不同初始条件的UGM(1,1)管道腐蚀预测建模研究
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摘要
为研究非等间距灰色模型(UGM(1,1))的初始条件对管道腐蚀预测的影响,首先,探讨现有4种不同初始条件的UGM(1,1)管道腐蚀预测模型的建模步骤;其次,融合新陈代谢和新信息优先原理的建模思想,对现有的初始条件进行优化,建立初始条件滑动的非等间距管道腐蚀预测灰色模型(SUGM(1,1,ρ));最后,以某海洋立管为例,预测其腐蚀速率,对比分析SUGM(1,1,ρ)模型和现有4种不同初始条件的UGM(1,1)模型的预测效果,验证SUGM(1,1,ρ)模型的有效性。结果表明:用现有4种不同初始条件的UGM(1,1)管道腐蚀速率预测模型所得预测结果的平均相对误差分别为3. 16%、3. 35%、3. 49%和3. 36%,用SUGM(1,1,ρ)模型所得预测结果的平均相对误差为1. 77%。
In order to study the influence of the initial condition for unequal interval grey models( UGM( 1,1)) on pipeline corrosion prediction,firstly,the modeling steps of unequal interval pipeline corrosion prediction grey model under different initial conditions were discussed,secondly,aiming at solving the problem of selection of initial conditions in the traditional unequal interval pipeline corrosion prediction grey model,a sliding unequal interval grey pipeline corrosion prediction model( SUGM( 1,1,ρ)) under a sliding initial condition was built up by combing the ideas of metabolism and new information priority principle. Finally,the models were used to predict the pipeline corrosion of a certain marine riser as an example,and a comparison was made between the prediction effects of SUGM( 1,1,ρ) model and the unequal interval pipeline corrosion prediction grey models under different initial conditions. The effectiveness of SUGM( 1,1,ρ) model was verified. The results show that the average relative errors of predicted results obtained by using four unequal interval pipeline corrosion rate prediction grey models under different initial conditions are 3. 16%,3. 35%,3. 49% and 3. 36%,and that obtained by using SUGM( 1,1,ρ) model is 1.77%.
In order to study the influence of the initial condition for unequal interval grey models( UGM( 1,1)) on pipeline corrosion prediction,firstly,the modeling steps of unequal interval pipeline corrosion prediction grey model under different initial conditions were discussed,secondly,aiming at solving the problem of selection of initial conditions in the traditional unequal interval pipeline corrosion prediction grey model,a sliding unequal interval grey pipeline corrosion prediction model( SUGM( 1,1,ρ)) under a sliding initial condition was built up by combing the ideas of metabolism and new information priority principle. Finally,the models were used to predict the pipeline corrosion of a certain marine riser as an example,and a comparison was made between the prediction effects of SUGM( 1,1,ρ) model and the unequal interval pipeline corrosion prediction grey models under different initial conditions. The effectiveness of SUGM( 1,1,ρ) model was verified. The results show that the average relative errors of predicted results obtained by using four unequal interval pipeline corrosion rate prediction grey models under different initial conditions are 3. 16%,3. 35%,3. 49% and 3. 36%,and that obtained by using SUGM( 1,1,ρ) model is 1.77%.
引文
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[17]刘解放,刘思峰,方志耕.基于新型数据变换技术的灰色预测模型及应用[J].数学的实践与认识,2015,45(1):197-202.LIU Jiefang,LIU Sifeng,FANG Zhigeng. The grey prediction model based on new date transformation technology and its application[J].Mathematics in Practice and Theory,2015,45(1):197-202.
[18]丁松,党耀国,徐宁,等.非等间距GM(1,1)模型性质及优化研究[J].系统工程理论与实践,2018,38(6):1 575-1 585.DING Song,DANG Yaoguo,XU Ning,et al. Research on properties and optimization of unequal interval GM(1,1)model[J]. Systems Engineering-Theory&Practice,2018,38(6):1 575-1 585.
