GH4169晶粒尺寸的多参数超声评价方法

doi:10.3901/JME.2018.24.018

机械工程学报 ›› 2018, Vol. 54 ›› Issue (24): 18-26.doi: 10.3901/JME.2018.24.018

GH4169晶粒尺寸的多参数超声评价方法

陈昊¹, 董金龙¹, 陈曦^1,2, 邬冠华¹, 周正干²

1. 南昌航空大学无损检测技术教育部重点实验室南昌 330063;
2. 北京航空航天大学机械工程及自动化学院北京 100191

收稿日期:2018-01-30 修回日期:2018-07-02 出版日期:2018-12-20 发布日期:2018-12-20
通讯作者: 陈曦(通信作者),女,1982年出生,博士研究生,讲师。主要研究方向为电磁与声学检测技术、无损检测智能化。E-mail:chenxi4645@nchu.edu.cn
作者简介:陈昊,男,1982年出生,博士,副教授,硕士研究生导师。主要研究方向为智能计算理论与应用、人工智能与模式识别、无损检测智能化。E-mail:chenhaoshl@nchu.edu.cn;董金龙,男,1991年出生,硕士研究生。主要研究方向为智能计算理论与应用、无损检测智能化。E-mail:dongjinglong_edu@163.com
基金资助:
国家自然科学基金（61772255，61440049）、江西省创新驱动“5511”工程优势学科创新团队（20165BCB19007）、江西省优势科技创新团队计划（20152BCB24004）、无损检测技术教育部重点实验室（南昌航空大学）开放基金（ZD201529004）、江西省科技厅科技（20161BBG70047，20161BAB202038）、江西省教育厅科技（GJJ150716）和江西省图像处理与模式识别重点实验室开放基金（ET201604246）资助项目。

Novel Multi-parameter Ultrasonic Evaluation Method for GH4169 Grain Size

CHEN Hao¹, DONG Jinlong¹, CHEN Xi^1,2, WU Guanhua¹, ZHOU Zhenggan²

1. Key Laboratory of Nondestructive Test of Ministry of Education, Nanchang Hangkong University, Nanchang 330063;
2. School of Mechanical Engineering and Automation, Beihang University, Beijing 100191

Received:2018-01-30 Revised:2018-07-02 Online:2018-12-20 Published:2018-12-20

摘要/Abstract

摘要： 考虑到单个超声响应特性参数反应出晶粒尺寸的特征信息不够全面，提出将多个超声参数相结合，构建面向GH4169晶粒尺寸无损定量表征的多参数超声评价方法。依据相关性度量准则，从声速、衰减系数、非线性系数等8个超声参数中选取有效参数；构建二次多项式的映射模型，将选取的多维参数降成单维参数并进行量纲一化处理；在对单维参数与晶粒尺寸拟合过程中，构建以两者平均绝对误差最小为目标的优化问题并结合进化算法进行求解，寻找最佳的映射函数和拟合函数系数；最终建立多参数超声评价模型。经测试样本验证表明，与单一参数的声速法模型、衰减系数法模型和背散射EMD法模型相比，所建模型评价结果精度高，性能稳定、误差小且有着良好的评价效应；融合了多个超声检测参数而保留了对晶粒尺寸的响应信息，提高了测量精度和抗干扰能力。

关键词: 超声评价, 多参数, 进化算法, 晶粒尺寸, 映射模型

Abstract: Considering that the characteristic information of grain size that reflects from single ultrasonic response characteristic parameter is not comprehensive enough, a combination of multiple ultrasonic parameters is proposed to construct a multi-parameter ultrasonic evaluation method for the non-destructive quantitative characterization of the grain size of GH4169. According to the correlation metric, the effective parameters are selected from 8 ultrasonic parameters, such as sound velocity, attenuation coefficient and nonlinear coefficient. A quadratic polynomial mapping model is constructed to reduce the selected multidimensional parameters to single-dimensional parameters and normalizing. In the process of fitting single-dimensional parameters and grain size, an optimization problem aiming at minimizing the average absolute error between them is constructed and solved by evolutionary algorithm to find the best mapping function and fitting function coefficient. Finally, a multi-parameter ultrasonic evaluation model is given. Compared with single-parameter sound velocity model, attenuation coefficient model and backscattering EMD model, the test results show that the model evaluation results have high accuracy, stable performance, small error and good evaluation effect. Due to the integration of multiple ultrasonic detection parameters, the response information to the grain size is retained, thereby improving the measurement accuracy and anti-interference ability.

Key words: evolutionary algorithm, grain size, mapping model, multi-parameter, ultrasonic evaluation

中图分类号:

TG115

陈昊, 董金龙, 陈曦, 邬冠华, 周正干. GH4169晶粒尺寸的多参数超声评价方法[J]. 机械工程学报, 2018, 54(24): 18-26.

