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Process Control Method And System Of Rail Single Pass Multi-layer Ultra Narrow Gap Welding

Posted on:2022-10-01Degree:MasterType:Thesis
Country:ChinaCandidate:D D ChangFull Text:PDF
GTID:2492306515466584Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of high-speed trains in my country,higher requirements are put forward on the running track of trains.The safe,reliable,high-quality and smooth seamless railway has greatly increased the running speed of trains.As the weakness of seamless railways,the welding quality of joints directly affects the safety of train operation.However,in-service railways often have various damages,and in severe cases,on-site welding repairs are required.At present,most mainstream rail welding methods at home and abroad cannot meet the requirements of efficient and convenient on-site repair.The flux band constrained arc ultra-narrow gap welding method proposed by the research group is an efficient welding method with convenient equipment and low heat input.It is proved that this method can effectively guarantee the welding quality and has great application prospects.The environment of the rail welding site is very harsh,which puts forward higher requirements for the portability of the welding device and the robustness of the system.This article uses Mitsubishi’s third-generation programmable logic controller FX3U-64MR/ES-A as the control core,with expansion module FX3U-4DA,Panasonic A5 series servo drive system,self-designed new welding gun system,general company’s analog welding machine NB-500 T,etc.build a mechanical xx platform,based on multi-sensor and communication between Lab VIEW and PLC to develop upper-level software with welding process signal acquisition,welding system control and welding parameter setting control,etc.,which can quickly and efficiently complete the pre-welding parameter one Set the key to build a single-track multi-layer ultra-narrow gap welding system for rails that integrates the functions of display,detection,speed regulation,welding start and stop,welding layer height adjustment,arc ignition and stable welding power supply circuit switching.It has improved its digitization and automation,and further studied the setting method of welding specification parameters through a large number of experiments.Combining the experience and characteristics of parameter setting of ultra-narrow gap welding process,a multiple linear regression model based on heat input was established,and the model was tested from the angles of goodness of fit,overall significance,and variable significance.According to the analysis of the mechanism of the ultra-narrow gap welding process,a forward prediction model based on SVR was established to accurately predict the weld bead height,and the reverse model to predict the key welding parameters of wire feeding speed and welding speed.Adopting the strategy of closed-loop optimization of the positive and negative models,the welding parameters obtained by the reverse model are used as the input of the forward model,sensitivity analysis is made,and the parameters are constantly modified to make the forward output reach the desired layer height value.Finally,all the predicted welding parameters and groove width conditions are used as the input of the SVR model to predict the welding heat input under this condition,and the simultaneous heat input multiple linear regression model solves the welding voltage value,and realizes the ultra-narrow gap welding parameter setting work.Finally,the ultra-narrow gap welding test of BU71 Mn rail was carried out using the above-mentioned welding system and parameter setting method.The study proved that the system and parameter setting method are reliable and effective,and a rail joint with good welding quality can be obtained.In addition,the problems existing in the rail welding process are summarized and analyzed,which lays a foundation for subsequent experiments and industrial field applications.
Keywords/Search Tags:Ultra-narrow gap welding, Parameter setting, Rail welding, Multiple linear regression, Support vector machine
PDF Full Text Request
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