[1]邱张维佳,王志强,秦承鹏.基于机器视觉的标准试片磁痕评价方法[J].热力发电,2023,52(01):140-148.[doi:10.19666/j.rlfd.202206167]
　QIU Zhangweijia,WANG Zhiqiang,QIN Chengpeng.Research and application of magnetic trace evaluation method for standard test shims based on machine vision[J].Thermal Power Generation,2023,52(01):140-148.[doi:10.19666/j.rlfd.202206167]
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基于机器视觉的标准试片磁痕评价方法

《热力发电》[ISSN:1002-3364/CN:61-1111/TM] 卷: 52 期数: 2023年01期 页码: 140-148 栏目: 发电技术论坛 出版日期: 2023-01-08
Title:
Research and application of magnetic trace evaluation method for standard test shims based on machine vision
作者:
邱张维佳; 王志强; 秦承鹏
西安热工研究院有限公司，陕西 西安 710054
Author(s):
QIU Zhangweijia;  WANG Zhiqiang;  QIN Chengpeng
Xi’an Thermal Power Research Institute Co., Ltd., Xi’an 710054, China
关键词:
磁粉检测; 机器视觉; 磁痕图像; OpenCV; 标准试片
DOI:
10.19666/j.rlfd.202206167
摘要:
磁粉检测作为一种无损检测方法，在电力行业有广泛应用，其综合灵敏度由A1型标准试片检验，然而标准试片磁痕的清晰度评价仍取决于检测人员的主观判断。为排除磁痕清晰度评价中人为主观因素，提出一种基于机器视觉的标准试片磁痕清晰度评价方法。对获取的标准试片磁痕图像，使用Python程序设计语言调用OpenCV函数库，实现对磁痕图像的掩膜获取，然后通过二值化提取磁痕以及计算磁痕与背景的直方图，定量分析与评价磁痕图像的清晰度，同时使用该方法确定了非磁性层厚度对磁粉检测综合灵敏度的影响。标准试片磁痕图像分析结果可知，基于机器视觉的标准试片磁痕提取效果良好，清晰度评价结果比传统人工评价更加客观可靠。

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（责任编辑 杜亚勤）

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备注/Memo

邱张维佳（1993），男，博士，工程师，主要研究方向为无损检测与电站材料分析，qiuzhangweijia@tpri.com.cn。

更新日期/Last Update: 2023-01-15