基于多特征量的脉冲涡流平底盲孔缺陷测厚方法
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1.中国石油大学华东控制科学与工程学院;2.中国石油大学华东海洋与空间信息学院

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TG115.28

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国家重点研发计划项目(2016YFC0802302)


Thickness measurement method of flat bottom blind hole defect based on multi feature quantity by pulsed eddy current
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School of control science and engineering, China University of Petroleum (East China)

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    摘要:

    采用脉冲涡流技术开展承压设备壁厚检测时,若待检测的缺陷尺寸小于传感器尺寸时,则实际检测的厚度要远大于设备真实厚度。通过仿真分析,发现利用单一的特征量反演得到的检测厚度实质为传感器接收范围内试件的平均厚度,而并非试件缺陷处的真实厚度。针对此问题,首先根据缺陷类型的最小特征数,建立多个特征量与试件缺陷特征的映射关系,之后,利用PCA技术在众多特征量中确定反演效果最佳的特征量组合,最后提出一种基于多特征量的检测方法用于反演试件厚度。本文利用仿真数据验证了该方法的可行性,同时利用平底盲孔测试件进行了实验验证。结果显示,平底盲孔测试件壁厚的反演误差可控制在5%之内,表明该方法具有广泛的工程应用价值。

    Abstract:

    when using pulsed eddy current technology to detect the wall thickness of pressure equipment, if the defect size to be detected is smaller than the sensor size, the actual thickness to be detected is much greater than the true thickness of the equipment. Through the simulation analysis, it is found that the detection thickness obtained by using a single characteristic quantity inversion is the average thickness of the specimen within the receiving range of the sensor, rather than the real thickness of the specimen defect. In order to solve this problem, firstly, according to the minimum feature number of defect type, the mapping relationship between multiple feature quantities and defect features of specimen is established. Then, PCA technology is used to determine the best combination of feature quantities. Finally, a detection method based on multiple feature quantities is proposed to inverse the thickness of specimen. In this paper, the feasibility of the method is verified by the simulation data, and the experimental verification is carried out by using the flat bottom blind hole test piece. The results show that the wall thickness inversion error of flat bottom blind hole test piece can be controlled within 5%, which indicates that the method has a wide range of engineering application value.

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孙国健,万勇,郝宪锋,等. 基于多特征量的脉冲涡流平底盲孔缺陷测厚方法[J]. 科学技术与工程, , ():

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  • 收稿日期:2021-06-25
  • 最后修改日期:2021-11-16
  • 录用日期:2021-11-22
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