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Modeling And Its Application Of Resource Environmental Attributes Of Welding Technology For Concrete Pump Trucks

Posted on:2020-09-09Degree:MasterType:Thesis
Country:ChinaCandidate:Y D ShiFull Text:PDF
GTID:2381330620454816Subject:Mechanical engineering
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In recent years,the pilot demonstration of 'green factories' and 'smart factories' has vigorously promoted by China.It is extremely urgent for concrete machinery enterprises to transform and upgrade in the direction of sustainable,digitization and intelligent.Concrete pump truck plays an important role in concrete machinery products,and the welding technology is one of the typical manufacturing processes.However,the existing literature at home and abroad in the analysis of resource environmental attributes for welding technology,modeling and other aspects of the research were not comprehensive and in-depth.Besides,more and more attention has been paid to the database system of resource environmental attributes for welding technology of concrete machinery enterprises.Therefore,this paper focuses on the analysis and modeling of resource environmental attributes for welding technology of concrete pump truck and its application.Firstly,resource environmental attributes of the welding technology of concrete pump truck were analyzed,and its IPO(Input-Process-Output)model and quantitative model were established.The comprehensive analysis system of resource environmental attributes was established by three aspects of material flow,energy flow and environmental emission flow.Among them,the characteristics of multi-source energy consumption and multi-source carbon emission of the welding technology of concrete pump truck were analyzed,and quantitative models of multi-source energy consumption and multi-source carbon emission of the welding technology were established.Then,the basic data acquisition platform for resource environmental attributes of welding process of concrete pump truck was set up,experiments of welding technology were carried out,and the key technologies of basic data acquisition of resource environmental attributes such as material consumption,energy consumption,dust and noise in the welding process were studied.In view of the welding process experiment of two typical structural parts of concrete pump truck,combined with the analysis system of resource environmental attributes of concrete pump truck and its quantitative model established in this paper,the overall situation of resource environmental attributes,multi-source energy consumption and multi-source carbon emission of the welding process of two typical structural parts of concrete pump truck were analyzed.Among them,the energy consumption model of the welder was verified by relative experiment.The theoretical value of the welder energy consumption is in good agreement with its test value,and the relative error is within 8%.Furthermore,the neural network prediction model of resource environmental attributes for welding technology of concrete pump truck was established,and the performance test results of this prediction model show that the alignment between neural network training samples,validation sample,test sample and estimated values are 0.9992,0.9983 and 0.9981 respectively.All of them were over 0.9980,and the experimental value of three kinds ofsamples and the overall alignment is as high as 0.9989.Moreover,the results showed that the relative error rate between the neural network and its experimental measurement/test value of the electric welding machine energy consumption,dust PM 2.5,PM 10 and noise were respectively within 4.2%,8.5%,4.0% and 2.5%.Finally,through the software development platform of Visual Basic,the database system of resource environmental attributes for concrete pump truck of welding technology has been developed.This software system has passed the software identification test in software evaluation center of Hunan province,and has successfully demonstrated and applied in Zoomlion Heavy Industry Science & Technology Co.,Ltd.
Keywords/Search Tags:Concrete pump trucks, Welding technology, Multi-source energy consumption models, Multi-source carbon emission models, Database system for resource environmental attributes data
PDF Full Text Request
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