基于数据挖掘的高速船舶柴油机使用寿命预测

Life prediction of high-speed marine diesel engine based on data mining

柴油机内部活塞性能与使用时长直接影响高速船舶的航行情况,提出基于数据挖掘的高速船舶柴油机使用寿命预测方法。利用k-means聚类算法数据挖掘技术收集高速船舶柴油机及其活塞的运行状态,利用该数据构建柴油机活塞的有限元模型,计算机械荷载、热力耦合等工况下活塞偶的应力变化,并确定边界条件;将有限元计算结果导入Femfat软件,利用Miner准则预测柴油机活塞寿命,结合Aeran理论优化预测计算结果,确定不同工况循环次数与采油机活塞损伤的关系。试验结果表明,机械荷载与热力耦合工况下,柴油机活塞的应力主要集中在销孔过渡圆弧以及裙中腔等位置,热力耦合工况下柴油机活塞损伤最严重,寿命也最短。

The performance and service life of diesel engine piston directly affect the sailing conditions of high-speed ships, so this paper studies the service life prediction of high-speed Marine diesel engine based on data mining. The data mining technology of k-means clustering algorithm was used to collect the running state of high-speed Marine diesel engine and its piston. The finite element model of diesel engine piston was constructed by using the data, and the stress changes of piston couple under mechanical load and thermodynamic coupling conditions were calculated, and the boundary conditions were determined. The finite element calculation results were imported into Femfat software, and the life of diesel engine piston was predicted by Miner criterion. The prediction results were optimized by Aeran theory, and the relationship between the number of cycles under different working conditions and piston damage was determined. The test results show that the stress of diesel engine piston is mainly concentrated in the position of excessive arc of pin hole and skirt cavity under mechanical load and thermodynamic coupling condition, and the damage of diesel engine piston is the most serious and its life is the shortest under thermodynamic coupling condition.