机器学习方式，在引入人类智能后，Sawyer在应对非结构化环境下的抓取任务中表现更佳。
付海军 +4 more
doaj
基于半监督学习的断路器弹簧机构机械特性监测及状态评估技术研究
Gaoya dianqi, 2022 针对断路器弹簧机构机械特性监测及状态识别系统普遍存在监测类型不全、特征值提取单一、判断标准太过绝对等问题，文中提出了基于小波及半监督学习的多特征分析的断路器弹簧操动机构机械状态识别新方法。通过感知元件对分合闸线圈电流、动触头位移等信号进行采集，采用小波算法对信号进行滤波处理，分析断路器弹簧操动机构的分合闸线圈电流、动触头位移等信号与断路器异常状态之间的对应关系，提取特征值，建立半监督学习多分类网络模型，实现断路器弹簧操动机构故障的机械特性监测及状态识别。实验结果验证了此方法具有较高的诊断正确率 ...
彭跃辉 +3 more
doaj
Rare Metals, Volume 45, Issue 4, April 2026.ABSTRACT Nickel‐based superalloys (Ni‐based superalloys) have attracted extensive attention in laser additive manufacturing (LAM) due to their capability to directly fabricate complex and high‐performance structural components. However, the rapid melting and solidification inherent to LAM result in intense thermal cycling, which induces high residual ...
Tianxiang Lin +9 more
wiley +1 more source
, 2018 鳗鱼机器人的动力学模型非线性强、高度欠驱动,导致多关节鳗鱼机器人的切向速度跟踪控制极具挑战.本文采用P型迭代学习控制与步态生成器相结合的方法对多关节鳗鱼机器人的切向速度进行跟踪控制.首先,采用解析牛顿―欧拉法建立非惯性系下的鳗鱼机器人动力学模型,直接获得切向速度子动力学模型;然后,利用带饱和函数的P型迭代学习控制器控制步态参数,并且利用复合能量函数和切向速度子动力学模型分析该控制器的收敛性,得到切向速度跟踪误差的收敛条件;最后,提出鳗鱼机器人的运动控制框架,并对多模块的鳗鱼机器人进行仿真和实验 ...
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Gaoya dianqi, 2015 针对变压器故障的特征,结合变压器油中气体分析法以及三比值法,提出了基于遗传算法改进极限学习机的故障诊断方法。由于输入层与隐含层的权值和阈值是随机产生,传统的极限学习机可能会使隐含层节点过多,训练过程中容易产生过拟合现象。该方法运用遗传算法对极限学习机的输入层与隐含层的权值与阈值进行优化,从而提高模型的稳定性和预测精度。将诊断结果与传统的基于极限学习机故障诊断进行对比,结果表明,基于遗传算法改进极限学习机变压器故障诊断的精度更高。
吕忠 +4 more
doaj
Optimized Design of Cu‐Ni‐Co‐Si Alloy Combining Machine Learning and Experimental Feedback
Rare Metals, Volume 45, Issue 4, April 2026.ABSTRACT The machine learning method was employed to accelerate alloy design, and experimental feedback was provided to enhance predictive accuracy. A Cu‐2.7Ni‐1.0Co‐0.8Si alloy with superior properties was selected using a double‐objective optimization algorithm.
Shifang Li +3 more
wiley +1 more source