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学者姓名：何存富
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Abstract ：
This study proposes a novel modelling approach that integrates mutual information (MI)-based parameter screening with random forest (RF) modelling to achieve an accurate quantitative prediction of surface hardness and impact energy in two martensitic stainless steels (1Cr13 and 2Cr13). Preliminary analyses indicated that the magnetic parameters derived from Barkhausen noise (MBN), and the incremental permeability (IP) measurements showed limited linear correlations with the target properties (surface hardness and impact energy). To address this challenge, an MI feature screening method has been developed to identify both the linear and non-linear parameter dependencies that are critical for predicting target mechanical properties. The selected features were then fed into an RF model, which outperformed traditional multiple linear regression in handling the complex, non-monotonic relationships between magnetic signatures and mechanical performance. A key advantage of the proposed MI-RF framework lies in its robustness to small sample sizes, where it achieved high prediction accuracy (e.g., R-2 > 0.97 for hardness, and R-2 > 0.86 for impact energy) using limited experimental data. By leveraging MI's ability to capture multivariate dependencies and RF's ensemble learning power, it effectively mitigates overfitting and improves generalisation. In addition to demonstrating a promising tool for the non-destructive evaluation of martensitic steels, this study also provides a transferable paradigm for the quantitative assessment of other mechanical properties by magnetic feature fusion.
Keyword ：
surface hardness surface hardness micromagnetic testing micromagnetic testing impact energy impact energy random forests random forests quantitative prediction quantitative prediction mutual information mutual information
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| GB/T 7714 | Xu, Changjie , Dong, Haijiang , Yan, Zhengxiang et al. Micromagnetic and Quantitative Prediction of Hardness and Impact Energy in Martensitic Stainless Steels Using Mutual Information Parameter Screening and Random Forest Modeling Methods [J]. | MATERIALS , 2025 , 18 (7) . |
| MLA | Xu, Changjie et al. "Micromagnetic and Quantitative Prediction of Hardness and Impact Energy in Martensitic Stainless Steels Using Mutual Information Parameter Screening and Random Forest Modeling Methods" . | MATERIALS 18 . 7 (2025) . |
| APA | Xu, Changjie , Dong, Haijiang , Yan, Zhengxiang , Wang, Liting , Ning, Mengshuai , Liu, Xiucheng et al. Micromagnetic and Quantitative Prediction of Hardness and Impact Energy in Martensitic Stainless Steels Using Mutual Information Parameter Screening and Random Forest Modeling Methods . | MATERIALS , 2025 , 18 (7) . |
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Abstract ：
磁声发射是评价铁磁性材料力学性能的一种重要无损检测方法,然而鲜见磁声发射理论/数值模型的报道.本文提出了一种考虑微观结构(位错密度、晶粒尺寸)的磁声发射理论模型.通过数值计算,研究了磁化结构参数和微观结构参数对磁声发射信号包络的影响.之后,重点对磁声发射理论模型的合理性进行了验证.基于不同硬度试件上测得的磁声发射信号,利用遗传算法对理论模型中的动态磁滞参数和磁化结构参数进行了反演.结果发现,在反演参数下理论模型计算得到的磁声发射信号与实验信号吻合较好,且关键磁滞参数的反演值与理论值最大误差小于15%.因此,提出的理论模型可用于磁声发射信号的预测.
Keyword ：
微观结构 微观结构 磁声发射 磁声发射 铁磁性材料 铁磁性材料 硬度 硬度 理论模型 理论模型
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| GB/T 7714 | 张红亮 , 焦敬品 , 李光海 et al. 一种考虑微观结构的磁声发射理论模型 [J]. | 仪器仪表学报 , 2024 , 45 (5) : 300-310 . |
| MLA | 张红亮 et al. "一种考虑微观结构的磁声发射理论模型" . | 仪器仪表学报 45 . 5 (2024) : 300-310 . |
| APA | 张红亮 , 焦敬品 , 李光海 , 何存富 , 吴斌 . 一种考虑微观结构的磁声发射理论模型 . | 仪器仪表学报 , 2024 , 45 (5) , 300-310 . |
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Abstract ：
This study investigates the correlation between various micromagnetic signature patterns and the yield and tensile strengths of carbon steel (Cr12MoV steel as per Chinese standards). For this purpose, back-propagation neural network (BP-NN) models are established to quantitatively predict the yield and tensile strengths of carbon steels. The accuracy of prediction models is significantly affected by the presence of redundant micromagnetic signature patterns. By carefully screening the input parameters, it is able to effectively mitigate prediction errors arising from unreasonable model inputs. In the field of micromagnetic nondestructive testing (NDT), prediction models calibrated for a specific instrument or sensor cannot be directly applied to another instrument or sensor. In the study, a joint distribution adaptation transfer learning strategy based on auxiliary data is proposed to enhance the generalization of prediction models for cross-instrument applications. When auxiliary data accounts for 30% of the source domain data, the joint distribution adaptation transfer learning method based on auxiliary data improves the robustness of the model. The accuracy of the yield strength and tensile strength calibration models witnesses remarkable improvements of approximately 91.4% and 93.5%, respectively.
