摘要
针对304奥氏体不锈钢顺磁性材料,提出了将多类分类支持向量机Libsvm算法用于弱磁信号磁异常反演的研究。采用正交试验设计,制作4块304奥氏体不锈钢试块,共16组人工槽缺陷并使用弱磁检测对试块进行检测。对采集到的缺陷信号磁异常提取占宽、幅值、面积等特征值,使用Libsvm算法建立缺陷信号磁异常与缺陷之间的联系,并测试每组缺陷的反演结果。结果表明:16组缺陷中有10组长度和宽度反演正确,有8组深度反演正确。缺陷长度、宽度、深度的反演精度较高,为弱磁信号磁异常反演研究、相关实验方法和设备开发等提供了参考依据。
Aiming at 304 austenitic stainless steel paramagnetic material,a multi-class classification support vector machine LIBSVM algorithm was carried out for the magnetic anomaly inversion of weak magnetic signals.Orthogonal test design was used to make 4 testing samples with an artificial defect.The characteristics of artificial defect such as width,amplitude,and area were extracted for the collected magnetic anomalies of the defect signals.The LIBSVM algorithm was used to establish the relationship between the magnetic anomalies of the defect signals and the artificial defects.A total of 16 groups testing results indicate that 10 of the 16 defects inversion are correct in length and width,and 8 defects inversion are correct in depth.The inversion accuracy of defect length,width and depth is high,which provides a reference basis for the study of magnetic anomaly inversion for weak field signals,related experimental methods and equipment development.
作者
郭萌梦
胡博
彭贤虎
廖连文
GUO MengMeng;HU Bo;PENG XianHu;LIAO LianWen(Key Laboratory of Non-destructive Testing of Ministry of Education,Nanchang Hangkong University,Nanchang 330063,China)
出处
《机械强度》
CAS
CSCD
北大核心
2021年第2期293-299,共7页
Journal of Mechanical Strength
基金
国家自然科学基金项目(51967014,51765048)
江西省自然科学基金项目(20192BAB206031)
南昌航空大学研究生创新专项(YC2018045)资助。
关键词
304奥氏体不锈钢
人工槽缺陷
支持向量机Libsvm
弱磁检测
反演
304 austenitic stainless steel
Artificial groove defect
Support vector machine LIBSVM
Weak magnetic detection
Inversion
