盐湖大气环境下316 L仪表管点蚀深度预测研究
Prediction on pitting depth of 316 L instrument tube in salt-lake atmospheric environment
骆正山 1刘月1
作者信息
- 1. 西安建筑科技大学管理学院,陕西西安 710055
- 折叠
摘要
为提高316 L仪表管在盐湖大气环境下点蚀深度的预测精度,采用变阶平均弱化缓冲算子、积分背景值和新陈代谢对分数阶累加灰色模型FGM(1,1,r)进行改进,首先通过改进Tent混沌映射、莱维飞行和区间自适应反向学习策略提高黏菌算法(SMA)的寻优能力和收敛速度,随后利用改进黏菌算法(ISMA)对FGM(1,1,r,p)中的参数r和p进行寻优,最后构建仪表管ISMA-FGM(1,1,r,p)点蚀深度预测模型.研究结果表明:经优化的新模型比原模型误差更小、拟合度更高,在仪表管点蚀深度预测方面具有更好的性能.研究结果可为仪表管道系统的完整性评价和风险预警提供参考.
Abstract
In order to improve the prediction accuracy of pitting depth by the 316 L instrument tube in the salt-lake atmos-pheric environment,the fractional order cumulative grey model(FGM(1,1,r))was improved by using the variable order av-erage weakening buffer operator,integrated background value and metabolism.Firstly,the optimization ability and convergence speed of slime mould algorithm(SMA)were improved by improving the Tent chaos mapping,Levy flight and interval adaptive reverse learning strategies.Then,the parameters r and p in FGM(1,1,r,p)were optimized by ISMA.Finally,the ISMA-FGM(1,1,r,p)prediction model of the pitting depth of instrument tube was constructed.The results show that the optimized new model has smaller error and higher fitting degree than the original model,and has better performance in predicting the pitting depth of instrument tube.The research results can provide a reference for the integrity evaluation and risk warning of instrument tube system.
关键词
盐湖大气环境/316/L仪表管/点蚀深度/改进黏菌算法(ISMA)/FGM(1,1,r)模型Key words
salt-lake atmospheric environment/316 L instrument tube/pitting depth/improved slime mold algorithm(IS-MA)/FGM(1,1,r)model引用本文复制引用
出版年
2024
NETL
NSTL
万方数据