A Vibration-Based Hybrid Deep Learning Approach for Anomaly Detection of Multijoint Industrial Robots

Condition monitoring is essential to ensuring precision and reliability of multi-joint industrial robots. Fault diagnosis is an effective method to identify different types of faults, whereas the tremendous obstacle to applying this method to multi-joint industrial robots is the difficulty of collecting and labeling a substantial quantity of abnormal samples. In this paper, a vibration-based hybrid deep learning approach for anomaly detection of multi-joint industrial robots is proposed to addre