并以建立轴承疲劳试验故障诊断专家系统知识库为例，说明了其具体应用。
An example in order to explain how to build up a knowledge base of the bearing failure diagnosis ES is given.
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。
The bearing life forecast model based on BP network is researched. The multi step and multi feature forecasts can be realized concurrently.
基于机械加工误差的特点，利用灰色系统理论建立轴承磨削加工过程尺寸误差动态分析的数学模型。
The mathematical model is established for the dynamic distributions of dimension errors in bearing grinding process by means of the Grey theory.
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