Leakage detection in a gas pipeline using artificial neural networks based on wireless sensor network and Internet of Things

In this paper, a neural network-based method for leakage detection of a gas pipeline by using gas flow pattern is proposed. The pipe is divided in several segments and each segment is modeled by considering input/output pressure of the gas flow. The idea is to use a computer network based on Internet of Things (IOT) phenomena to gather all the required information for detection of the leakage point. In order to process the acquired data from the pipeline, a neural network is used and trained. As usual some of the data are used as training set to adjust the neural network weights and some other are used to evaluate the performance of the neural network based fault detection system. Practical data gathered from a real life pipeline is used to train the network to make sure that the proposed method is applicable real life projects.