САНКТ-ПЕТЕРБУРГСКИЙ ГОРНЫЙ УНИВЕРСИТЕТ ИМПЕРАТРИЦЫ ЕКАТЕРИНЫ II

ПЕРВОЕ ВЫСШЕЕ ТЕХНИЧЕСКОЕ УЧЕБНОЕ ЗАВЕДЕНИЕ В РОССИИ

Modeling the Transient Resistance of Trunk Pipeline Insulation Based on Measurements of the Magnetic Induction Vector Modulus

Ссылка для цитирования (ENG)

Krizsky Vladimir Nikolayevich , Viktorov S. V., Luntovskaya Y. A. Modeling the Transient Resistance of Trunk Pipeline Insulation Based on Measurements of the Magnetic Induction Vector Modulus Mathematical Models and Computer Simulations. 2023. №2. pp. 312-322. DOI: 10.1134/S2070048223020102

Авторы

Krizsky Vladimir Nikolayevich , Viktorov S. V., Luntovskaya Y. A.

Журнал

Mathematical Models and Computer Simulations

Год

2023

Ключевые слова


Аннотация

Interpretation of the magnetometry data of trunk pipelines in order to assess the state of their insulating coating is a relevant subtask for automated control systems for the process of pipeline operation. Determining the transient resistance at the ground/pipe boundary is an inverse problem of mathematical physics. In the article, a mathematical model of the inverse problem of determining the transient resistance at the ground/pipe boundary is constructed according to measurements in air of the modulus of the magnetic induction vector of the magnetic field excited by a direct electric current of the cathodic electrochemical protection of the pipeline. In the class of bounded piecewise constant functions, the solution is sought by A.N. Tikhonov’s method as an extremal of the regularizing functional. The results of the computational experiment demonstrate the possibility of determining the transient resistance of the outer insulating coating of the pipeline according to the measurements of the magnetic induction vector in air at heights varying from 2 to 4 lengths of the defective segments. [Перевод статьи: Кризский В.Н., Викторов С.В., Лунтовская Я.А. Моделирование переходного сопротивления изоляции магистрального трубопровода по данным измерений модуля вектора магнитной индукции //Математическое моделирование – 2022. –№9 – С.107-122. DOI: 10.20948/mm-2022-09-07]