基于红外视频的VOCs泄漏源定位与气羽实例分割  

VOCs Leakage Source Location and Gas Plume Instance Segmentation Based on Infrared Video

作　　者：江逸远 谷小婧[1] 顾幸生[1] JIANG Yiyuan;GU Xiaojing;GU Xingsheng(Key Laboratory of Smart Manufacturing in Energy Chemical Process,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China)

机构地区：[1]华东理工大学能源化工过程智能制造教育部重点实验室,上海200237

出　　处：《华东理工大学学报（自然科学版）》2024年第5期695-707,共13页Journal of East China University of Science and Technology

基　　金：国家自然科学基金(61973122,62173143)。

摘　　要：为实现对基于红外视频的挥发性有机化合物(VOCs)的自动化检测,提出了一种泄漏源定位和气羽实例分割的协同建模方法,既保证了模型对气羽实例的区分,也保证了每个实例只预测一个泄漏源,并支持单支路网络通过单次前向推理同时进行泄漏源定位和实例分割。考虑到泄漏源附近的气羽逸散特性,使用泄漏源位置作为气羽在嵌入空间的聚类中心,并根据泄漏气羽的时空分布选取高斯分布概率密度函数的协方差变量,对嵌入空间内的像素进行聚类,得到不同实例的泄漏源定位和实例分割结果。将泄漏源定位问题定义为具有单一关键点的关键点检测问题并给出定量评价指标。此外,通过合成数据集获得更加精确且易于获取的标注。实验结果表明,本文提出的方法可以对泄漏气羽进行较为准确的泄漏源定位和实例分割,综合定量指标高于其他同类方法,且在真实视频中具有良好的泛化性。In order to realize automated detection of volatile organic compounds(VOCs)based on infrared video,a collaborative modeling method for leakage source location and air plume instance segmentation is proposed.This not only ensures that this model can distinguish gas plume instances,but also ensures that each instance only predicts one leak source.It supports a single branch network to simultaneously achieve the leakage source location and instance segmentation through a single forward inference.Considering the escape characteristics of gas plumes near the leakage source,the location of the leakage source is used as the clustering center of the gas plumes in the embedding space.Based on the spatiotemporal distribution of the leakage gas plume,the covariance variables of the Gaussian distribution probability density function are selected to cluster the pixels in the embedding space and the leakage source location and instance segmentation results for different instances are obtained.The leakage source localization problem is defined as a key point detection problem with a single key point and quantitative evaluation indicators are given.In addition,more precise and accessible annotations are obtained by synthesizing the dataset.Experimental results show that the proposed method can accurately locate the leakage source and segment instances of the gas plume,with higher comprehensive quantitative index than other similar methods,and has good generalization in real videos.

关 键 词：红外气体成像 气体泄漏检测 泄漏源定位 实例分割 合成数据 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]