[19]潘昶.基于新陈代谢GM(1,1)模型的导弹遥测故障预测算法[J].飞行器测控学报,2014,33(1):35-39.PAN Chang. Missle telemetry fault forecast algorithm based on metabolic GM(1,1)model[J]. Journal of Spacecraft TT&C Technology,2014,33(1):35-39.
[20]张朝飞,罗建军,徐兵华,等.基于灰色理论的新陈代谢自适应多参数预测方法[J].上海交通大学学报,2017,51(8):970-976.ZHANG Chaofei,LUO Jianjun,XU Binghua,et al.Metabolism adaptive multi-parameter prediction method based on the grey theory[J]. Journal of Shanghai Jiaotong University,2017,51(8):970-976.
[21]赵建忠,李海军,叶文,等.基于信息融合和改进UGM(1,1)模型的故障预测[J].系统工程与电子技术,2013,35(10):2 135-2 140.ZHAO Jianzhong,LI Haijun,YE Wen,et al. Fault prediction based on information fusion and improved UGM(1,1)model[J].Systems Engineering and Electronics,2013,35(10):2 135-2 140.
[2] NOOR N M,YAHAYA N,DIN M M,et al. Prediction of corroding pipeline remaining life-time using semi-probalistic approach[J]. Malaysian Journal of Civil Engineering,2010,21(1):204-218.
[3]毕傲睿,骆正山,王小完,等.基于土壤腐蚀主成分的金属管道退化维纳过程研究[J].材料保护,2018,51(1):37-42.BI Aorui,LUO Zhengshan,WANG Xiaowan,et al. Wiener process of degradation of metal pipelines based on principal components of soil corrosion[J]. Materialy Protection,2018,51(1):37-42.
[4]张新生,曹乃宁,王小完,等. Gumbel分布的油气管道的剩余寿命预测[J].中国安全科学学报,2015,25(9):96-101.ZHANG Xinsheng,CAO Naining,WANG Xiaowan,et al. Residual life prediction of oil and gas pipeline based on Gumbel distribution[J]. China Safety Science Journal,2015,25(9):96-101.
[5]骆正山,袁宏伟.基于误差补偿的GM-RBF海底管道腐蚀预测模型[J].中国安全科学学报,2018,28(3):96-101.LUO Zhengshan,YUAN Hongwei. GM-RBF model based error compensation for prediction of submarine pipelines corrosion[J]. China Safety Science Journal,2018,28(3):96-101.
[6]姜峰,郑运虎.预测腐蚀管道剩余寿命的新方法研究[J].机械强度,2015,37(3):539-545.JIANG Feng,ZHENG Yunhu. Study of new method for the remaining life of prediction of corrosion pipeline[J]. Journal of Mechanical Strength,2015,37(3):539-545.
[7]经建芳,邓富康,李康春,等.海水腐蚀速率的不等时距灰色模型与BP神经网络模型组合预测[J].材料保护,2015,48(8):33-36.JING Jianfang,DENG Fukang,LI Kangchun,et al. Seawater corrosion rate prediction based on unequal time gray model and BP neural network model[J]. Materialy Protection,2015,48(8):33-36.
[8]戴文战,李俊峰.非等间距GM(1,1)模型建模研究[J].系统工程理论与实践,2005,25(9):89-93.DAI Wenzhan,LI Junfeng. Modeling research on non-equidistance GM(1,1)model[J]. Systems Engineering-Theory&Practice,2005,25(9):89-93.
[9]李志伟,李克昭.基于Markov理论的加权非等距GM(1,1)预测优化模型[J].测绘工程,2016,25(12):38-43.LI Zhiwei,LI Kezhao. An optimized weighted non-equidistance GM(1,1)prediction model based on Markov theory[J].Engineering of Surveying and Mapping,2016,25(12):38-43.
[10]王叶梅,党耀国,王正新.非等间距GM(1,1)模型背景值的优化[J].中国管理科学,2008,16(4):159-162.WANG Yemei,DANG Yaoguo,WANG Zhengxin. The optimization of background value in non-equidistant GM(1,1)model[J]. Chinese Journal of Management Science,2008,16(4):159-162.
