臺灣博碩士論文加值系統

微電阻銲(micro resistance welding)屬於微接合(micro-joining)領域中之一種薄金屬接合方法，被廣泛應用於汽車電子、光電元件封裝、醫工元件、感測器等工業上，具有生產快速及低營業成本之優點，非常適合大量生產。但在實際生產線上，至今仍缺乏非破壞性之線上檢測技術，無法非常精確及時監測銲接之品質，導致銲件之不良率偏高。因此，本文主要目標為建立一套微電阻點銲實驗系統，並發展其線上檢測技術，以即時監測銲接品質。
利用所發展之系統於0.1594mm鐵鈷鎳合金(KOVAR)及0.1mm不鏽鋼等材料銲接時，由銲接過程之動態資料，並經過拉伸實驗驗證銲接品質之銲點抗拉強度資料，經參數相關性分析後，發現最大電極位移量及最低動態電阻兩項參數與最大破壞拉力之相關係數分別為0.9161及-0.8808，顯示兩參數與銲點強度間之相關性非常高。將兩參數匯入類神經網路建立之品質監測模組，對類神經網路進行銲接品質判斷訓練，測試該神經網路之預測能力。
本研究利用類神經網路所建立之品質監測模組，可依照銲點之應用強度需求，設定銲點之強度分類等級進行分類。在鐵鈷鎳合金材料檢測部分，將銲接品質分為良好及不良兩類，其預測準確度高達100%。另外在不鏽鋼部分依照銲接之數據，區分成三個強度等級，包括不良、良好及最佳等三個等級，經測試其判斷銲接品質準確度高達93%，測試結果顯示本系統可精確預測銲點之強度。
本系統可依需求設定不同之銲接強度分類標準，將可實際應用在線上之銲接品質監控，得到即時之銲接品質資訊。未來將資訊應用在銲接系統控制上，將可得到更穩定之銲接品質。

Micro-resistance spot welding (MRSW) is a group of micro-joining processes in which micro-joints are formed between two sheets by resistance heating caused by the passage of electric current. These processes are commonly applied to the weld of auto electrical components, and micro-electrical components, and medical packing. Because of its many advantages such as high manufacturing speed and low cost, the MRSW is very suitable for industrial mass-production applications.
Surprisingly, there is no satisfactory non-destructive on line monitoring systems to assure the quality of the welding process. This thesis is aimed to develop a MRSW equipment and its associated monitoring system that can predict the welding quality during the welding process.
The thesis was preceded by designing an experimental test rig for the MRSW. Then a series of experiments were carried out to find the key parameters that can feature the welding quality. Experiments have shown that the values of the maximum electrode displacement and minimum dynamic resistance of a joint relate its welding quality quite well. Using these two parameters, a neural network based on-line welding quality monitor was developed.
The developed quality monitor system has been successfully applied to the welds of 0.1mm stainless steel and 0.1594mm KOVAR sheets, respectively. In the experiments, the achieved success rates in the two-class welding quality classification for the KOVAR sheets was 100% whilst the three-class classification for the stainless steel sheets was 93%.
The results show that the proposed MRSW monitor system processes an excellent accuracy in predicting the quality of a welding joint in terms of the tensile strength.
The developed monitoring system has the advantage of easy implementation in the field.

Table of Contents
摘要......................................................................................................... Ⅰ
Abstract................................................................................................... Ⅲ
誌謝........................................................................................................ Ⅴ
Table of Contents.................................................................................... Ⅵ
List of Figure........................................................................................... Ⅷ
List of Table............................................................................................ Ⅹ
Chapter 1 Introduction............................................................................ 1
1.1 Background................................................................................. 1
1.2 Motivation................................................................................... 3
1.3 Literature review......................................................................... 5
1.4 Thesis arrangement..................................................................... 7
Chapter 2 Design of the Test Rig............................................................ 8
2.1 .Design of welding stand............................................................. 10
2.2 Design of current controller........................................................ 12
2.3 Tensile strength tester................................................................. 15
2.4 Characteristics of the MRSW..................................................... 17
Chapter 3 The Weld of KOVAR............................................................. 20
3.1 Welding quality estimation …………….................................... 20
3.2 Experimental results................................................................... 26
Chapter 4 The Weld of Stainless Steel................................................... 31
4.1 Welding quality estimation......................................................... 31
4.2 Experimental results.................................................................... 35
Chapter 5 Conclusions and Remarks...................................................... 41
Reference................................................................................................ 43
Appendix A The Neural Network........................................................... 47
Biosketch of Author................................................................................ 50

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