A NEW FAULT DIAGNOSIS METHOD BASED ON IMMUNE MODEL

摘要：

An immune-based model is proposed to accomplish a non-linear mapping from feature space to a two dimensional classification space in fault diagnosis. The mapping is conducted to create the best cluster effect for training samples belonging to the same class. Especially Artificial immune regulation (AIR) scheme used to generate automatically the antibodies (memory B-cells) in the model is explained in detail.Finally the numerical experiments in fault diagnosis of a tapered roller bearing are performed. The results show that the method is simple and effective through comparing with NN.

关键词： Immune model artificial immune regulation fault diagnosis tapered roller bearing

作者: GUI-HONG ZHOU CHUN-CHENG ZUO JIA-ZHONG WANG SHU-XIA LIU

作者单位: College of Information Science and Technology, Agricultural University of Hebei, 071000 PR China;Col College of Mechanical Science and Engineering, Jilin University, Changchun 130025 PR China College of Information Science and Technology, Agricultural University of Hebei, 071000 PR China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 2954-2958

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）