Abstract: Thin-walled pipelines, with their significant economic advantages, mainly due to the lightweight characteristics and lower manufacturing costs brought about by reduced material usage, coupled with excellent performance, including superior corrosion resistance and high strength to weight ratio, have been widely used in diversified industrial scenarios such as chemical processing plants, oil and gas transportation systems, and power generation facilities. These structures are particularly favored in large-scale infrastructure projects where material efficiency and operational economy are paramount. However, under severe operating conditions, such as rapid temperature variations, high-pressure corrosive environments, or high-frequency mechanical vibrations, the cross-sectional loads of thin-walled pipelines are prone to significant fluctuations and complex dynamic responses. These loading variations substantially increase the risk of structural integrity compromises through local buckling phenomena, plastic deformation mechanisms, or stress-corrosion cracking failures, particularly at critical sections like weld joints and support attachments. Consequently, the accurate extraction, precise analysis, and systematic optimization of cross-sectional loads in thin-walled pipelines have become essential research objectives—not only for enhancing their load-bearing capacity through improved design methodologies but also for developing proactive maintenance strategies to prevent fatigue-induced failures and catastrophic fractures. Such advanced monitoring capabilities are crucial for ensuring the long-term structural reliability and operational safety of pipeline systems, especially in critical infrastructure applications where failure consequences are severe. Current industrial practices primarily rely on periodic manual inspections or simplified analytical models, which often fail to capture the full complexity of real-time loading conditions and their evolution throughout the operational lifecycle. In this paper, an innovative methodology for extracting cross-sectional loads in thin-walled pipelines based on distributed strain measurement data was proposed. The comprehensive approach involved installing optimized sensor networks along the pipeline surface to capture strain variations, calculating equivalent stress values through constitutive material relationships, and subsequently back-calculating the multi-axial loads acting on critical cross-sections through advanced inverse analysis algorithms. This integrated measurement-to-load transformation enabled continuous real-time monitoring of cross-sectional force conditions, including axial forces, bending moments, torsional loads, and shear forces, with high temporal resolution and accuracy. The methodological framework incorporated compensation mechanisms for temperature effects, material non-linearity, and boundary condition uncertainties to ensure robust performance under varying operational conditions. The rationality and accuracy of the proposed methodology were rigorously validated through comprehensive comparative analysis using advanced finite element software simulations. A series of numerical experiments were conducted on various pipeline configurations under different loading scenarios, with systematic comparisons between the reconstructed loads and the applied reference values. Additional experimental validation was performed using laboratory-scale test rigs instrumented with high-precision strain gauges and load cells. The proposed theoretical method can effectively reconstruct cross-sectional loads at any arbitrary location of thin-walled pipelines, with low mean absolute errors across all load components, demonstrating performance that significantly outperforms conventional monitoring approaches. The method shows particular advantages in identifying combined loading conditions and detecting localized stress concentrations that traditional methods often miss.