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| Fault diagnosis for excavator＇s hydraulic system based on principal component regression model |
College of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan 410083, China）
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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.
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2008, Vol. 29 
