Oilfield Pipeline Leakage Monitoring Based on UNet++
Aiming at the problems of initial target of oil leakage is small,the color characteristics of oil is not easy to distinguish in the dark scene,and the residual leakage traces are difficult to be completely removed,and easy to cause misdetection and omission issues.An oil pipeline leakage monitoring network based on UNet++is proposed.The method uses Kind++image enhancement to increase image illumination.SiLU activation function is introduced to ease gradient disappearance,retain more feature information,accelerate network convergence speed,and EMA attention mechanism is introduced to aggregate multi-scale spatial structure information to enhance feature fusion quality.The experimental results show that the accuracy rate of the method is 95.5％,the precision rate is 95.5％,the recall rate is 95.2％,and the average crossover ratio is 91.3％.The method can accurately segment the oil leakage area in dim environment,shielded environment and small target,and can be qualified for pipeline leakage monitoring in oil fields.
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