Accuracy Improvement of Mutual Integration Mechanism Driven Algorithms for Boom Cable Force Recognition

Abstract

Accurate measurement of cable tension is crucial for real-time monitoring of bridge systems, preventing potential risks, and ensuring bridge safety and continuous operation. However, traditional cable tension measurement often faces the challenge of ensuring accuracy when dealing with complex elastic boundary conditions. This article uses 9 finite element model suspension cables with complex elastic boundary conditions as data for cable force identification, and uses heuristic algorithms to achieve cable force identification with the goal of minimizing the frequency and actual frequency. Based on the recognition results and process, the reasons for inaccurate identification of cable forces under complex elastic boundaries were analyzed, and a mutual fusion mechanism was proposed to improve the accuracy of cable force identification. The results show that the proposed mutual fusion mechanism reduces the maximum relative error of cable tension in accuracy by 12.6%, significantly improving accuracy, and reduces the relative error of most initial cable tension identification to 5%, meeting the needs of practical engineering. In addition, the non parametric test statistical method also proves that the introduction of mutual fusion mechanism has a significant impact on the relative error value of cable tension. Finally, the fusion mechanism was verified through data from three engineering cables to meet engineering requirements. This method provides a new technical solution for intelligent and accurate identification of cable forces in long bridge beams, and has broad application prospects.