Optimizing inspection plan for corroded pipeline with considering imperfect maintenance

Metal-loss corrosion may result in pipeline's failure and expensive downtime loss. Thus, to keep the pipeline's normal operation, it is crucial to draw up scientific inspection and maintenance plans. This study is to optimize the inspection plan for corroded pipeline. Limit state functions are established for the corrosion leakage and burst respectively, and the pipeline's failure probability is obtained with Monte Carlo simulation. The pipeline's failure probability is further evaluated by the copula function and with considering the correlation of different failure modes. Moreover, a hybrid failure rate model is developed to update the pipeline's failure probability, where the age reduction factor and failure rate increase factor are adopted, and imperfect maintenance is taken into account. On this basis, an optimization model is established with the objective to minimize the total maintenance cost, and genetic algorithm is applied to optimize the inspection plans. A case study is conducted, and the optimal results are analyzed according to acceptable maximum failure probability characteristics for the areas with different risk levels. The results show that periodic inspection and perfect maintenance are suitable for high-risk areas, and the proposed inspection plan is more suitable for corroded pipeline in low or medium-risk areas.