On-line Identification of Narrow Gap P-GMAW Sidewall Fusion States Based on Arc Acoustic Signals
To grasp the internal welding status of welds in real time during welding processes,an on-line acquisition system of arc sound signals was constructed.The correlation analysis between arc sound signal characteristics and sidewall fusion states was carried out under the conditions that the torch swing center were in different positions.Arc acoustic features with strong correlation to side wall fusion state were extracted from time domain and frequency domain respectively.In order to fur-ther improve the effectiveness of the fusion state prediction,a support vector regression model for sidewall fusion state recognition was constructed by arc acoustic feature parameters.To reduce the im-pacts of non-features and improve the prediction accuracy of the model,genetic algorithm was used to optimize the model parameter.After parameter optimization,the recognition rate of the model is as 93.33％,which realizes the effective recognition of the fusion states of the narrow gap sidewalls.
narrow gap weldingarc soundsidewall fusionsupport vector machine(SVM)pulse gas metal arc welding
万方数据
维普
