A Novel Approach to Optimal Strain Gauge Placement for Structural Assessment: Integrating Close Looping Configuration with Calibration Techniques

Addressing the challenge of optimal strain gauge placement on complex structural joints and pipes, this research introduces a novel methodology combining strategic gauge configurations with numerical optimization techniques. Traditional methods often struggle to accurately capture combined loading states and real-world complexities, leading to measurement errors and flawed structural assessments. For intricate joints, a looping strain gauge configuration is proposed to comprehensively capture both bending and torsional effects, preventing the bypassing of applied loads. A calibration technique is used to create strain distribution matrices and access structural behavior under different loading conditions. Optimization algorithms are then applied to identify gauge placements that yield well-conditioned matrices, minimizing measurement errors and enhancing data reliability. This approach offers a cost-effective solution by reducing the number of gauges required for accurate stress characterization. Extending this concept to both round and complex-shaped pipes, this research emphasizes enhancing damage calculation accuracy using Road Load Data Acquisition (RLDA). FEA models, validated against analytical solutions for round pipes and accounting for geometric intricacies in complex shapes, simulate stress fields under diverse loading scenarios. The optimization objective prioritizes maximizing strain sensitivity in critical areas, minimizing errors, and ensuring robust strain field representation, considering RLDA limitations. The unique contribution lies in directly linking optimized strain gauge placement with improved damage calculation. By integrating RLDA, optimized configurations are tested under actual operating conditions, validating numerical models and assessing damage accumulation based on measured strain data. This leads to more realistic damage predictions compared to simplified loading assumptions. The findings demonstrate that optimized placement significantly enhances damage calculation accuracy, crucial for industries like oil and gas, aerospace, and infrastructure monitoring, where RLDA provides valuable insights into real-world loading.