基于PSO-SAE神经网络的城市燃气管道剩余寿命预测

Residual Life Prediction of Urban Gas Pipeline Based on PSO-SAE Neural Network

城市燃气管道由于长时间受到温度、压力、含水量等环境因素的影响,管材极易腐蚀、老化,无法到达设计寿命。针对这一问题,本文提出了一种PSO-SAE算法,利用优化算法自适应调整SAE网络中的超参数,实现对城市燃气管道的剩余寿命这一保障管材安全使用的关键指标做出准确预测,并通过实验验证该方法的有效性和可行性,对燃气企业的安全生产管理具有积极的参考意义。

Due to the influence of environmental factors such as temperature,pressure and water content for a long time,the pipe of urban gas pipeline is very easy to corrode and age,and can not reach the design life.To solve this problem,this paper proposes a PSO-SAE algorithm,which uses the optimization algorithm to adaptively adjust the super parameters in the SAE network,so as to accurately predict the remaining life of urban gas pipeline,which is the key index to ensure the safe use of pipes,and verifies the effectiveness and feasibility of this method through experiments.It has positive reference significance for the safety production management measures of gas enterprises.