Keyword ：
BP neural network BP neural network Transfer learning Transfer learning Yield strength Yield strength Tensile strength Tensile strength Micromagnetic testing Micromagnetic testing
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| GB/T 7714 | Wang, Xianxian , He, Cunfu , Li, Peng et al. Micromagnetic and Quantitative Prediction of Yield and Tensile Strength of Carbon Steels Using Transfer Learning Method [J]. | JOURNAL OF NONDESTRUCTIVE EVALUATION , 2024 , 43 (2) . |
| MLA | Wang, Xianxian et al. "Micromagnetic and Quantitative Prediction of Yield and Tensile Strength of Carbon Steels Using Transfer Learning Method" . | JOURNAL OF NONDESTRUCTIVE EVALUATION 43 . 2 (2024) . |
| APA | Wang, Xianxian , He, Cunfu , Li, Peng , Liu, Xiucheng , Xing, Zhixiang , Ning, Mengshuai . Micromagnetic and Quantitative Prediction of Yield and Tensile Strength of Carbon Steels Using Transfer Learning Method . | JOURNAL OF NONDESTRUCTIVE EVALUATION , 2024 , 43 (2) . |
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Abstract ：
The correlation between magnetic Barkhausen noise (MBN) features and the surface hardness of two types of die steels (Cr12MoV steel and S136 steel in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established with MBN magnetic features extracted by different methods as the input nodes to realize the quantitative prediction of surface hardness. The accuracy of the BP-NN model largely depended on the quality of the input features. In the extraction process of magnetic features, simplifying parameter settings and reducing manual intervention could significantly improve the stability of magnetic features. In this study, we proposed a method similar to the magnetic Barkhausen noise hysteresis loop (MBNHL) and extracted features. Compared with traditional MBN feature extraction methods, this method simplifies the steps of parameter setting in the feature extraction process and improves the stability of the features. Finally, a BP-NN model of surface hardness was established and compared with the traditional MBN feature extraction methods. The proposed MBNHL method achieved the advantages of simple parameter setting, less manual intervention, and stability of the extracted parameters at the cost of small accuracy reduction.
Keyword ：
MBNHL MBNHL magnetic Barkhausen noise magnetic Barkhausen noise BP-NN BP-NN surface hardness surface hardness
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| GB/T 7714 | Wang, Xianxian , Cai, Yanchao , Liu, Xiucheng et al. Quantitative Prediction of Surface Hardness in Cr12MoV Steel and S136 Steel with Two Magnetic Barkhausen Noise Feature Extraction Methods [J]. | SENSORS , 2024 , 24 (7) . |
