Research on Spatial Coordinate Estimation of Karst Water-Rich Pipelines Based on Strapdown Inertial Navigation System

In the field of tunnel engineering, the precise determination of the spatial coordinates of karst water-rich pipelines represents a critical area of research for disaster prevention and control. Traditional detection methods often exhibit limitations, including inadequate accuracy and low efficiency...

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Bibliographic Details
Main Authors: Zhihong Tian, Wei Meng, Xuefu Zhang, Bowen Wan
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Buildings
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Online Access:https://www.mdpi.com/2075-5309/15/15/2644
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Summary:In the field of tunnel engineering, the precise determination of the spatial coordinates of karst water-rich pipelines represents a critical area of research for disaster prevention and control. Traditional detection methods often exhibit limitations, including inadequate accuracy and low efficiency, which can significantly compromise the safety and quality of tunnel construction. To enhance the accuracy of the spatial coordinate estimation for karst water-rich pipelines, this study introduces a novel method grounded in a strapdown inertial navigation system (SINS). This approach involves the deployment of sensing equipment within the karst water-rich pipeline to gather motion state data. Consequently, it provides spatial coordinate information pertinent to the karst water-rich pipeline within the tunnel site, thereby augmenting the completeness and accuracy of the spatial coordinate estimation results compared to conventional detection methods. This study employs ESKF filtering to process the data collected by the SINS, ensuring the robustness and accuracy of the data. The research integrates theoretical analysis, model testing, and numerical simulation. It systematically examines the operational principles and error characteristics associated with the SINS, develops an error model for this technology, and employs a comparative selection method to design the spatial coordinate sensing equipment based on the SINS.
ISSN:2075-5309