Authors: I.I. Rastvorova, S.A. Trufanov

Title of the article: Modeling of the control and diagnostics system of the electrical complex of the drilling rig

Year: 2025, Issue: 4, Pages: 12-21

Branch of knowledge: 2.4.2. Electrotechnical complexes and systems (engineering)

Index UDK: 621.398

DOI: 10.26730/1816-4528-2025-4-12-21

Abstract: The requirements for the reliability and safety of the electrical systems of drilling rigs, which are operated in harsh conditions, are constantly growing. That is why the problem of improving the methods of monitoring and diagnosing these systems is urgent, which will reduce the likelihood of emergencies and increase their efficiency. The article is devoted to the development of a model for monitoring and diagnostics of electrical systems of drilling rigs, based on the use of modern wireless telecommunications technologies that do not require additional laying of communication cables between various elements of the drilling rig and the control center. The key components of the system are integrated sensors with telecommunication modules that provide real-time data transmission to the driller's personal computer for subsequent analysis. The paper analyzes existing diagnostic methods, and proposes a control system architecture that allows evaluating system parameters in real time. Laboratory experiments were conducted to verify the adequacy of the model, as well as tests on real equipment to verify the results obtained. For data analysis, it is proposed to use machine learning algorithms to increase the speed of detecting optimal parameters and abnormal behavior of drilling equipment. The main results of the work include: the development of an architecture for monitoring and diagnostics of the drilling complex, as well as the development of an algorithm for processing data from a temperature sensor in real time. The results of the study can be adapted for implementation in various types of drilling operations and operating conditions in order to minimize downtime and optimize the cost of maintaining drilling rigs.

Key words: drilling management optimization automation algorithm

Receiving date: 04.04.2025

Approval date: 30.06.2025

Publication date: 28.08.2025

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