Research On Narrow Gap P-GMAW Wireless Monitoring And Defect Diagnosis Based On Multi-information Fusion

The narrow gap P-GMAW welding of medium and thick plates is widely used in all walks of life because of its advantages such as less filler metal,small thermal deformation,and low cost during the welding process.However,it is more sensitive to the welding environment during the welding process,and is easily affected by many factors to produce welding defects.If the quality of the narrow gap P-GMAW welding process can be monitored,then certain interventions can be made when welding defects occur,and then the welding quality can be improved to a certain extent.Therefore,monitoring the welding quality is of great significance.Reasonable use of sensors to obtain information on the welding process is the most critical link for welding quality monitoring.The traditional welding monitoring process uses a single arc sensor to collect the electric arc signal during the welding process,and the acquired welding monitoring information is single,partial and easily affected by the welding environment,and the welding monitoring results are not ideal.In order to improve this situation,this article built a set of multi-information wireless monitoring system for narrow gap P-GMAW welding process.The monitoring system uses arc sensors and image acquisition equipment to simultaneously collect arc electrical signals and image signals in the welding process,and uses the redundancy and complementarity between different types of sensor information to improve the effectiveness and accuracy of welding monitoring information.And extract the characteristic parameters in the multi-sensor information,and use the BP neural network model to realize the diagnosis of the weld sidewall fusion state.First of all,this article clarifies the functions and performance indicators of the multi-information wireless monitoring system by investigating the current research status of multi-information quality monitoring of the welding process and the characteristics of the actual narrow-gap P-GMAW welding process,thereby determining the communication scheme and overall system architecture,and analyzed the operating process of the system.Secondly,the core hardware circuit system of the multi-information wireless monitoring system was developed according to the overall architecture of the system,mainly including the circuit design and core chip selection of the multi-information acquisition module,wireless communication module and related power supply circuit modules,and through drawing The schematic diagram and PCB diagram complete the production of the core control board of the monitoring system.Thirdly,the software development of the core function modules has been completed,including the development of the multi-information high-speed acquisition program during the welding process,the development of the board-level communication program between the wireless module ALK?8266 and the core processing chip,and the communication protocol and grouping between the wireless modules The network configuration program was developed,and the wireless communication process was debugged and precision tested.The host computer monitoring interface is developed through the Lab View platform,which realizes the centralized collection and display of various welding information during the narrow gap P-GMAW welding process.Finally,this article conducts multiple sets of welding experiments with different sidewall fusion conditions,extracts characteristic parameters from the collected welding multi-sensor information,and uses the BP neural network model for information fusion processing to realize the sidewall fusion during the narrow gap P-GMAW welding process Classification and recognition of conditions with high accuracy.