【摘要】：采用激光表面仿生強(qiáng)化技術(shù)提高模具的使用壽命是近幾年新興的一個(gè)課題，是仿生學(xué)在模具工業(yè)領(lǐng)域中的重要應(yīng)用，為模具行業(yè)帶來了巨大的經(jīng)濟(jì)效益。將激光仿生強(qiáng)化工藝規(guī)范化更有助于其在未來的發(fā)展與推廣。 文中以人工神經(jīng)網(wǎng)絡(luò)理論為依據(jù)，將激光熔凝單元體形態(tài)和激光加工工藝之間存在的高度非線性關(guān)系視為“黑箱”，把熔凝單元體橫截面尺寸作為神經(jīng)網(wǎng)絡(luò)的輸入，激光工藝參數(shù)作為神經(jīng)網(wǎng)絡(luò)的輸出，建立了激光熔凝參數(shù)反求模型。采用結(jié)構(gòu)化分析方法對壓鑄模具激光仿生強(qiáng)化工藝決策系統(tǒng)進(jìn)行了功能模塊劃分和結(jié)構(gòu)設(shè)計(jì)。從系統(tǒng)總體功能出發(fā)，設(shè)計(jì)了壓鑄模具材料表、激光工藝參數(shù)表、熔凝結(jié)果表、仿生形態(tài)表、熱疲勞性能表和摩擦磨損性能表以及表與表之間的關(guān)系，建立了壓鑄模具激光仿生強(qiáng)化工藝數(shù)據(jù)庫。以Visual C++6.0為開發(fā)平臺(tái)，采用模塊化編程設(shè)計(jì)人機(jī)交互界面，，開發(fā)出具有自主知識(shí)產(chǎn)權(quán)的壓鑄模具激光仿生強(qiáng)化工藝決策系統(tǒng)。 最后，以DIEVAR模具鋼為例，從激光熔凝單元體的橫截面尺寸、組織形態(tài)、顯微硬度和熱疲勞性能四個(gè)方面對壓鑄模具激光仿生強(qiáng)化工藝決策系統(tǒng)的決策精度和整體性能進(jìn)行了測試。結(jié)果顯示：系統(tǒng)穩(wěn)定性良好；決策精度能夠達(dá)到1.33%；經(jīng)反求的激光工藝參數(shù)熔凝加工后，材料硬度提高了40-100HV，熱疲勞性能也顯著提高。將該系統(tǒng)應(yīng)用于實(shí)際模具強(qiáng)化工藝制定中，經(jīng)生產(chǎn)運(yùn)行顯示，強(qiáng)化后的模具壽命提高約70%。
[Abstract]:The application of laser surface bionic strengthening technology to improve the service life of mould is a new topic in recent years. It is an important application of bionics in the field of mould industry and brings great economic benefits to die industry. The standardization of laser bionic strengthening technology is helpful to its development and popularization in the future. Based on the theory of artificial neural network, the highly nonlinear relationship between the shape of laser coagulation unit and the laser processing technology is regarded as a "black box", and the cross section size of the fusion unit is regarded as the input of neural network. Laser process parameters are used as the output of neural network, and the inverse model of laser melting parameters is established. The structural analysis method is used to divide the function modules and design the structure of the process decision system for the laser bionic strengthening of die casting die. Based on the overall function of the system, the material table of die casting die, the parameter table of laser process, the result table of melting, the bionic form table, the table of thermal fatigue performance and the table of friction and wear performance, and the relationship between the table and the table are designed. The database of laser bionic strengthening process for die casting die was established. With Visual C 6.0 as the development platform, the man-machine interactive interface is designed by modular programming, and a die casting mould laser bionic strengthening process decision system with independent intellectual property rights is developed. Finally, taking DIEVAR die steel as an example, the cross section size and microstructure of laser solidifying unit are analyzed. Four aspects of microhardness and thermal fatigue performance of the die casting die laser bionic strengthening process decision-making system decision-making accuracy and overall performance were tested. The results show that the stability of the system is good, the decision accuracy can reach 1.33, and the hardness of the material is increased by 40 ~ 100 HVV, and the thermal fatigue property is also improved significantly after the reverse laser processing parameters are fused and solidified. The system is applied to the actual die strengthening process. The operation shows that the service life of the strengthened die is increased by about 70%.
【學(xué)位授予單位】：太原科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TG665;TG233.1

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