MOE Key Lab of Liquid Structure and Heredity of Materials, Institute of Materials Joining, Shangdong University, 73 Jingshi Road, Jinan 250061, People's Republic of China This paper introduces an intelligent system for monitoring and recognition of process disturbances during short-circuiting gas-metal arc welding. It is based on the measured and statistically processed data of welding electrical parameters. A 12-dimensional array of process features is designed to describe various welding conditions and is employed as input vector of the intelligent system. Three methods, such as fuzzy c-means, neural network and fuzzy Kohonen clustering network are used to conduct process monitoring and automatic recognition. The correct recognition rates of these three methods are compared.