摘要
试图用ＢＰ神经网络建立轴承寿命预测模型，并在该模型上进行多特征参数和多步预测方法的研究。实践表明：该模型能够较好地逼近轴承的运行状态的变化曲线，有效地消除了随机干扰，提高和改善了预测的精度和效果。
The bearing life forecast model based on BP network is researched. The multi step and multi feature forecasts can be realized concurrently. This model can approximate the changing curve of the bearing running condition. The forecast accruacy is high and the application results of bearing fatigue life forecasts are satisfactory.
出处
《机械科学与技术》
CSCD
北大核心
1999年第4期584-586,共3页
Mechanical Science and Technology for Aerospace Engineering
基金
冶金部基础理论研究资助
