本文選題：激光熔覆修復 + 工藝規(guī)劃�。� 參考：《南京航空航天大學》2017年碩士論文

【摘要】：激光熔覆作為一項新型的綠色再制造技術,以成形組織性能好、適用范圍廣、對環(huán)境污染小等優(yōu)點在金屬零件的修復中得到了廣泛的應用。工藝規(guī)劃是實現(xiàn)激光熔覆修復自動化的基礎,合理的工藝規(guī)劃可以大大提高修復的質(zhì)量和效率。但目前激光熔覆修復缺乏完整的工藝規(guī)劃體系,修復中工藝參數(shù)設置缺乏理論依據(jù),使得修復質(zhì)量無法保證,修復自動化難以實現(xiàn)。為了提高修復質(zhì)量與效率,實現(xiàn)激光熔覆修復自動化,本文對激光熔覆修復的工藝規(guī)劃進行了相關研究,主要內(nèi)容包括:(1)針對預處理后零件表面缺損特點,提出了一種基于機器視覺的三維缺損特征提取方法。首先根據(jù)缺損區(qū)域二維圖像邊界與三維特征點坐標,對零件缺損底面的空間邊界進行重構和定位,再結合缺損表面信息,實現(xiàn)對零件三維缺損特征的提取。(2)根據(jù)零件缺損特征,對激光掃描路徑進行規(guī)劃,分析了熔覆層形貌特征對熔覆成形的影響,建立了單道熔覆層特征參數(shù)決策模型,在此基礎上研究了激光熔覆修復的路徑規(guī)劃與運動實現(xiàn)問題。(3)針對熔覆過程的復雜性,采用粒子群優(yōu)化(PSO)的反向傳播(BP)神經(jīng)網(wǎng)絡建立熔覆工藝參的預測模型,通過仿真測試和熔覆試驗驗證了所建預測模型的可靠性,實現(xiàn)了在樣本范圍內(nèi)對特定單道熔覆層特征的熔覆工藝參數(shù)決策。本文針對表面損傷零件的激光熔覆修復,建立了一套修復工藝規(guī)劃體系,并圍繞著修復路徑規(guī)劃和熔覆工藝參數(shù)決策設計了多道激光熔覆試驗,驗證了修復工藝規(guī)劃方法的合理性與可行性,表明所提方法可以有效的指導缺損零件的激光熔覆修復工作,為激光熔覆修復的自動化實現(xiàn)提供了理論依據(jù)。
[Abstract]:Laser cladding, as a new green remanufacturing technology, has been widely used in the repair of metal parts because of its advantages of good forming structure and properties, wide application range and low environmental pollution. Process planning is the basis to realize the automation of laser cladding repair, and reasonable process planning can greatly improve the quality and efficiency of restoration. But at present, the laser cladding repair lacks a complete process planning system, and the process parameters set in the restoration are lack of theoretical basis, which makes the repair quality can not be guaranteed, and the repair automation is difficult to realize. In order to improve the quality and efficiency of laser cladding and realize the automation of laser cladding repair, the process planning of laser cladding repair is studied in this paper. The main contents include: 1) aiming at the characteristics of surface defect of pretreated parts. A 3D defect feature extraction method based on machine vision is proposed. Firstly, according to the coordinates of 2D image boundary and 3D feature point of the defect area, the space boundary of the bottom surface of the defect is reconstructed and located, and then the 3D defect feature of the part is extracted according to the defect feature by combining the defect surface information. The laser scanning path is planned, and the influence of the morphology of the cladding layer on the cladding forming is analyzed, and the decision model of the characteristic parameters of the cladding layer is established. Based on this, the path planning and motion realization of laser cladding repair is studied. Aiming at the complexity of cladding process, a predictive model of cladding process parameters is established by using PSO (Particle Swarm Optimization) and back Propagation (BPN) neural network. The reliability of the prediction model is verified by simulation test and cladding test, and the decision of cladding process parameters is realized in the sample range for the characteristics of a specific single cladding layer. In this paper, a repair process planning system is set up for repairing surface damage parts by laser cladding, and multi-channel laser cladding test is designed around repair path planning and cladding process parameters decision. The rationality and feasibility of the repair process planning method are verified. The results show that the proposed method can effectively guide the laser cladding repair of defective parts and provide a theoretical basis for the automatic realization of laser cladding repair.
【學位授予單位】：南京航空航天大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TG665

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本文編號：2010208