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学者姓名:刘增华
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GB/T 7714 | Liu, Zenghua . Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation [J]. | SENSORS , 2024 , 24 (2) . |
MLA | Liu, Zenghua . "Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation" . | SENSORS 24 . 2 (2024) . |
APA | Liu, Zenghua . Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation . | SENSORS , 2024 , 24 (2) . |
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In the ultrasonic testing of the mechanical properties of ferromagnetic materials, the main excitation mechanism modes of ultrasonic waves are Lorentz force mechanism ultrasonic and magnetostriction mechanism ultrasonic. Lorentz force mechanism ultrasonic mainly detects the conductive characteristics of materials, while magnetostriction mechanism ultrasonic mainly detects the hysteresis characteristics of materials. However, conventional electromagnetic acoustic transducers (EMATs) cannot simultaneously characterise these two characteristics of ferromagnetic materials. In this study, we conclude from the finite element simulation that a quantitative lift-off distance (i.e. the distance between EMAT and the specimen) can change the main mechanism mode of the excited ultrasonic wave. Based on this conclusion, an electromagnet electromagnetic acoustic transducer with dual main excitation modes (DM-E-EMAT) is designed, which can realise the dual mode switching of the main Lorentz force mechanism and main magnetostriction mechanism by adding or removing hollow square gasket. The ultrasonic testing of ferromagnetic materials based on the two main mechanisms of DM-E-EMAT can simultaneously characterise the conductivity and magnetostriction properties of ferromagnetic materials, which enables the characterisations of two types of characteristic parameters with one transducer, improves the efficiency of electromagnetic ultrasonic non-destructive testing of the mechanical properties and reduces the detection errors of ferromagnetic material.
Keyword :
Electromagnetic acoustic transducer Electromagnetic acoustic transducer Lorentz force mechanism ultrasonic Lorentz force mechanism ultrasonic ferromagnetic material ferromagnetic material mechanical property mechanical property magnetostriction mechanism ultrasonic magnetostriction mechanism ultrasonic
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GB/T 7714 | Zhang, Peiying , Liu, Zenghua , Guo, Yanhong et al. Development of dual-main excitation mechanism modes electromagnet EMAT for testing ferromagnetic materials [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2023 . |
MLA | Zhang, Peiying et al. "Development of dual-main excitation mechanism modes electromagnet EMAT for testing ferromagnetic materials" . | NONDESTRUCTIVE TESTING AND EVALUATION (2023) . |
APA | Zhang, Peiying , Liu, Zenghua , Guo, Yanhong , Wang, Xiaosai , Gong, Yu . Development of dual-main excitation mechanism modes electromagnet EMAT for testing ferromagnetic materials . | NONDESTRUCTIVE TESTING AND EVALUATION , 2023 . |
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The service life and structural safety of components are affected by the thermal ageing of materials; therefore, a non-destructive evaluation of materials is extremely essential and crucial. In this work, heat-resistant steel Cr12MoV was selected as a specimen, and the embrittlement period of heat-resistant steel Cr12MoV was obtained by accelerated thermal ageing experiments. The effects of service temperature and service time on the mechanical properties of heat-resistant steel were analysed. The non-destructive testing of heat-resistant steel was carried out by using magneto-acoustic compound detection techniques based on electromagnetic acoustic transducers. In the process, magneto-acoustic compound detection signals were decoupled. The electromagnetic characteristic parameters and ultrasonic characteristic parameters of the detection signals were extracted to evaluate the mechanical properties and thermal ageing of heat-resistant steel. The quantitative evaluation ability of thermal ageing brittleness of heat-resistant steel was improved by using the magneto-acoustic compound detection techniques compared with single eddy current detection method or single ultrasonic detection method.
Keyword :
Magneto-acoustic compound Magneto-acoustic compound Electromagnetic acoustic transducer Electromagnetic acoustic transducer Ultrasonic waves Ultrasonic waves Nondestructive evaluation Nondestructive evaluation Eddy current Eddy current
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GB/T 7714 | Guo, Yanhong , Liu, Zenghua , Zhao, Xin et al. Detection and evaluation of thermal aging brittleness of heat-resistant steel using magneto-acoustic compound techniques [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2023 . |
MLA | Guo, Yanhong et al. "Detection and evaluation of thermal aging brittleness of heat-resistant steel using magneto-acoustic compound techniques" . | NONDESTRUCTIVE TESTING AND EVALUATION (2023) . |
APA | Guo, Yanhong , Liu, Zenghua , Zhao, Xin , He, Cunfu , Wu, Bin . Detection and evaluation of thermal aging brittleness of heat-resistant steel using magneto-acoustic compound techniques . | NONDESTRUCTIVE TESTING AND EVALUATION , 2023 . |
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Abstract :
Fe-based amorphous coatings prepared by high-velocity oxy-fuel (HVOF) spraying have the advantages of good mechanical properties, high density, low porosity, and high amorphous content. The service life and bonding strength of coating greatly depend on its thickness; however, the characterization of ferromagnetic coating thickness is a very difficult problem. Pulsed eddy current (PEC) is characterized by abundant signals in frequency domains. In this paper, the thickness measurement principle of ferromagnetic coating was explored, and the typical and entropy features from PEC signals were extracted. Seven integrated learning methods were combined to quantitatively characterize the coating thickness, namely ridge regression (RR), lasso regression (LR), random forest regression (RFR), extra trees regression (ETR), gradient boosting tree regression (GBTR), addaptive boost regression (ABR) and eXtreme Gradient Boosting Regression (XGBR) algorithms. By comparing typical features with new ones, it was verified that the effective combination of entropy features and typical features could be used as effective feature parameters of eddy current signal. Statistical scores (RMSE and R-2) and GridsearchCV features were used to evaluate and optimize the established model. As indicated by the results, the proposed XGBR machine learning model well predicted the coating thickness, and the relative error less than 0.05 mm.
