【摘要】：旋轉(zhuǎn)電弧角焊是焊接領(lǐng)域中的重要工藝,不同的焊接參數(shù)對(duì)應(yīng)的焊接溫度場(chǎng)與應(yīng)力應(yīng)變場(chǎng)又有所不同,對(duì)于焊接后續(xù)變形控制研究造成較大阻礙,因此有必要利用焊接智能優(yōu)化算法來(lái)優(yōu)化焊接工藝參數(shù),并與數(shù)值模擬方法相結(jié)合,從而得到高質(zhì)量成形焊縫,而較優(yōu)工藝參數(shù)又能夠用于焊接熱力學(xué)研究,這樣節(jié)省試驗(yàn)成本,縮短研發(fā)周期。為對(duì)旋轉(zhuǎn)電弧角焊進(jìn)行焊接工藝參數(shù)優(yōu)化,減少試驗(yàn)次數(shù),提高焊接效率,首先采用基于minitab的正交試驗(yàn)法,并充分考慮各焊接參數(shù)之間相互作用與影響,建立正交試驗(yàn)?zāi)Ｐ筒⑦M(jìn)行相應(yīng)的焊接試驗(yàn),然后測(cè)量焊后各工件角焊縫尺寸,利用主觀分析法與殘差分析法分析該正交模型中各焊接工藝參數(shù)間相互匹配關(guān)系與擬合優(yōu)度問(wèn)題。為快速獲得較優(yōu)焊接工藝參數(shù),基于BP(Back Propagation,BP)神經(jīng)網(wǎng)絡(luò)建立旋轉(zhuǎn)電弧角焊焊縫尺寸預(yù)測(cè)模型。通過(guò)對(duì)預(yù)測(cè)樣本數(shù)據(jù)的訓(xùn)練,得出焊接參數(shù)與焊縫尺寸之間的映射關(guān)系,其預(yù)測(cè)樣本可驗(yàn)證調(diào)試后的遺傳神經(jīng)網(wǎng)絡(luò)�；贐P神經(jīng)網(wǎng)絡(luò)非線性映射預(yù)測(cè)能力與遺傳算法全局尋優(yōu)能力,建立遺傳神經(jīng)網(wǎng)絡(luò)的旋轉(zhuǎn)電弧焊接參數(shù)優(yōu)化模型,對(duì)焊接參數(shù)進(jìn)行了優(yōu)化。為準(zhǔn)確模擬工件在焊接過(guò)程中所受外載荷,采用基于ANSYS的數(shù)值模擬與試驗(yàn)相結(jié)合的方法,以位移約束和集中力約束的施加與釋放模擬焊接夾具的外拘束,通過(guò)接觸分析得到工件所承受的支持力與夾緊力。最后,依據(jù)所設(shè)計(jì)的試驗(yàn)平臺(tái)分別建立3種不同的多體耦合模型模擬夾具與工件的夾緊作用,分析工件上、下側(cè)板von Mises應(yīng)力與X、Y向應(yīng)力分布規(guī)律及X、Y向變形形成機(jī)理。由于外拘束模型仿真分析結(jié)果需試驗(yàn)驗(yàn)證,為此實(shí)驗(yàn)室搭建了旋轉(zhuǎn)電弧角焊工件變形測(cè)量試驗(yàn)平臺(tái),采用角焊專(zhuān)用量規(guī)對(duì)工件下側(cè)板對(duì)應(yīng)測(cè)量點(diǎn)進(jìn)行了準(zhǔn)確測(cè)量以得到工件角變形與彎曲變形,進(jìn)而對(duì)旋轉(zhuǎn)電弧角焊熱應(yīng)力數(shù)值模擬平臺(tái)進(jìn)行完善與改進(jìn)。
[Abstract]:Rotating arc angle welding is an important technology in welding field. The welding temperature field and stress-strain field corresponding to different welding parameters are different, which is a big obstacle to the research of welding subsequent deformation control. Therefore, it is necessary to optimize welding parameters by using welding intelligent optimization algorithm, and combine with numerical simulation method to obtain high quality formed weld, and the better process parameters can be used in the study of welding thermodynamics. This saves the test cost, shortens the research and development cycle. In order to optimize the welding process parameters, reduce the number of tests and improve the welding efficiency, the orthogonal test method based on minitab is adopted, and the interaction and influence of the welding parameters are fully considered. The orthogonal test model was established and the corresponding welding test was carried out. Then the angle weld size of each workpiece after welding was measured. The matching relationship and the goodness of fit among the welding process parameters in the orthogonal model were analyzed by the subjective analysis method and the residual analysis method. In order to obtain better welding parameters quickly, a prediction model of welding seam size for rotating arc angle welding was established based on BP (Back Propagation BP (BP) neural network. The mapping relationship between welding parameters and weld size is obtained by training the predicted sample data. The predicted sample can verify the genetic neural network after debugging. Based on BP neural network nonlinear mapping prediction ability and genetic algorithm global optimization ability, the optimization model of rotating arc welding parameters based on genetic neural network is established, and the welding parameters are optimized. In order to accurately simulate the external load of workpiece in welding process, the method of combining numerical simulation and test based on ANSYS is adopted to simulate the external restraint of welding fixture by applying and releasing the constraint of displacement and concentrated force. The supporting force and clamping force of the workpiece are obtained by contact analysis. Finally, according to the designed test platform, three different multi-body coupling models are established to simulate the clamping action between the fixture and the workpiece, and the distribution of von Mises stress and XY direction stress in the upper and lower side plates of the workpiece are analyzed, as well as the forming mechanism of the X-Y direction deformation. Because the simulation results of external restraint model need to be tested and verified, a test platform for measuring the deformation of rotating arc angle welding workpiece has been set up in the laboratory. The angle deformation and bending deformation of the workpiece are obtained by measuring the corresponding measuring points of the lower side plate of the workpiece by using the special gauge for angle welding, and the numerical simulation platform for the thermal stress of the rotary arc angle welding is improved and improved.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TG44

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