Accuracy improvement of inner defects of cylindrical components using ultrasonic detection with modified ALOK method

Hai Gong, Jia Liu, Tao Zhang, Xuan Cao, Long Zhang
{"title":"Accuracy improvement of inner defects of cylindrical components using ultrasonic detection with modified ALOK method","authors":"Hai Gong, Jia Liu, Tao Zhang, Xuan Cao, Long Zhang","doi":"10.1784/insi.2024.66.3.159","DOIUrl":null,"url":null,"abstract":"The accuracy of defect localisation and its size quantification is poor in the detection of internal defects of cylindrical components using the ultrasonic Amplituden und Laufzeit Orts-Kurven (ALOK) method. The influence of acoustic beam spread is not taken into consideration in the\n ultrasonic ALOK method, resulting in difficulties with the precise characterisation of the defect state. To address this, the relationship between the acoustic distance, amplitude, ultrasonic frequency, size and depth of hole defects was studied. The acoustic distance curve and the amplitude\n curve were fitted and then the localisation model of the defect was obtained. The acoustic beam spreading angle and echo sound pressure were introduced and then the size quantification model for defects was acquired based on principal component analysis (PCA). Both the simulated and experimental\n results show that the modified ALOK algorithm improved the detection accuracy of the defect location and its size and the relative error of defect sizing decreased by more than 35% compared with the original algorithm.","PeriodicalId":506650,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Insight - Non-Destructive Testing and Condition Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1784/insi.2024.66.3.159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The accuracy of defect localisation and its size quantification is poor in the detection of internal defects of cylindrical components using the ultrasonic Amplituden und Laufzeit Orts-Kurven (ALOK) method. The influence of acoustic beam spread is not taken into consideration in the ultrasonic ALOK method, resulting in difficulties with the precise characterisation of the defect state. To address this, the relationship between the acoustic distance, amplitude, ultrasonic frequency, size and depth of hole defects was studied. The acoustic distance curve and the amplitude curve were fitted and then the localisation model of the defect was obtained. The acoustic beam spreading angle and echo sound pressure were introduced and then the size quantification model for defects was acquired based on principal component analysis (PCA). Both the simulated and experimental results show that the modified ALOK algorithm improved the detection accuracy of the defect location and its size and the relative error of defect sizing decreased by more than 35% compared with the original algorithm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用改良 ALOK 方法进行超声波检测,提高圆柱形部件内部缺陷的精度
在使用超声波振幅和时间间隔法(ALOK)检测圆柱形部件内部缺陷时,缺陷定位和尺寸量化的准确性较差。在超声波 ALOK 方法中没有考虑声束传播的影响,导致难以精确表征缺陷状态。为了解决这个问题,我们研究了声距、振幅、超声频率、孔洞缺陷的大小和深度之间的关系。通过拟合声距曲线和振幅曲线,得到了缺陷定位模型。引入声束展宽角和回波声压后,基于主成分分析(PCA)获得了缺陷尺寸量化模型。模拟和实验结果表明,改进后的 ALOK 算法提高了对缺陷位置及其大小的检测精度,与原始算法相比,缺陷大小的相对误差减少了 35% 以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Contrast-based notch-to-crack transfer function for digital radiography Modelling and simulation for the investigation on the ultrasonic propagation mechanism in advanced microelectronic packages Noise recognition of moving parts in a sealed cavity based on the fusion of recognition results and high-dimensional mapping Thermal non‐destructive testing and evaluation for inspection of carbon fibre‐reinforced polymers Overview of welding defect detection utilising metal magnetic memory technology
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1