本文關(guān)鍵詞：基于改進(jìn)GA-BP算法的SMAW工藝參數(shù)的優(yōu)化　出處：《內(nèi)蒙古科技大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 手工電弧焊 焊接變形 GA-BP算法 工藝參數(shù)優(yōu)化

【摘要】：焊接技術(shù)是現(xiàn)代機(jī)械制造的關(guān)鍵工藝技術(shù)，其中以手工電弧焊最為常見(jiàn)，但容易產(chǎn)生較嚴(yán)重的焊接變形是手工電弧焊最大的缺陷。本文應(yīng)新宏昌重工有限責(zé)任公司技術(shù)部的研發(fā)需求，針對(duì)該公司生產(chǎn)的自卸車車廂焊接變形較為嚴(yán)重的問(wèn)題，結(jié)合公司焊接生產(chǎn)實(shí)際，以實(shí)用、可行為基本原則，，在深入了解焊接變形形成機(jī)理、影響因素和控制技術(shù)的基礎(chǔ)上，從優(yōu)化焊接工藝參數(shù)的角度出發(fā)，采用改進(jìn)型GA-BP算法來(lái)對(duì)該公司手工電弧焊焊接工藝進(jìn)行優(yōu)化，以期達(dá)到解決產(chǎn)品焊接質(zhì)量缺陷的目的。 本文首先對(duì)新宏昌重工有限責(zé)任公司現(xiàn)有的焊接工藝進(jìn)行全面分析，客觀判斷導(dǎo)致焊接變形產(chǎn)生的工藝因素，確定工藝優(yōu)化方向。在此基礎(chǔ)上，針對(duì)性的選擇基于改進(jìn)GA-BP算法的焊接變形預(yù)測(cè)策略和多目標(biāo)工藝參數(shù)優(yōu)化相結(jié)合的策略，來(lái)實(shí)現(xiàn)對(duì)焊接工藝參數(shù)的優(yōu)化。 因焊接工藝參數(shù)與焊接變形之間的非線性關(guān)系高度復(fù)雜，本文以焊接電流、焊接電壓、焊接速度和冷卻速度為輸入，以橫向收縮變形和角變形為輸出，構(gòu)建了小樣本、高精度、基于改進(jìn)GA-BP算法的變形預(yù)測(cè)模型，在各項(xiàng)實(shí)測(cè)數(shù)據(jù)的基礎(chǔ)上，利用該GA-BP模型強(qiáng)大的非線性關(guān)系識(shí)別能力，來(lái)尋找焊接工藝參數(shù)與焊接變形之間的非線性關(guān)系，奠定多目標(biāo)工藝參數(shù)優(yōu)化的基礎(chǔ)。 在多目標(biāo)工藝參數(shù)優(yōu)化中，以GA-BP變形預(yù)測(cè)模型所尋找得到的工藝參數(shù)與焊接變形之間的非線性關(guān)系，來(lái)代替多目標(biāo)工藝參數(shù)優(yōu)化中的目標(biāo)函數(shù)，并結(jié)合工廠焊接生產(chǎn)實(shí)際情況選定優(yōu)化變量約束條件、即焊接工藝參數(shù)的取值范圍，構(gòu)建基于正交原則的優(yōu)化求解空間，以橫向收縮變形和角變形最小為優(yōu)化目標(biāo)，建立多目標(biāo)工藝參數(shù)優(yōu)化模型，用于實(shí)現(xiàn)焊接工藝參數(shù)的優(yōu)化。 此外，本文合理設(shè)計(jì)試驗(yàn)方案，利用真實(shí)的實(shí)測(cè)數(shù)據(jù)對(duì)基于改進(jìn)GA-BP算法的變形預(yù)測(cè)模型的預(yù)測(cè)效率、多目標(biāo)工藝參數(shù)優(yōu)化模型優(yōu)化結(jié)果的有效性進(jìn)行了驗(yàn)證，驗(yàn)證表明本文所提出的焊接工藝參數(shù)優(yōu)化策略可以通過(guò)實(shí)現(xiàn)對(duì)焊接工藝參數(shù)的優(yōu)化有效減小焊接變形量。并在此基礎(chǔ)上，利用Matlab平臺(tái)開(kāi)發(fā)出基于改進(jìn)GA-BP算法的SMAW焊接工藝參數(shù)優(yōu)化系統(tǒng)，大大提升了本文核心理論的的工程應(yīng)用價(jià)值。
[Abstract]:Welding technology is the key technology of modern mechanical manufacturing, in which manual arc welding is the most common. But more serious welding deformation is the biggest defect of manual arc welding. This paper should meet the research and development requirements of the technical department of Xinhongchang heavy Industry Co., Ltd. Aiming at the serious problem of welding deformation of dump truck car produced by the company, combined with the actual welding production of the company, taking practical and feasible as the basic principle, the forming mechanism of welding deformation is deeply understood. On the basis of influencing factors and control technology, from the point of view of optimizing welding process parameters, the improved GA-BP algorithm is adopted to optimize the welding process of manual arc welding in this company. In order to solve the welding quality defects. In this paper, the existing welding process of Xinhongchang heavy Industry Co., Ltd. is analyzed comprehensively, the process factors that lead to welding deformation are judged objectively, and the direction