An improved surface roughness measurement method for micro-heterogeneous texture in deep hole based on gray-level co-occurrence matrix and support vector machine
An improved surface roughness measurement method for micro-heterogeneous texture in deep hole based on gray-level co-occurrence matrix and support vector machine
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DOI：
10.1007/s00170-013-5048-0
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
Wei Liu;Xianming Tu;Zhenyuan Jia;Wenqiang Wang;Xin Ma;Xiaodan Bi
中科院分区：
文献类型：
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作者：
Wei Liu;Xianming Tu;Zhenyuan Jia;Wenqiang Wang;Xin Ma;Xiaodan Bi
利用显微图像的频域特征和遗传算法优化的BP人工神经网络，将显微视觉系统应用于深孔微异质结构表面粗糙度的测量。但是，测量精度还有待提高，以便于工程应用。提出了一种基于显微视觉的气门R型面表面粗糙度检测方法。首先介绍了深孔R面粗糙度测量系统。然后，采用灰度共生矩阵（GLCM）方法对R型表面形貌图像进行分析，提取与表面粗糙度近似单调的显微图像特征，建立了R型表面粗糙度的精确预测模型。此外，支持向量机（SVM）模型来描述的灰度共生矩阵的功能和实际的表面粗糙度的关系。实验结果表明，GLCM-SVM模型对深孔微观非均匀纹理表面粗糙度的评价具有较高的精度和泛化能力。
Microscopic vision system has been employed to measure the surface roughness of micro-heterogeneous texture in deep hole, by virtue of frequency domain features of microscopic image and back-propagation artificial neural network optimized by genetic algorithm. However, the measurement accuracy needs to be improved for engineering application. In this paper, we propose an improved method based on microscopic vision to detect the surface roughness of R-surface in the valve. Firstly, the measurement system for the roughness of R-surface in deep hole is described. Thereafter, the surface topography images of R-surface are analyzed by the gray-level co-occurrence matrix (GLCM) method, and several features of microscopic image, which are nearly monotonic with the surface roughness, are extracted to fabricate the prediction model of the roughness of R-surface accurately. Moreover, a support vector machine (SVM) model is presented to describe the relationship of GLCM features and the actual surface roughness. Finally, experiments on measuring the surface roughness are conducted, and the experimental results indicate that the GLCM-SVM model exhibits higher accuracy and generalization ability for evaluating the microcosmic surface roughness of micro-heterogeneous texture in deep hole.