主成分分析和灰色模型组合的身管多点烧蚀磨损量预测
Prediction of Gun Barrel Multi-point Erosion and Wear Based on Principal Component Analysis and Gray Model Combination
康总宽 1闫彬 2周子璇 3宋洪震 2陈学军2
作者信息
- 1. 西北机电工程研究所,陕西 咸阳 712099;华中科技大学机械科学与工程学院,武汉 430074
- 2. 西北机电工程研究所,陕西 咸阳 712099
- 3. 华中科技大学机械科学与工程学院,武汉 430074
- 折叠
摘要
身管是火炮类武器的关键零件,对其烧蚀磨损量进行预测,有助于保持火炮作战效能.针对火炮身管沿轴向各点烧蚀磨损量需分别建立数学模型进行预测问题,提出一种组合烧蚀磨损量预测方法.采用主成分分析(principal component analysis,PCA)方法对身管多点烧蚀磨损量进行数据空间降维,提取反映烧蚀磨损量变化的主成分,利用灰色模型对主成分进行多步预测,通过PCA逆运算获得身管内膛多点烧蚀磨损量预测值.结果表明,在历史数据较少的条件下,通过选择合适的预测步数可获得较为准确的预测值,为身管内膛多点烧蚀磨损量的预测提供了一种新的有效途径.
Abstract
Barrel is a key part of artillery weapons.To predict its erosion and wear is helpful to maintain the operational effectiveness of artillery.Aiming at the problem that it is necessary to establish a mathematical model to predict the erosion and wear of gun barrel at each point along the axis,acom-bined erosion and wear prediction method was propsoed.Principal component analysis(PCA)was used to reduce the dimensionality of the data of the multi-point erosion and wear of artillery barrel,and principal components reflecting erosion and wearchanges were extracted.The gray model was used to predict the multi-step of the principal components,and the predicted value of multi-point erosion and wear of the barrel was obtained by PCA inverse calculation.The results show that,under the condition of less historical data,more accurate prediction value can be obtained by selecting the appropriate numbers of prediction step,which provides a new effective way for the prediction of multi-point ero-sion and wear of the bore.
关键词
身管/烧蚀磨损/主成分分析/灰色模型Key words
gun barrel/erosion and wear/principal component analysis/gray model引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据