of process optimization is determined. The welding deformation prediction strategy based on the improved GA-BP algorithm and the multi-objective process parameter optimization strategy are selected to optimize the welding process parameters. Because the nonlinear relationship between welding parameters and welding deformation is highly complex, this paper takes welding current, welding voltage, welding speed and cooling speed as input, and takes transverse shrinkage deformation and angular deformation as output. The deformation prediction model based on the improved GA-BP algorithm is constructed with small sample and high precision. Based on the measured data, the strong nonlinear relationship recognition ability of the GA-BP model is utilized. To find the nonlinear relationship between welding process parameters and welding deformation, and lay the foundation of multi-objective process parameters optimization. In the optimization of multi-objective process parameters, the nonlinear relationship between process parameters and welding deformation obtained by GA-BP deformation prediction model is used to replace the objective function in multi-objective process parameter optimization. Combined with the actual situation of factory welding production, the constraints of optimization variables, that is, the range of welding process parameters, are selected, and the optimization solution space based on orthogonal principle is constructed. Aiming at minimum transverse shrinkage and angle deformation, a multi-objective process parameter optimization model is established to optimize welding process parameters. In addition, the experiment scheme is designed reasonably, and the prediction efficiency of the deformation prediction model based on the improved GA-BP algorithm is obtained by using the real measured data. The effectiveness of the optimization results of multi-objective process parameters optimization model is verified. The results show that the proposed optimization strategy can effectively reduce the welding deformation by optimizing the welding parameters. The optimization system of welding parameters for SMAW welding based on improved GA-BP algorithm is developed by using Matlab platform, which greatly enhances the engineering application value of the core theory of this paper.
【學(xué)位授予單位】：內(nèi)蒙古科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TG404

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 蔡廣宇;楊家軍;李永久;;弧焊機(jī)器人焊接工藝參數(shù)設(shè)計(jì)系統(tǒng)研究[J];組合機(jī)床與自動(dòng)化加工技術(shù);2009年11期

2 吳濤;;用遺傳算法優(yōu)化神經(jīng)網(wǎng)絡(luò)權(quán)值[J];湛江師范學(xué)院學(xué)報(bào);2007年03期

3 郭釗;;Q345鋼的焊接工藝及其應(yīng)用研究[J];科技創(chuàng)新導(dǎo)報(bào);2008年26期

4 劉松;賈東樂(lè);;自卸車焊接變形的控制和矯正[J];專用汽車;2011年06期

5 梁毅;劉世洪;;基于遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)的組合預(yù)測(cè)模型方法研究[J];中國(guó)農(nóng)業(yè)科學(xué);2012年23期

本文編號(hào)：1436334