基于RPN和FCN的电力设备锈迹检测

Rust Detection of Power Equipment Based on RPN and FCN

针对电力设备在高温、高压、高流速条件下长期连续运行发生锈蚀隐患难以及时发现的问题,提出一种基于区域建议网络与全卷积神经网络相结合的对无规则锈迹进行检测的方法 RPN-FCN。首先使用区域建议网络生成带锈迹的候选区域,然后对锈迹候选区域进行全卷积操作,从而在像素级别进行精确的分类定位。通过实验对比,结果表明本文提出的方法对于无规则的锈蚀检测更加准确有效。

As the rust risk of power equipment is difficult to be discovered in the long-term continuous operation under high temperature,high pressure and high flow rate conditions,this paper develops an irregular rust detection method RPN-FCN based on region proposal network and fully convolution network.First,region proposal network generates region proposals,then performs a fully convolution operation on region proposals to perform accurate classification and positioning at the pixel level.The experimental results show the method improves the accuracy and effect of irregular rust detection.