Recognition model of arc welding penetration using ICA-BP neural network

A BP neural network model based on ICA (Imperialist Competitive Algorithm) is proposed to recognize the arc welding penetration status. The weights and thresholds of the neural network are initialized using ICA which has the features of uneasy accessibility to local extremum and fast search speed. Then the BP algorithm is used to train the neural network. By capturing the images of the molten pool in welding process, three features of a molten pool image are processed. The features includes the weld pool area, weld pool width and the distance between the weld pool centroid and the bottom. These features are as the inputs of neural network to create the mapping relationship between the three features of molten pool and the weld penetration status, and eventually a predicted model of penetration status is established. Welding experimental results show that the welding penetration status can be accurately recognized using the ICA-BP neural network.