船舶机械设备运行的可靠性对于船舶整体而言非常重要，随着船舶机械设备复杂程度的提高，机械故障的预测和防范成为研究热点。本文系统介绍SMM马尔科夫模型和HSMM隐马尔科夫模型的原理和应用场景，针对船舶机械故障的演化预测模型进行详细研究。利用HSMM隐马尔科夫模型在随机信号特征提取以及时间概率的准确性优势，对船舶动力系统变速箱的齿轮故障进行预测和诊断，取得了较好的效果。
The reliability of marine mechanical equipment operation is very important for the ship as a whole. with the improvement of the complexity of marine mechanical equipment, the prediction and prevention of mechanical failures has become a hot research. This paper systematically introduces the principles and application scenarios of SMM Markov model and HSMM hidden Markov model, conducts a detailed study on the evolutionary prediction model of marine machinery failure, and makes use of the accuracy advantages of HSMM hidden Markov model in random signal feature extraction and time probability to predict and diagnose the gear failure of marine machinery system power system gearbox, which has achieved good results.
2022,44(22): 174-177 收稿日期：2022-07-21
DOI：10.3404/j.issn.1672-7649.2022.22.035
分类号：U645.15
作者简介：贾成芬(1981-),女,硕士,讲师,研究方向为机电控制及机器人控制
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