A novel neural model-based approach to leak detection and localization in oil pipelines for environmental protection

Monitoring oil transporting pipelines is an important task for economical and safe operation, loss prevention, and environmental protection from crude oil emission. The leak detection of oil pipelines, therefore, plays a key role in the overall integrity monitoring of a pipeline system. This paper proposes a neural decision-making approach to oil pipeline leak localization. The one main methods, model based fault detection is used (to find leaks quantity and location-making) to form a novel fault diagnosis scheme. This scheme can improve the precision of localization. An application example, 600m long oil pipeline leak detection and localization are illustrated, and the effectiveness of the proposed approach is demonstrated using practical results.