| MLA | Wang, Xianxian et al. "Quantitative Prediction of Surface Hardness in Cr12MoV Steel and S136 Steel with Two Magnetic Barkhausen Noise Feature Extraction Methods" . | SENSORS 24 . 7 (2024) . |
| APA | Wang, Xianxian , Cai, Yanchao , Liu, Xiucheng , He, Cunfu . Quantitative Prediction of Surface Hardness in Cr12MoV Steel and S136 Steel with Two Magnetic Barkhausen Noise Feature Extraction Methods . | SENSORS , 2024 , 24 (7) . |
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Abstract ：
本发明公开了一种用于曲轴轴颈和过渡圆角同步检测的微磁传感器，采用的U型电磁铁的磁芯端部加工成内切面，内切面和轴颈表面接触以形成磁回路。U型电磁铁提供的交变磁场主要沿轴颈环向分布以磁化轴颈表面材料，也部分穿绕过渡圆角区域回到主磁路，穿绕磁场可以对过渡圆角区域材料进行磁化。在U型电磁铁内部配置两组独立的检测元件，分别拾取轴颈表面和圆角处的多类型微磁信号(磁巴克豪森噪声、切向磁场强度、增量磁导率和多频涡流)。本发明公布的传感器可以对曲轴轴颈和过渡圆角进行同步微磁检测，应用于无损评价曲轴轴颈和过渡圆角区域的微观组织及残余应力均匀性。
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| GB/T 7714 | 何存富 , 王晶 , 刘秀成 . 一种用于曲轴轴颈和过渡圆角同步检测的微磁传感器 : CN202310351017.0[P]. | 2023-04-04 . |
| MLA | 何存富 et al. "一种用于曲轴轴颈和过渡圆角同步检测的微磁传感器" : CN202310351017.0. | 2023-04-04 . |
| APA | 何存富 , 王晶 , 刘秀成 . 一种用于曲轴轴颈和过渡圆角同步检测的微磁传感器 : CN202310351017.0. | 2023-04-04 . |
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Abstract ：
陶瓷基复合材料(Ceramic matrix composites,CMC)具有密度低和耐高温等一系列优点，广泛应用于飞机机翼前缘与先进燃气涡轮发动机等部件。由于在其生产过程中存在着制作工艺多样和制作步骤繁复等因素影响，材料内部不可避免地会存留缺陷，这对材料质量稳定性以及可靠性都造成了不可忽视的影响。针对其内部缺陷检测的迫切需求，基于太赫兹时域光谱(Terahertz time-domain spectroscopy,THz-TDS)技术具有信息量丰富、时间分辨率高的优势，提出一种用于CMC内部缺陷无损检测的太赫兹检测方法。首先，采用反射式THz-TDS系统，对预制的CMC试样进行了非接触式无损检测，获得样品逐点扫描检测信号。然后，针对其高频信号在高阶滤波后常出现的明显相位延迟现象，提出一种零相位滤波方法，消除相位延迟并精确提取出峰值、相位与渡越时间等信息。在此基础上，采用多特征加权融合成像方法绘制材料缺陷的二维表面成像结果，并重构与其对应的缺陷三维形貌图，直观展示出了缺陷形貌位置信息，最终实现了CMC试样的缺陷定位与尺寸定量评估。
Keyword ：
零相位滤波 零相位滤波 缺陷检测 缺陷检测 融合成像 融合成像 陶瓷基复合材料 陶瓷基复合材料 太赫兹波谱 太赫兹波谱
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| GB/T 7714 | 刘增华 , 吴育衡 , 王可心 et al. 基于太赫兹时域光谱技术的陶瓷基复合材料缺陷检测成像研究 [J]. | 机械工程学报 , 2023 , 59 (14) : 33-42 . |
| MLA | 刘增华 et al. "基于太赫兹时域光谱技术的陶瓷基复合材料缺陷检测成像研究" . | 机械工程学报 59 . 14 (2023) : 33-42 . |
| APA | 刘增华 , 吴育衡 , 王可心 , 满润昕 , 何存富 , 吴斌 . 基于太赫兹时域光谱技术的陶瓷基复合材料缺陷检测成像研究 . | 机械工程学报 , 2023 , 59 (14) , 33-42 . |
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Abstract ：
超声导波检测技术是新型的无损检测方法之一.水平剪切(SH)导波是超声导波的一种.在板和管结构的检测中,SH导波检测技术占据着越来越重要的位置.电磁声传感器(EMAT)常被用于SH导波的激励或接收.SH-EMAT具有适应性强、效率高的特点,基于SH-EMAT检测技术的应用场景越来越多.以近十几年的相关文献为基础,介绍了SH-EMAT设计以及SH导波缺陷检测技术的研究现状和进展,提供了SH导波检测在不同应用背景下的传感器选择,总结了不同频率SH导波的检测能力,分析了不同SH导波检测技术的优缺点.同时还对电磁超声水平剪切导波检测的未来研究趋势进行了展望,为相关研究人员提供了研究方向和思路.