Keyword :
Fe-based amorphous coating Fe-based amorphous coating Entropy Entropy PEC PEC Coating thickness Coating thickness HVOF HVOF
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GB/T 7714 | Huang, Xiaofei , Liu, Zenghua , Gong, Yu et al. Quantitative Estimation of Fe-Based Amorphous Coating Thickness Based on Pulsed Eddy Current Technology [J]. | JOURNAL OF NONDESTRUCTIVE EVALUATION , 2023 , 42 (1) . |
MLA | Huang, Xiaofei et al. "Quantitative Estimation of Fe-Based Amorphous Coating Thickness Based on Pulsed Eddy Current Technology" . | JOURNAL OF NONDESTRUCTIVE EVALUATION 42 . 1 (2023) . |
APA | Huang, Xiaofei , Liu, Zenghua , Gong, Yu , Wu, Sha , Chen, Kewei , He, Cunfu . Quantitative Estimation of Fe-Based Amorphous Coating Thickness Based on Pulsed Eddy Current Technology . | JOURNAL OF NONDESTRUCTIVE EVALUATION , 2023 , 42 (1) . |
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This paper is the first of a series of papers on the roughness characteristics of the burden surface in the blast furnace. The measurement method of the burden surface roughness texture is described, and the overall roughness characteristics of the burden surface are studied from a statistical point of view. This study focuses on two typical granularized burden materials, coke and sintered ore, which present four kinds of burden particles under two individual particle sizes. Simulated cold-state burden belts proportional to the practical burden radial sectors were stacked in a pilot plant. An RGBD camera was used to measure the simulated burden belt surfaces to obtain the surface texture details. Four corresponding digital eleva-tion models of the burden belts were obtained through data processing. The root mean squared height, skewness, kurtosis, and spatial autocorrelation function are selected as statistical indexes. The obtained digital elevation models were counted. The results show that all four kinds of burden surfaces are Isotro-pic-Rough-Surface. In addition, the height distributions of the rough burden surface are close to the Gaussian distribution. Also, the spatial autocorrelation functions of the coke and large-sized sintered ore burden surfaces are close to the Gaussian function form. And lastly, the spatial autocorrelation function of the small sintered ore burden surface is close to the exponential function form.
Keyword :
digital elevation model digital elevation model blast furnace blast furnace burden surface roughness burden surface roughness RGBD camera RGBD camera burden particle burden particle
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GB/T 7714 | Tian, Jiuzhou , Tanaka, Akira , Gao, Di et al. Characterization of the Blast Furnace Burden Surface: Experimental Measurement and Roughness Statistics [J]. | ISIJ INTERNATIONAL , 2023 , 63 (7) : 1217-1225 . |
MLA | Tian, Jiuzhou et al. "Characterization of the Blast Furnace Burden Surface: Experimental Measurement and Roughness Statistics" . | ISIJ INTERNATIONAL 63 . 7 (2023) : 1217-1225 . |
APA | Tian, Jiuzhou , Tanaka, Akira , Gao, Di , Liu, Zenghua , Hou, Qingwen , Chen, Xianzhong . Characterization of the Blast Furnace Burden Surface: Experimental Measurement and Roughness Statistics . | ISIJ INTERNATIONAL , 2023 , 63 (7) , 1217-1225 . |
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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 :
涂层结构具有美观、隔热和耐腐蚀等优点,被广泛应用于航空航天、汽车船舶制造和制药等领域.但在涂层制备和服役过程中会不可避免地出现气泡和裂纹等缺陷,且涂层厚度和均匀性会直接影响涂层寿命,因此对涂层结构的检测显得十分重要.与常规无损检测技术相比,太赫兹时域光谱(THz-TDS)技术非接触性好、抗干扰性强,适用于涂层结构快速无损检测.首先,简要地介绍了太赫兹波、太赫兹时域光谱技术和典型的太赫兹时域光谱系统;然后,详细地阐述了太赫兹时域光谱技术在光学参量、厚度和微结构检测方面的国内外研究进展,特别是太赫兹波在汽车船舶、航空航天和生物制药方向的厚度检测与成像;最后,分析了涂层结构无损检测的现状,对现有的太赫兹波检测涂层存在的问题进行了总结,并对其未来的发展进行了讨论和展望.
