基于灰色马尔科夫模型的随机多次冲击损伤累积研究

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (24) : 295-300.

论文

基于灰色马尔科夫模型的随机多次冲击损伤累积研究

陈卓，闫明，金映丽

作者信息 +

A study on damage accumulation of random multiple impact based on a grey Markov model

CHEN Zhuo, YAN Ming, JIN Yingli

Author information +

文章历史 +

摘要

针对海战时舰船设备遭受敌方武器冲击及自身火炮后坐力造成的损伤累积问题，提出了结合灰色马尔科夫模型和Dirlik公式的随机多次冲击损伤累积预测方法。以GM(1,1)模型为基础，通过引入马尔科夫状态转移矩阵，给出新的灰色马尔科夫方法处理和预测随机冲击载荷数据。基于Dirlik公式，提出一种在随机冲击下零件的损伤累积和寿命预测方法。以铝合金6061轴试样为研究对象，将本方法与Miner法的预测值对比。结果表明，随机冲击下的预期损伤率与峰度成正相关，较大的峰度对冲击疲劳损伤有显著的影响。本方法得到的寿命预测值与真实值的误差更小，显著优于传统的Miner法。本方法可靠并偏于保守，可以为舰船设备零件的随机多次冲击损伤累积研究提供数据支持和理论参考。

Abstract

Aiming at the problem of damage accumulation caused by the impact of enemy weapons and the recoil of its own artillery during naval battle, a random multiple impact damage accumulation prediction method combining grey Markov model and Dirlik formula is proposed. Based on GM(1,1) model, a new grey Markov method is given to process and predict random impact load data by introducing Markov state transition matrix. Based on Dirlik formula, a method of damage accumulation and life prediction of parts under random impact is proposed. Taking aluminum alloy 6061 axial samples as the research object, the predicted values of this method are compared with those of Miner method. The results show that the expected damage rate under random impact is positively correlated with kurtosis, and the larger kurtosis has a significant impact on impact fatigue damage. The error between the predicted life value and the real life value obtained by this method is smaller, which is significantly better than the traditional Miner method. This method is reliable and conservative, which can provide data support and theoretical reference for the study of random multiple impact damage accumulation of ship equipment parts.

导出引用

陈卓, 闫明, 金映丽. 基于灰色马尔科夫模型的随机多次冲击损伤累积研究[J]. 振动与冲击, 2024, 43(24): 295-300

CHEN Zhuo, YAN Ming, JIN Yingli. A study on damage accumulation of random multiple impact based on a grey Markov model[J]. Journal of Vibration and Shock, 2024, 43(24): 295-300

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