CHEN Hao, DONG Jinlong, CHEN Xi, WU Guanhua, ZHOU Zhenggan. Novel Multi-parameter Ultrasonic Evaluation Method for GH4169 Grain Size[J]. Journal of Mechanical Engineering, 2018, 54(24): 18-26.

参考文献

[1] GU J, ZHANG L, NI S, et al. Effects of grain size on the microstructures and mechanical properties of 304 austenitic steel processed by torsional deformation[J]. Micron, 2018, 105:93-97.
[2] TIAN S, LI Z, ZHAO Z, et al. Influence of deformation level on microstructure and creep behavior of GH4169 alloy[J]. Materials Science and Engineering:A, 2012, 550(9):235-242.
[3] LU X D, DU J H, DENG Q. High temperature structure stability of GH4169 superalloy[J]. Materials Science and Engineering:A, 2013, 559(1):623-628.
[4] GAO X, ZENG W, ZHAO Q, et al. Acquisition of recrystallization information using optical metallography in a metastable beta titanium alloy[J]. Journal of Alloys and Compounds, 2017, 727:346-352.
[5] CHEN H, YAO Y, WARNER J A, et al. Grain size quantification by optical microscopy, electron backscatter diffraction, and magnetic force microscopy[J]. Micron, 2017, 101:41-47.
[6] CHEN X, NING F, HOU J, et al. Dual-frequency ultrasonic treatment on microstructure and mechanical properties of ZK60 magnesium alloy[J]. Ultrasonics Sonochemistry, 2018, 40:433-441.
[7] PEREVERTOV O, NESLUSAN M, STUPAKOV A. Detection of milled 100Cr6 steel surface by eddy current and incremental permeance methods[J]. NDT & E International, 2017, 87:15-23.
[8] GHANEI S, ALAM A S, KASHEFI M, et al. Nondestructive characterization of microstructure and mechanical properties of intercritically annealed dual-phase steel by magnetic Barkhausen noise technique[J]. Materials Science & Engineering A, 2014, 607:253-260.
[9] ZHU Y K, TIAN G Y, LU R S, et al. A review of optical NDT technologies[J]. Sensors, 2011, 11(8):7773-7798.
[10] TOOZANDEHJANI M, MATORI K A, OSTOVAN F, et al. On the correlation between microstructural evolution and ultrasonic properties:a review[J]. Journal of Materials Science, 2015, 50(7):2643-2665.
[11] MANDAL T, TINJUM J M, EDIL T B. Non-destructive testing of cementitiously stabilized materials using ultrasonic pulse velocity test[J]. Transportation Geotechnics, 2016, 6:97-107.
[12] AGHAIE-KHAFRI M, HONARVAR F, ZANGANEH S. Characterization of grain size and yield strength in 301 stainless steel using ultraonic attenuation measurements[J]. Journal of Nondestructive Evaluation, 2012, 31(3):191-196.
[13] SHARMA G K, KUMAR A, RAO C B, et al. Short time Fourier transform analysis for understanding frequency dependent attenuation in austenitic stainless steel[J]. NDT & E International, 2013, 53(1):1-7.
[14] RAYES M M, EL-DANAF E A, ALMAJID A A. Characterization and correlation of mechanical, microstructural and ultrasonic properties of power plant steel[J]. Materials Characterization, 2015, 100:120-134.
[15] LI X, SONG Y, LIU F, et al. Evaluation of mean grain size using the multi-scale ultrasonic attenuation coefficient[J]. NDT & E International, 2015, 72:25-32.
[16] GARCIN T, SCHMITT J H, MILITZER M. In-situ laser ultrasonic grain size measurement in superalloy INCONEL 718[J]. Journal of Alloys and Compounds, 2016, 670:329-336.
[17] 李雄兵,宋永锋,胡宏伟,等. 基于衰减速率的晶粒尺寸超声评价方法[J]. 机械工程学报, 2015, 51(14):1-7. LI Xiongbing, SONG Yongfeng, HU Hongwei, et al. Evaluation of grain size using the ultrasonic attenuation rate[J]. Journal of Mechanical Engineering, 2015, 51(14):1-7.
[18] 宋永锋,李雄兵,吴海平,等. In718晶粒尺寸对超声背散射信号的影响及其无损评价方法[J]. 金属学报, 2016, 52(3):378-384. SONG Yongfeng, LI Xiongbing, WU Haiping, et al. Effects of In718 grain size on ultrasonic backscatting signals and its nondestructive evaluation method[J]. Acta Metallurgica Sinica, 2016, 52(3):378-384.
[19] DUNN M, CARCIONE A, BLANLOEUIL P, et al. Critical aspects of experimental damage detection methodologies using nonlinear vibro-ultrasonics[J]. Procedia Engineering, 2017, 188:133-140.
[20] WANG K, SHRIVER D, LI Y, et al. Characterization of weld attributes in ultrasonic welding of short carbon fiber reinforced thermoplastic composites[J]. Journal of Manufacturing Processes, 2017, 29:124-132.
[21] LV H, JIAO J, MENG X, et al. Characterization of nonlinear ultrasonic effects using the dynamic wavelet fingerprint technique[J]. Journal of Sound and Vibration, 2017, 389:364-379.
[22] CHEN X, WU G, ZHOU Z, et al. Study of the relationship between ultrasonic properties and microstructure of nickel-based superalloy GH706[J]. Insight-Non-Destructive Testing and Condition Monitoring, 2017, 59(11):609-614.
[23] MAIER S G. Noncontact nonlinear resonance ultrasound spectroscopy for small metallic samples[D]. Atlanta:Georgia Institute of Technology, 2017.
[24] 陈曦,熊鸿建,吴伟,等. 固溶温度对GH4169微观组织形貌及超声特性的影响[J]. 无损检测, 2018, 40(1):1-9. CHEN Xi, XIONG Hongjian, WU Wei, et al. Effects of solution temperature on microstructure and ultrasonic properties of GH4169[J]. Nondestructive Testing, 2018, 40(1):1-9.

