Xu DIAO présentera sa thèse le 5 juin 2022 à 10h00 en vue de l'obtention du diplôme de Doctorat
311 Houde Building
Nanjing Tech University
Identifiant : 937 7721 8584
Code : 9 sbbRb
In order to deal with the problems caused by pipeline leakage, this research first aims at investigating the flow electrification of the intact pipe and the leak pipe. The theoretical models able to calculate the space charge density of intact and leak pipes are proposed. The distributions of the space charge density and electrostatic potential are investigated through numerical simulation. Furthermore, the streaming current inside the pipe and the leakage current from the pipe wall to the ground are also studied by experiments.
Afterward, the risk of the domino effect of fire or explosion accident caused by petrochemical fluid pipeline leakage is studied based on the fault tree analysis (FTA) and in combination with the analytic hierarchy process (AHP) and fuzzy theory.
A pipeline leak detection and location method based on transient flow is proposed. In the leak detection model, the one-dimensional unsteady friction model is introduced into the method of characteristics (MOC). Then, the governing equations are derived as a ternary system of equations, in which the unknown parameters, especially leak size coefficient, are obtained by analyzing the first transient pressure wave.
Furthermore, a pipeline leak detection and location method based on the acoustic emission (AE) technology is also proposed. An improved signal decomposition method based on particle swarm optimized variational modal decomposition (PSO-VMD) is proposed to denoise AE signals. The leakage detection methods based on supervised learning (SVM) and semi-supervised learning (PCA) are performed, respectively. The wave velocity for leak location is obtained according to the dispersion guided wave curve of actual pipeline. Finally, the leakage location is carried out according to the time delay estimation, and the location error is between 0.8% and 12.1%.