基于YOLOv5s-CBAM的海上平台注水流程现场漏液智能检测

Intelligent Monitoring System for Field Leakage of Water Injection Process of Offshore Platform Based on YOLOv5s-CBAM

针对海上平台注水流程现场原油泄漏问题,提出基于双通道注意力机制的改进YOLOv5s模型,实现漏液智能检测。首先,通过监控摄像头及单反相机采集海上平台注水流程现场漏液数据并对其进行标注。其次,将双通道注意力机制引入YOLOv5s模型,增强模型的特征提取能力,构建高精度漏液检测模型。最后,对该模型进行功能及性能测试。测试结果表明,该检测模型可大幅度提升海上平台注水流程现场漏液检测能力。

To address the crude oil leakage problem at the offshore platform injection process site,the YOLOv5s model is improved by adopting a dual-channel attention mechanism to achieve intelligent leakage detection.In order to build an algorithm model that can achieve high-precision liquid leakage detection,this paper introduces a dual-channel attention mechanism on the basis of the YOLOv5s model to enhance the feature extraction capability of the model,so as to achieve automatic detection of liquid leakage in the monitoring video.Finally,function and performance tests are conducted on this model.Test results show that this model is capable of significantly improving the detection capability of liquid leakage in the field of water injection process on offshore platform.