journal article·2026-02-18Open access

Moment of Inertia Identification of a Top Drive–Drill String System Based on Dynamic Response Analysis

Zhipeng Xu, Xingming Wang, Li Zhang, Qiaozhu Wang, Yixuan Xin

Applied Sciences· Volume 16· Issue 4

Abstract

Accurate identification of the rotational moment of inertia of a top drive system is essential for dynamic modeling, control design, and performance optimization in drilling operations. However, the strong coupling between the drive motor, transmission components, and drill string makes direct inertia measurement challenging under field conditions. To address this issue, this study proposes a moment of inertia identification method based on dynamic response analysis of the top drive system. A simplified torsional dynamic model is established by representing the top drive and drill string assembly as an equivalent lumped inertia system. By applying controlled torque excitation under no-load conditions, the system’s angular velocity response is measured and analyzed in both time and frequency domains. The relationship between applied torque and angular acceleration is utilized to identify the equivalent rotational inertia through parameter estimation. Experimental results indicate that low-frequency excitation provides more favorable conditions for reliable and accurate inertia identification, yielding improved stability and reduced estimation error compared with higher-frequency inputs. In addition, frequency response characteristics are investigated to validate the consistency and robustness of the identified inertia across different excitation frequencies. Experimental results obtained from a top drive test rig demonstrate that the proposed method can reliably estimate the equivalent moment of inertia with good repeatability under controlled experimental conditions. The identified inertia shows good agreement with theoretical calculations and exhibits stable behavior over a wide frequency range. The proposed approach avoids the need for additional sensors or structural modifications and is well suited for practical engineering applications. This study provides an effective and experimentally validated method for inertia identification of top drive systems, offering valuable support for dynamic modeling, control parameter tuning, and vibration analysis in drilling engineering.
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Research context

OpenAlex topics: Control Systems in Engineering · Drilling and Well Engineering · Hydraulic and Pneumatic Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu 610059, China

Tianfu Yongxing Laboratory, Chengdu 610213, China

Key Laboratory of Fluid and Power Machinery, Ministry of Education, Xihua University, Chengdu 610039, China

Funding

National Natural Science Foundation of China

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