Keyword ：
水平剪切导波 水平剪切导波 信号处理 信号处理 EMAT EMAT 缺陷检测 缺陷检测 阵列技术 阵列技术
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| GB/T 7714 | 刘增华 , 洪泽汇 , 吴斌 et al. 电磁超声水平剪切导波的缺陷检测研究进展 [J]. | 测控技术 , 2023 , 42 (5) : 28-36 . |
| MLA | 刘增华 et al. "电磁超声水平剪切导波的缺陷检测研究进展" . | 测控技术 42 . 5 (2023) : 28-36 . |
| APA | 刘增华 , 洪泽汇 , 吴斌 , 何存富 . 电磁超声水平剪切导波的缺陷检测研究进展 . | 测控技术 , 2023 , 42 (5) , 28-36 . |
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Abstract ：
基于勒让德级数法, 联立Green-Nagdhi热弹性理论, 建立了含温度场各向异性层合板的超声导波频散特性理论模型, 揭示温度场环境下多层复合材料中超声导波的传播过程. 同时, 构建了温度场环境下多层各向同性与各向异性层合板的声学频域仿真模型, 以提取特定温度下层合板超声导波的频散曲线. 通过对比仿真数据与理论计算的结果, 验证了所提理论方法的有效性. 随后, 以不同铺层方向单向纤维材料组成的层合板为例, 分析了相同温度条件下中间层纤维角度对各向异性层合板超声导波频散曲线的影响规律, 并细节分析了特定频率处A0模态的位移及应力波结构的分布特征. 此外, 着重考虑温度场变化对碳纤维复合材料层合板中超声导波频散特性的影响机理, 指出导波基础模态的偏移规律, 并详细列举了不同频率与温度下的基础模态相速度值. 最后, 利用不同温度工况下的相速度差值, 提取多层各向异性层合板相速度温度敏感度变化曲线, 探究不同频率下对称和反对称模态的相速度温度敏感度, 为多层复合材料力学性能的超声无损检测与评估提供了理论基础.
Keyword ：
超声导波 超声导波 温度场 温度场 勒让德级数法 勒让德级数法 频散曲线 频散曲线 单向纤维层合板 单向纤维层合板
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| GB/T 7714 | 吕炎 , 林晓磊 , 高杰 et al. 基于级数法的热弹各向异性层合板兰姆波频散特性分析 [J]. | 力学学报 , 2023 , 55 (9) : 1939-1949 . |
| MLA | 吕炎 et al. "基于级数法的热弹各向异性层合板兰姆波频散特性分析" . | 力学学报 55 . 9 (2023) : 1939-1949 . |
| APA | 吕炎 , 林晓磊 , 高杰 , 何存富 . 基于级数法的热弹各向异性层合板兰姆波频散特性分析 . | 力学学报 , 2023 , 55 (9) , 1939-1949 . |
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Abstract ：
声弹性导波在波导结构的应力检测方面表现出巨大的发展潜力。基于声弹性理论及勒让德级数法(LOPE-Prestress Method),建立了预应力介质中声弹性导波的理论分析模型。通过与子波法(SPBW Method)的计算结果进行对比,验证了所提方法的准确性。基于所提模型研究了预应力对基础模态导波的作用规律,为基于声弹性导波的预应力检测奠定了基础。
Keyword ：
应力检测 应力检测 声弹性导波 声弹性导波 级数法 级数法 频散曲线 频散曲线
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| GB/T 7714 | 张义政 , 吕炎 , 高杰 et al. 基于级数法的声弹性导波传播特性理论研究 [C] //北京力学会第二十九届学术年会论文集 . 2023 . |
| MLA | 张义政 et al. "基于级数法的声弹性导波传播特性理论研究" 北京力学会第二十九届学术年会论文集 . (2023) . |
| APA | 张义政 , 吕炎 , 高杰 , 何存富 . 基于级数法的声弹性导波传播特性理论研究 北京力学会第二十九届学术年会论文集 . (2023) . |
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Abstract ：
基于锂离子电池超声导波的传播特性,进行了有限元时域仿真分析。分别建立了无孔隙电池时域仿真模型和多孔电池时域仿真模型,探究荷电状态对A0模态幅值以及渡越时间的影响。随后以有限元仿真研究结果为依据,对锂离子电池进行超声导波实验研究。建立了锂离子电池超声导波检测系统,对定制电池进行导波检测实验,提取电池不同荷电状态下的时域特征参数,探究了荷电状态对导波传播特性的影响。此外,还研究了定制电池不同工况条件下的导波传播特性。
Keyword ：
超声导波 超声导波 荷电状态 荷电状态 导波检测实验 导波检测实验 锂离子电池 锂离子电池
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| GB/T 7714 | 林晓磊 , 吕炎 , 何存富 . 基于超声导波的锂离子电池荷电状态无损检测研究 [C] //北京力学会第二十九届学术年会论文集 . 2023 . |
| MLA | 林晓磊 et al. "基于超声导波的锂离子电池荷电状态无损检测研究" 北京力学会第二十九届学术年会论文集 . (2023) . |
| APA | 林晓磊 , 吕炎 , 何存富 . 基于超声导波的锂离子电池荷电状态无损检测研究 北京力学会第二十九届学术年会论文集 . (2023) . |
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