Chemical Gas Leak Detection Method Based on Infrared Image
MA Yiming
MA Hailiang
ZHANG Xing
SONG Xuehua
LENG Kang
YANG Yang
Abstract：To address the problem of chemical gas leakage occurring in industrial production,a semantic segmentation net-work based on infrared image of leaking gas is proposed for gas leakage detection.The method is based on the semantic segmentation network SegNet,which adds a hopping connection containing an attention mechanism to fuse shallow information in the process of upsampling,and adds a pyramid pooling module at the end of downsampling to enhance the feature extraction ability,and adds a Dropout module between the encoder and decoder to increase the generalization ability of the network.The network is trained by a synthetic dataset with pixel-level annotation,and experiments are conducted on the synthetic and real datasets separately,showing that the network can accurately mark the leaking gas in the infrared image and the speed can meet the requirements of real-time de-tection.
Keywords：semantic segmentationinfrared gas imageleak gas detection
Publication Date：2025-12-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：8( 3557-3564 )