«Proceedings of Gubkin University»

Optimization of procedures for office stage of in-line inspection using methodology of sufficient statistics

UDC: 622.691.4
DOI: -

Authors:

¹ National University of Oil and Gas “Gubkin University”, Moscow, Russian Federation
² Don State Technical University, Rostov-on-Don, Russian Federation

Keywords: digital signal processing, algorithm, sufficient statistics, in-line inspection, weld seam, office-stage data analysis

Annotation:

The study focuses on developing an algorithm to process signals from magnetic field sensors of an in-line inspection tool during the office stage of data analysis. A description of existing approaches is provided, taking into account the development of modern digital signal processing methods. Special emphasis is placed on optimizing the analyst's working time during office-based data processing, which provides a direct economic benefit and reduces the influence of human factors in routine tasks. The necessity of automating the business process through a robust algorithm is demonstrated. The proposed solution utilizes the methodology of sufficient statistics based on the Rao – Blackwell – Lehmann – Scheffé theorem as a tool to estimate parameters of periodic signals corresponding to weld seams observed in magnetic detection data. A mathematical model is developed, forming the basis for evaluating the potential accuracy of the proposed methods. It is established that, for sample sizes n > 15, the relative root means square error in estimating the weld signal repetition period using the sufficient statistics methodology is significantly lower compared to traditional estimation methods. The results are validated across a wide signal-to-noise ratio range from 0 to 10 dB, where traditional estimators typically encounter challenges. In addition to theoretical calculations, modeling results are presented, confirming the achieved effect. The calculation and modeling data are illustrated with graphs and diagrams, demonstrating the robustness of the proposed methodology to variations in n and signal-to-noise ratio. The obtained results have a broad range of applications and can be utilized in the design of control and measurement equipment, development of medical devices, telecommunications, and the design of pulse-Doppler radars, among other fields.

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