Keyword :
微结构 微结构 太赫兹时域光谱技术 太赫兹时域光谱技术 厚度 厚度 涂层 涂层 无损检测 无损检测
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GB/T 7714 | 万玉红 , 董形影 , 吴育衡 et al. 太赫兹时域光谱技术在涂层检测中的研究进展 [J]. | 测控技术 , 2023 , 42 (6) : 22-35 . |
MLA | 万玉红 et al. "太赫兹时域光谱技术在涂层检测中的研究进展" . | 测控技术 42 . 6 (2023) : 22-35 . |
APA | 万玉红 , 董形影 , 吴育衡 , 刘增华 . 太赫兹时域光谱技术在涂层检测中的研究进展 . | 测控技术 , 2023 , 42 (6) , 22-35 . |
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Abstract :
针对复合材料层合板中耦合Lamb波的传播问题,基于分层模型提出解析建模与有限元数值模拟相结合的方法对其进行预测和评估.利用Legendre正交多项式展开法推导多层各向异性复合材料层合板中耦合Lamb波的控制方程,并对频率-波数域频散特性曲线实现数值求解.基于平面壳单元构建复合材料层合板的有限元模型,采用波结构加载法生成单一Lamb波基本模态,设计复合材料层合板的不同纤维取向、边界和界面约束条件,并经二维傅里叶变换获得有限元模拟数据的频率-波数域频散特性曲线.通过对比验证,结果表明两种方法均有较好的吻合性.
Keyword :
有限元 有限元 复合材料 复合材料 频散 频散 Lamb波 Lamb波 Legendre正交多项式 Legendre正交多项式
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GB/T 7714 | 张旭 , 刘宏业 , 李璇 et al. 基于分层模型的复合材料耦合Lamb波频率-波数域特性研究 [J]. | 测控技术 , 2023 , 42 (5) : 66-72 . |
MLA | 张旭 et al. "基于分层模型的复合材料耦合Lamb波频率-波数域特性研究" . | 测控技术 42 . 5 (2023) : 66-72 . |
APA | 张旭 , 刘宏业 , 李璇 , 施展 , 刘增华 . 基于分层模型的复合材料耦合Lamb波频率-波数域特性研究 . | 测控技术 , 2023 , 42 (5) , 66-72 . |
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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 :
Truck cranes are indispensable heavy-duty loading and unloading equipment in industrial production. A boom is the key load-bearing component of a truck crane, and its health has a vital influence on a crane's lifting performance and safety in production. Therefore, it is urgent to develop a structural health monitoring (SHM) method for a boom structure. In this research, an improved intelligent defect location algorithm based on helical guided waves is applied to the defect detection of a U-shaped boom. The improved intelligent algorithm is a defect location algorithm based on the ellipse imaging principle, which combines an evolutionary algorithm with a K-means algorithm and can identify the location of defects through the distribution of individuals. According to the propagation characteristics of the helical guided waves in the structure of a U-shaped boom, an optimization scheme for the improved intelligent defect location algorithm is proposed that fully considers the fact that the group velocity of the helical guided waves varies with the wall thickness, and the corresponding group velocity is used to accurately calculate the arrival time of each initial individual to improve the accuracy of the defect location. Numerical simulations and experiments are conducted to verify the effectiveness of the proposed improved intelligent defect location algorithm in the defect location algorithm. When only one group velocity is considered, the improved intelligent defect location algorithm is in good agreement with the elliptical imaging algorithm. When the group velocities for different wall thicknesses are fully considered, the detection results of the optimized intelligent defect location algorithm have a higher resolution. This optimization algorithm provides a tool for the SHM of a U-shaped boom based on guided waves.
Keyword :
defect location defect location imaging algorithm imaging algorithm structural health monitoring structural health monitoring helical guided waves helical guided waves U-shaped boom U-shaped boom
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GB/T 7714 | Lu, Zhaojing , Liu, Zenghua , Jiang, Wenshuo et al. Intelligent defect location of a U-shaped boom using helical guided waves [J]. | STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL , 2022 , 22 (4) : 2827-2855 . |
MLA | Lu, Zhaojing et al. "Intelligent defect location of a U-shaped boom using helical guided waves" . | STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 22 . 4 (2022) : 2827-2855 . |
APA | Lu, Zhaojing , Liu, Zenghua , Jiang, Wenshuo , Wu, Bin , He, Cunfu . Intelligent defect location of a U-shaped boom using helical guided waves . | STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL , 2022 , 22 (4) , 2827-2855 . |
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