金属疲劳损伤过程中表面形貌的多分辨特征提取  

Multiresolution Feature Extraction of Surface Topography in Metal Fatigue Damage Process

作　　者：刘涛 尹志强 雷经发 汪方斌 Liu Tao;Yin Zhiqiang;Lei Jingfa;Wang Fangbin(School of Mechanical and Electrical Engineering,Anhui Jianzhu University,Hefei,Anhui 230601,China;Anhui Provincial Key Laboratory of Intelligent Manufacturing of Construction Machinery,Hefei,Anhui 230601,China)

机构地区：[1]安徽建筑大学机械与电气工程学院,安徽合肥230601 [2]工程机械智能制造安徽省教育厅重点实验室,安徽合肥230601

出　　处：《激光与光电子学进展》2022年第8期434-443,共10页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(51805003);安徽省高校优秀拔尖人才培育资助项目(gxyqZD2019057);安徽高校协同创新项目(GXXT2019-022)。

摘　　要：为揭示疲劳损伤过程中金属表面形貌特征的变化规律,以Q235碳钢试样为对象,采集各疲劳损伤阶段试样表面的三维形貌信息并将其转化为灰度图,采用快速离散剪切波变换对图像进行分解和重构,获取到包含粗糙度、波纹度、形状误差信息的子图。利用灰度共生矩阵描述粗糙度子图纹理特征,得到了疲劳损伤过程能量、相关值、反差和逆差矩4类特征参数的变化规律。取一系列分解层数,开展多分辨分析,对比分析了不同分解层数对上述特征参数值的影响。结果表明:随着循环周次的增加,能量值和逆差矩值降低,反差值增加,上述特征量值的大小与提取方向的选取有关。疲劳断裂前,能量和逆差矩值突然升高,反差值突然降低。基于反差、能量和逆差矩三特征构建了支持向量机分类模型,此模型可用于构件疲劳损伤状态的评估。To reveal the law of features change of metal surface topography during fatigue damage,we collected and transformed the threedimensional surface topography information of Q235 carbon steel specimens into grayscale images at each fatigue damage stage.Then,these images were decomposed and reconstructed using fast discrete shear wave transform to obtain subimages containing roughness,waviness,and shape error.Furthermore,the graylevel cooccurrence matrix was used to describe the characteristics of the subimages’roughness.The variation rules of four characteristic parameters,namely,energy,correlation,contrast,and homogeneity,were obtained for the fatigue damage process.In addition,a series of decomposition layers were taken for multiresolution analysis,and the effects of different decomposition layers on the values of the abovementioned characteristic parameters were compared and analyzed.Results show that the increasing fatigue cycles decrease the energy and homogeneity values and increase contrast values.The above characteristic values are related to the selection of extraction directions.Before fatigue fracture,the energy and homogeneity values suddenly increase,whereas the contrast value sharply decreases.Thus,a support vector machine classification model was constructed based on the three features,including contrast,energy,and homogeneity,and was used for fatigue damage state assessment of components.

关 键 词：图像处理 金属表面 三维形貌 特征提取 多分辨分析 

分 类 号：TH164[机械工程—机械制造及自动化]