Diagnostic Algorithm Quality of the State of Underground Metal Structures the Using Neural Networks

Author:

Lozovan VitaliiORCID,

Abstract

The underground metal structures function in specific conditions of the soil environment and cyclic mechanical loads. It is necessary to conduct a detailed analysis of underground metal structures and monitor their technical condition, since damage and destruction of structural elements during operation can lead to dangerous and/or catastrophic consequences. Intelligent monitoring systems are able to control the life cycle of underground pipelines based on a comprehensive analysis of their current state, operating loads and the results of interaction with the environment.

Publisher

Karpenko Physico-Mechanical Institute of the NAS of Ukraine

Reference4 articles.

1. 1. Schweidtmann A.M. and Mitsos A. Global Deterministic Optimization with Artificial Neural Networks Embedded // J. Optim. Theory Appl. -2018. -180. - P. 925-948.

2. 2. Ren G., Cao Y., Wen S., Huang T. and Zeng, Z. A modified Elman neural network with a new learning rate scheme // Neurocomputing. - 2018. - 286. - P. 11-18.

3. 3. Lozovan V.P. Diagnostic algorithm for optimization electrophysical parameters of underground metal constructions taking into account the quality criterion and the method of neural network // International Young Scientists Conference on Materials Science and Surface Engineering MSSE2021 (September 22-24, Lviv, Ukraine): Proc. - Lviv, 2021. - P. 184-187.

4. 4. Dzhala R., Senyuk O. and Lozovan V. Contactless testing of insulation damages distribution of the underground pipelines // Procedia Struct. Integr. - 2022. - 36. - P. 17-23.

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