Abstract:

In order to improve the reliability and intelligence of the excavator, a fault diagnosis approach of its hydraulic system based on an auto-regressive with extra inputs (ARX) model and the fuzzy C-means (FCM) clustering was proposed. This approach does fault diagnosis by two steps: fault feature extraction and fault classification. In the first step, the ARX models are established for known faults and unknown faults. The auto-regressive parameters extracted from the model are regarded as the fault feature. In the second step, the FCM clustering is used as the fault feature classifier to identify unknown faults. Both the simulation and experiment results showed that the proposed fault diagnosis approach can be effectively applied to the excavator hydraulic system.

Key words: automatic control technology, fault diagnosis, auto-regressive with extra inputs(ARX) model, fuzzy C-means(FCM) clustering, hydraulic system, excavator