Abstract:

To address the problem of low accuracy of oil and gas pipeline leakage identification, the digital twintechnology is introduced, and a digital twin pipeline leakage identification model is constructed based onarithmetic optimisation AOA-SVM(Arithmetic Optimization Algorithm-Support Vector Machine). Firstly, the 3DROM(3D Reduced Order Model) pipeline model of oil and gas pipelines is constructed using Ansys software.Secondly, the collected pipeline signals are imported into MySql database through Java interface, and then thedata are imported into the 3D ROM pipeline model. Finally, the AOA-SVM algorithm is used to carry out the work recognition of the pipeline signals in Matlab environment, and the recognition effect is shown in its dynamic form by Twin builder software. The recognition effect is shown in its dynamic form. In order to show the superiority of AOA-SVM condition recognition ability, it is compared with other popular SVM( Support Vector Machine) optimisation algorithms on the basis of the same signal. The comparison results show that AOA-SVM has the highest classification accuracy, which can reach 90. 5% , i. e. , the recognition model of the proposed digital twin can simulate the leakage of pipelines and has a high monitoring credibility.

Key words: support vector machine, digital twinning, digital pipeline, 3D reduced order model(ROM) model