基于深度学习算法的远场涡流反馈波形图像自动识别技术  

Automatic recognition technology of remote field eddy current feedback waveform images based on deep learning algorithm

作　　者：陈国宝 林宝森 林志贤 涂宏应 徐光平 冯冰 CHEN Guobao;LIN Baosen;LIN Zhixian;TU Hongying;XU Guangping;FENG Bing(Quanzhou Thermoelectric Co.,Ltd.,National Energy Group,Quanzhou 362804,China;Beijing TRI-TECH Co.,Ltd.,Beijing 100085,China)

机构地区：[1]国家能源集团泉州热电有限公司,福建泉州362804 [2]北京中安吉泰科技有限公司,北京100085

出　　处：《中国高新科技》2023年第7期43-47,共5页

摘　　要：文章介绍了远场涡流的原理和历史,详细阐述了涡流信号各个缺陷波形的特点,以及常见的异常诱因,为远场涡流信号的预处理和模型评估提供相关的诊断检测缺陷知识支撑。This article introduces the principle and history of far field eddy current,elaborates on the characteristics of each defect waveform of eddy current signals,as well as common abnormal causes,providing relevant diagnostic and defect detection knowledge support for the preprocessing and model evaluation of far field eddy current signals.

关 键 词：无损检测 远场涡流 自动识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]