首页|基于超声辅助的汽车微小零部件内部缺陷无损检测方法

基于超声辅助的汽车微小零部件内部缺陷无损检测方法

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原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
为了更准确、全面地分析汽车微小零部件缺陷,基于超声辅助的方式,设计了内部缺陷无损检测方法.根据超声波传播反射情况及声场变化,采集微小零部件图像;通过融合边缘信息消除图像中噪声,分割图像主体并完成边缘识别,确定存在内部缺陷的区域;利用核主成分分析技术,通过降维处理方式确定缺陷区域特征,进而完成无损检测.结果表明:利用所提方法获取的零部件图像清晰,缺陷检测准确率始终高于95%,对气泡和气孔缺陷的检测时间小于 6s,对裂纹缺陷的检测时间小于8s,说明所提方法对内部缺陷的定位准确度和识别效率均较高.
Ultrasonic assisted nondestructive testing method for internal defects of automotive micro-parts
In order to analyze the defects of automotive micro-parts more accurately and completely,a nondestructive testing method based on ultrasonic assisted mode for internal defects was designed.According to the transmission and reflection of ultrasonic wave and the change of sound field,the images of micro-parts were collected.After the de-noising of image through the edge information fusion,the image was segmented and the edge information was recognized to determine the internal defect location.Kernel principal component analysis technology was used to detect the features of defective location through dimension reduction processing,in order to complete nondestructive testing.The results show that the images of micro-parts obtained by this method are relatively clear,the precision rate of defect detection is always higher than 95%,the detection time for bubble and pore defects is less than 6 s,and less than 8 s for crack defect detection,showing that this method has higher localization accuracy and detection efficiency for internal defects.

ultrasound assisted modeultrasonic sound fieldmicro-partmorphologygray level segmentation methodkernel principal component analysisinternal defectnondestructive testing

关亮亮、田国红

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辽宁工业大学 汽车与交通工程学院,辽宁 锦州 121001

超声辅助方式 超声声场 微小零部件 形态学 灰度分割法 核主成分分析 内部缺陷 无损检测

国家自然科学基金面上项目

51675257

2024

10.7688/j.issn.1000-1646.2024.03.13

沈阳工业大学学报
沈阳工业大学

沈阳工业大学学报

CSTPCD北大核心
影响因子：0.62
ISSN：1000-1646
年,卷(期)：2024.46(3)
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