GH4169晶粒尺寸的多参数超声评价方法

Novel Multi-parameter Ultrasonic Evaluation Method for GH4169 Grain Size

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	管超, 张则强, 李云鹏, 贾林. 多行设备布局的一种多目标差分进化算法和线性规划混合方法[J]. 机械工程学报, 2019, 55(13): 160-174.
[2]	惠恬静, 雷步芳, 李永堂, 贾璐. P91厚壁管铸挤复合成形工艺参数对组织和力学性能的影响[J]. 机械工程学报, 2018, 54(12): 156-164.
[3]	鲁军,于庆洋,苏超锋. MSMA传感器多参数变化时特性研究[J]. 电气工程学报, 2017, 12(8): 16-20.
[4]	殷安民, 杨荃, 何飞, 王晓晨, 董锋, 王燕龙, 束学道. 基于激光超声的低碳钢平均晶粒尺寸无损检测方法^*[J]. 机械工程学报, 2017, 53(2): 11-19.
[5]	陈征, 刘亚辉, 杨芳. 基于进化-增强学习方法的插电式混合动力公交车能量管理策略[J]. 机械工程学报, 2017, 53(16): 86-93.
[6]	贾庆轩, 李彤, 陈钢, 孙汉旭, 张健. 基于多层映射模型的空间机械臂运动可靠性影响因素灵敏度分析[J]. 机械工程学报, 2017, 53(11): 10-19.
[7]	魏彤, 田双彪. 基于RLS-DE算法的多变量径向磁轴承系统辨识[J]. 机械工程学报, 2016, 52(3): 143-150.
[8]	牟健慧, 郭前建, 高亮, 张伟, 牟建彩. 基于混合的多目标遗传算法的多目标流水车间逆调度问题求解方法^*[J]. 机械工程学报, 2016, 52(22): 186-197.
[9]	车林仙. 多样性保持离散差分进化算法及齿轮传动优化应用^*[J]. 机械工程学报, 2016, 52(21): 44-55.
[10]	吴楠, 张显程, 涂善东, 钱夏夷, 王一宁. 室温和650 ℃下晶粒尺寸对GH4169合金疲劳小裂纹萌生和扩展行为的影响[J]. 机械工程学报, 2016, 52(20): 66-75.
[11]	张扬, 张维刚, 马桃, 唐婷. 基于全局敏感性分析和动态代理模型的复杂非线性系统优化设计方法[J]. 机械工程学报, 2015, 51(4): 126-131.
[12]	张昭, 吴奇. 基于材料流动轨迹的搅拌摩擦焊接晶粒及焊接区大小预测模型[J]. 机械工程学报, 2015, 51(2): 43-48.
[13]	李雄兵, 宋永锋, 胡宏伟, 倪培君. 基于衰减速率的晶粒尺寸超声评价方法[J]. 机械工程学报, 2015, 51(14): 1-7.
[14]	车林仙，杜力，黄勇刚. 球面四杆机构函数综合的带修复策略可行性规则差分进化算法[J]. 机械工程学报, 2015, 51(11): 31-40.
[15]	王前;杨志坚;丁康. 基于新自适应差分进化算法的Magic Formula轮胎模型参数辨识方法研究[J]. , 2014, 50(6): 120-128.