Identification and Repair of Structural Damage of Building Foundations Based on Genetic Algorithm

The identification and repair of structural damage in building foundations are critical tasks in ensuring the safety and integrity of civil infrastructure. This research paper proposes a method based on genetic algorithms for the identification and repair of structural damage in building foundations. The proposed approach begins with the identification of structural damage by analysing sensor data, including vibration measurements and strain gauges, obtained from the building's foundation. A genetic algorithm is then employed to optimize the identification process by iteratively searching for the most likely damage scenarios based on the collected sensor data. Once the damage is identified, the algorithm proceeds to develop an optimal repair strategy. It considers various parameters, such as available repair materials, budget constraints, and desired structural performance, to generate a repair plan that minimizes cost and maximizes the restoration of structural integrity. The repair plan is optimized using the genetic algorithm to find the best combination of repair techniques and materials. To evaluate the effectiveness of the proposed method, extensive simulations and case studies are conducted on different types of building foundations. The performance of the algorithm is assessed in terms of its accuracy in identifying structural damage and the efficiency of the repair strategy.