摘要
摩擦学系统具有复杂性,但传统研究方法无法精确定量求解摩擦学复杂问题。为了了解摩擦学复杂问题的解决方法,更好地开展对摩擦学复杂问题的深入研究,阐述人工神经网络方法解决磨损过程的预测、摩擦因数预测与分析和磨屑识别等摩擦学复杂问题的研究进展,并对其未来发展趋势进行展望,如建立新型神经网络模型,建立集成度高、耦合多种分析方法的平台以及创新研究对象等。
The characteristic of the tribology system is complex so that the conventional methods cannot solve the tribo- logical complex problems accurately.In order to fully realize the methods of tribologieal research and make a quantitative study of complex tribological problems, the latest development of applications of artificial neural network theory in wear prediction,friction coefficient prediction and wear particles identification were summarized respectively. The development trends were prospected, including the establishment of a new neural network model and a high integration research model coupled with a variety of analytical methods, as well as the innovation of research objects.
出处
《润滑与密封》
CAS
CSCD
北大核心
2016年第11期117-123,116,共8页
Lubrication Engineering
基金
国家自然科学基金项目(51522504)
深圳市行业公共技术服务平台资金项目(SMJKPT20140417010001)
中国博士后科学基金项目(2015M580735)
关键词
摩擦学
复杂问题
人工神经网络
预测
识别
tribology
complex problem
artificial neural networks
prediction
identification 1
