Abstract: Aiming at the prediction of the remaining life of pipelines, this study proposes a prediction method based on the KPCA-FA-ELM combined model. The construction method of the remaining life prediction model of the corroded pipeline and the performance verification method of the prediction model are studied. Take oilfield reinjection pipelines and oil and gas gathering pipelines as examples to verify the pipeline remaining life prediction method proposed in this research. The research shows that the minimum relative error of the KPCA-FA-ELM model proposed by this research is 0.38%, the maximum relative error is 6.1%, and the average relative error is 2.35% in the process of predicting the remaining life of oilfield water injection pipelines. The root square error is 0.207, and the Hill inequality coefficient is 0.011. In the process of predicting the remaining life of oil and gas gathering and transportation pipelines, the evaluation indicators are smaller than other models. Therefore, the performance of this model is better than other common prediction models.

Key words: remaining life of pipeline, corroded pipeline, nuclear principal component analysis, firefly algorithm, extreme learning machine