Study On CMT Thin Plate Lap Welding Quality Monitoring Based On Welding Electronic Parameters And Welding Sound

Welding electrical parameters,including welding current and welding voltage,reflect the dynamic characteristics of welding power source.Welding sound also provides abundant dynamic information from another point of view.The combination of the two methods can reflect the dynamic welding process and welding quality information more comprehensively to a certain extent.In order to carry out this research,CMT(Cold Metal Transfer)lap welding experiments of low carbon steel sheet were carried out.CMT welding method has the advantages of no spatter and low heat input.It is widely used in thin plate welding,dissimilar metal welding and other fields.Firstly,the sound source characteristics of CMT are studied.Different operation modes of CMT have different sound characteristics.Further analysis of the "special two-step mode" of welding sound shows that the acoustic signal of welding arc originates from the energy change of welding arc,and the faster the change of arc energy,the greater the corresponding sound pressure value.On this basis,the signal acquisition methods of abnormal CMT welding status were studied.Two groups of experiments were carried out.In the first group,the gas flow was adjusted until the gas supply stopped under the condition of other technological parameters unchanged;in the second group when the lap gap was adjusted to 2 mm,the defect of welding wear achieved.Furthermore,the feature extraction and fusion methods of welding electrical parameters and welding sound signals were investigated.In the aspect of electric signal,welding current,welding voltage,line energy and so on;In the aspect of sound signal,MFCC is extracted after de-framing and windowing.BiLSTM-CTC algorithm can be used to identify welding process information such as welding wear,gas feeding fault and so on.For the recognition model of gas supply status and welding wear defects,the classification error rate based on sound feature is the lowest at 0.389,the classification error rate based on electrical signal feature is the lowest at 0.774,and the classification error rate based on fusion feature is at 0.295.These experiments prove that under the same model framework,the model which combines the characteristics of welding electrical signal and acoustic signal has the lowest classification error rate.In order to achieve the goal of real-time monitoring,this paper develops a real-time monitoring system based on B/S mode.This system applies the analysis model mentioned above,and can judge the stability of CMT lap welding and identify abnormal conditions based on real-time welding electrical and acoustic signals.