On the Background Levels of Emergency Hazards at Hazardous Production Facilities

Intelligent monitoring of the condition of hydrocarbon pipeline transport facilities using neural network technologies

“…Many Russian research papers [20][21][22] deal with the problems of creating systems for monitoring the reliability and safety of hydrocarbon transport processes by the main pipelines, but the question of providing an operational automated predictive monitoring of technogenic events and conditions during oil and gas transport is still open. To consider various security threats and factors reducing the reliability in the system of main oil and gas pipelines, a rather wide range of diagnostic monitoring tools is used and developed [23][24][25] including those for real-time operation [24][25][26] as well as models for predicting the mode parameters, leaks, and losses [27][28][29].…”

“…1); however, incidents occur, and accidents can reach the scale of a national catastrophe (diesel fuel spill near Norilsk on May 29, 2020). This points to the necessity not only to monitor the background risks [20], but also to create the systems of automated predictive monitoring with functions of control and prevention of technogenic events and their development based on modern models considering all the threats. The development and application of a universal intelligent approach in combination with available scientific developments for solving the tasks, and its systemic application in control [33][34][35] makes it possible to create a system for managing the condition of facilities of the new generation.…”