Abstract：In order to improve the reliability of the excavator＇ s hydraulic system, a fault diagnosis approach based on principal component regression （PCR） model was proposed. This approach has two steps ： fault feature extraction and fault classification. First, several input-output PCR models were established by the minimum number of principal components in terms of the total variance, and PCR parameters were regarded as the fault features. Second, FCM clustering was performed as the fault feature classifier to identify the fault patterns. Simulation results show that the proposed fault diagnosis approach can be effectively applied to excavator＇ s hydraulic system.
贺湘宇, 何清华, 郭勇, 朱建新. 基于主元回归模型的挖掘机液压系统故障诊断[J]. 江苏大学学报（自然科学版）, 2008, 29(2): 106-110.
He Xiangyu, He Qinghua, Guo Yong, Zhu Jianxin. Fault diagnosis for excavator＇s hydraulic system based on principal component regression model[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2008, 29(2): 106-110.
2008, Vol. 29 
