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LD2铝合金加速腐蚀蚀坑演化的ARIMA模型研究
引用本文:刘治国,穆志韬,边若鹏.LD2铝合金加速腐蚀蚀坑演化的ARIMA模型研究[J].机械强度,2012(4):608-614.
作者姓名:刘治国  穆志韬  边若鹏
作者单位:海军航空工程学院青岛分院;海军驻保定地区军事代表室
摘    要:依据加速腐蚀环境谱进行飞机LD2结构试件的加速腐蚀试验,并将LD2材料的加速腐蚀产生及发展过程视为随机过程,提出基于时间序列理论进行腐蚀损伤预测研究的方法,建立描述LD2材料在加速腐蚀环境下蚀坑深度演化规律的时间序列ARIMA(3,1,1)模型,并利用模型进行腐蚀深度预测研究。结果表明,所建的ARIMA(autoregressive integrated moving average,求和自回归移动平均)模型能以较高的精度预测未来一段周期内LD2材料蚀坑深度的发展趋势,说明采用基于时间序列理论的ARIMA模型方法进行飞机LD2结构材料腐蚀损伤预测研究有效可行。

关 键 词:LD2铝合金  加速腐蚀  腐蚀坑  时间序列  ARIMA模型  预测方法

STUDY ON ARIMA MODEL OF LD2 ALUMINUM ALLOY ACCELERATED CORROSION PIT EVOLVEMENT
LIU ZhiGuo,MU ZhiTao,BIAN RuoPeng.STUDY ON ARIMA MODEL OF LD2 ALUMINUM ALLOY ACCELERATED CORROSION PIT EVOLVEMENT[J].Journal of Mechanical Strength,2012(4):608-614.
Authors:LIU ZhiGuo  MU ZhiTao  BIAN RuoPeng
Affiliation:1.Naval Aeronautical Engineering Academy Qingdao Branch,Qingdao 266041,China)(2.The Military Representative Office in Baoding Area,Baoding 072152,China)
Abstract:An accelerated corrosion test of aircraft LD2 structure specimen was carried out according to an accelerated corrosion environment spectrum which established by statistically analysing a typical airport environment factor,and the appearance and development of specimen corrosion was viewed as a stochastic process,so the method which was based on time series theory was put forward to depict and forecast the corrosion damage evolvement of LD2 specimen by establishing ARIMA(3,1,1) model with the corrosion pit depths data itself,further more the erected model was applied to analyse the rule of corrosion pit evolvement.The method application results show that the built ARIMA(autoregressive integrated moving average) model can accurately depict the corrosion pit evolvement trend and predict the corrosion pit depth value of LD2 specimen in a prolongation corrosion period,it suggests that time series theory and ARIMA model can be affectively applied in aircraft structure material corrosion prediction research.
Keywords:LD2 aluminum alloy  Accelerated corrosion  Corrosion pit  Time series  Autoregressive integrated moving average model(ARIMA)  Forecasting method
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