本文選題：全自動探針臺　切入點：機器視覺　出處：《浙江大學(xué)》2017年碩士論文

【摘要】：近年來,半導(dǎo)體制造工藝快速發(fā)展,微小芯片的市場需求急劇增加,芯片尺寸、引線間距和焊盤直徑不斷減小,因此對封裝設(shè)備的運動精度要求越來越高,基于機器視覺的檢測技術(shù)已成為IC裝備精度保障的關(guān)鍵技術(shù)。本文研究了機器視覺在晶圓檢測中的應(yīng)用,基于視覺定位算法設(shè)計了全自動探針臺中X/Y方向上的三個主要定位功能:晶圓圓心定位、晶圓位置自動校正以及針尖與針痕中心檢測。全文主要包括以下內(nèi)容:第一章闡述了機器視覺系統(tǒng)的應(yīng)用及其研究現(xiàn)狀,分析了機器視覺在晶圓檢測中的應(yīng)用情況,最后給出了論文的主要研究內(nèi)容。第二章分析了全自動探針臺視覺定位系統(tǒng)的三大主要功能需求,給出了全自動探針臺視覺定位系統(tǒng)的總體設(shè)計方案,根據(jù)系統(tǒng)精度要求完成了視覺系統(tǒng)中相機、鏡頭的選型。第三章對比分析了四種經(jīng)典邊緣提取算法,在此基礎(chǔ)上提出了多尺度結(jié)構(gòu)邊緣檢測算法,實現(xiàn)了邊緣點的準(zhǔn)確定位;基于多尺度邊緣檢測算法設(shè)計了晶圓圓心檢測方案,提高了晶圓圓心定位精度。第四章研究了 SURF、SIFT特征點檢測算法,實驗對比分析了兩種算法的優(yōu)劣性。根據(jù)實驗結(jié)果,基于SIFT算法設(shè)計了晶圓位置校正方案,并通過實驗驗證了該方案的魯棒性以及高精度。第五章分析了形態(tài)學(xué)圖像處理算法以及多種輪廓中心求解算法,基于形態(tài)學(xué)圖像處理算法以及中心矩算法設(shè)計了針尖與針痕中心檢測方案,得出了針尖中心位置以及焊盤中心與針痕中心的位置差,保證了探針臺自動對針功能的實現(xiàn)。第六章總結(jié)了全文主要研究內(nèi)容,對后續(xù)研究工作進行展望。
[Abstract]:In recent years, with the rapid development of semiconductor manufacturing technology, the market demand for microchips has increased sharply, and the chip size, lead spacing and pad diameter have been reduced, so the motion accuracy of packaging equipment is required more and more. The detection technology based on machine vision has become the key technology of IC equipment precision guarantee. This paper studies the application of machine vision in wafer detection. Based on the visual localization algorithm, three main localization functions in the X / Y direction of the automatic probe table are designed: wafer center location, The main contents of this paper are as follows: in Chapter 1, the application of machine vision system and its research status are described, and the application of machine vision in wafer detection is analyzed. Finally, the main research contents of the thesis are given. In chapter 2, the three main functional requirements of the automatic probe platform vision positioning system are analyzed, and the overall design scheme of the automatic probe platform vision positioning system is given. According to the requirement of system precision, the selection of camera and lens in visual system is completed. In chapter 3, four classical edge detection algorithms are compared and analyzed. On this basis, a multi-scale structure edge detection algorithm is proposed to realize the accurate location of edge points. Based on the multi-scale edge detection algorithm, a wafer centroid detection scheme is designed, which improves the accuracy of the wafer centroid location. In Chapter 4, the detection algorithm of surfman sift feature points is studied, and the advantages and disadvantages of the two algorithms are compared and analyzed experimentally. According to the experimental results, the advantages and disadvantages of the two algorithms are compared and analyzed. Based on the SIFT algorithm, the wafer position correction scheme is designed, and the robustness and high precision of the scheme are verified by experiments. In chapter 5, the morphological image processing algorithm and various contour center solving algorithms are analyzed. Based on the morphological image processing algorithm and the center moment algorithm, the detection scheme of needle tip and needle mark center is designed, and the position difference between the tip center and the pin mark center is obtained. In chapter 6, the main contents of this paper are summarized, and the future research work is prospected.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TN307

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