[11]杨乐,王惠萌.基于灰色系统理论模型预测海底管道腐蚀剩余寿命[J].焊管,2013,36(8):21-24.YANG Le,WANG Huimeng. Residual life prediction to submarine pipeline corrosion based on the gray system theory model[J]. Welded Pipe and Tube,2013,36(8):21-24.
[12]韩晋.杨岳,陈峰,等.基于非等时距加权灰色模型与神经网络的组合预测算法[J].应用数学和力学,2013,34(4):408-419.HAN Jin,YANG Yue,CHEN Feng,et al. Combination forecasting algorithm based on non-equal interval weighted gray model and natural network[J]. Applied Mathematics and Mechanics,2013,34(4):408-419.
[13]姜峰,郑运虎,梁瑞.改进的非等间距GM(1,1)模型预测腐蚀立管剩余寿命[J].中国安全科学学报,2014,24(6):57-61.JIANG Feng,ZHENG Yunhu,LIANG Rui. Method for corrosion risers remaining life prediction based on improved nonequidistant GM(1,1)model[J]. China Safety Science Journal,2014,24(6):57-61.
[14]罗佑新.非等间距新息GM(1,1)的逐步优化模型及其应用[J].系统工程理论与实践,2010,30(12):2 254-2 258.LUO Youxin. Non-equidistant step by step optimum new information GM(1,1)and its application[J]. Systems Engineering-Theory&Practice,2010,30(12):2 254-2 258.
[15]熊萍萍,党耀国,姚天祥,等.基于初始条件优化的一种非等间距GM(1,1)建模方法[J].控制与决策,2015,30(11):2 097-2 102.XIONG Pingping,DANG Yaoguo,YAO Tianxiang. Modeling method of non-equidistant GM(1,1)model based on optimization initial condition[J]. Control&Decision,2015,30(11):2 097-2 102.
[16]赵建忠,叶文,张磊.基于数据融合和改进新陈代谢不等间距GM(1,1)模型的导弹装备故障预测[J].兵工学报,2014,35(10):1 689-1 695.ZHAO Jianzhong,YE Wen,ZHANG Lei. Failure prediction of missile equipment based on data fusion and AMUGM(1,1)model[J]. Acta Armamentaril,2014,35(10):1 689-1 695.
[17]刘解放,刘思峰,方志耕.基于新型数据变换技术的灰色预测模型及应用[J].数学的实践与认识,2015,45(1):197-202.LIU Jiefang,LIU Sifeng,FANG Zhigeng. The grey prediction model based on new date transformation technology and its application[J].Mathematics in Practice and Theory,2015,45(1):197-202.
[18]丁松,党耀国,徐宁,等.非等间距GM(1,1)模型性质及优化研究[J].系统工程理论与实践,2018,38(6):1 575-1 585.DING Song,DANG Yaoguo,XU Ning,et al. Research on properties and optimization of unequal interval GM(1,1)model[J]. Systems Engineering-Theory&Practice,2018,38(6):1 575-1 585.
[19]潘昶.基于新陈代谢GM(1,1)模型的导弹遥测故障预测算法[J].飞行器测控学报,2014,33(1):35-39.PAN Chang. Missle telemetry fault forecast algorithm based on metabolic GM(1,1)model[J]. Journal of Spacecraft TT&C Technology,2014,33(1):35-39.
[20]张朝飞,罗建军,徐兵华,等.基于灰色理论的新陈代谢自适应多参数预测方法[J].上海交通大学学报,2017,51(8):970-976.ZHANG Chaofei,LUO Jianjun,XU Binghua,et al.Metabolism adaptive multi-parameter prediction method based on the grey theory[J]. Journal of Shanghai Jiaotong University,2017,51(8):970-976.
[21]赵建忠,李海军,叶文,等.基于信息融合和改进UGM(1,1)模型的故障预测[J].系统工程与电子技术,2013,35(10):2 135-2 140.ZHAO Jianzhong,LI Haijun,YE Wen,et al. Fault prediction based on information fusion and improved UGM(1,1)model[J].Systems Engineering and Electronics,2013,35(10):2 135-2 140.