Research on Fault Identification and Diagnosis of Gantry Cranes Based on CMAC Neural Network
As an indispensable lifting equipment in logistics hubs such as port terminals and railway distribution centers,gantry cranes rely heavily on their motors and reducers.Failures in these core components can significantly impact operational efficiency and project progress.To ensure the stable operation of gantry cranes,this paper proposes a fault diagnosis system based on the CMAC neural network.The system first extracts key fault features through data preprocessing techniques and then utilizes the CMAC neural network for fault pattern recognition and prediction.Experimental results demonstrate that,compared to traditional fault diagnosis methods,the proposed system offers high accuracy and strong real-time performance,providing a new and effective means for gantry crane fault diagnosis.
NETL
NSTL
万方数据
