克服 2x-Thru 去嵌入法中的挑戰：解決印刷電路板校準 中的夾具誤差、參考阻抗及表面粗糙度估計問題

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姓名

許任翔(Jen-Hsiang Hsu) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

克服 2x-Thru 去嵌入法中的挑戰：解決印刷電路板校準中的夾具誤差、參考阻抗及表面粗糙度估計問題
(Overcoming Challenges in 2x-Thru De-embedding: Addressing Fixture Mismatch, Reference Impedance, and Surface Roughness Estimation in PCB Calibration)

相關論文

★ 兩端口及四端口2x-thru去嵌入法之實作

★ 使用平衡截取與被動降階互連建模法簡化向量擬合所得之模型

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至系統瀏覽論文 (2028-7-18以後開放)

摘要(中)

在高速傳輸時代中，隨著頻率的提升，保持信號完整性變得越來越重要。然而，從印刷電路板中獲取待測物響應是具有挑戰性的。因此，需要進行校正演算法來獲得純粹的待測物響應。許多校正演算法都要求夾具之間的匹配，但在印刷電路板中實現這一點非常困難。話雖如此，商用軟體中的2x-thru校正演算法已經實現了解決夾具不匹配的功能。
2x-thru是近幾年才開始盛行，且很少有研究從參考阻抗的角度分析2x-thru校正演算法，這些問題都是值得探討且不能被忽視的。例如，校正後的待測物參考組抗是什麼？如何決定？如何預估參考阻抗？本論文首先通過自行實現的Python校正演算法，驗證了校正兩種實際量測的PCB和模擬數據的精確度。其次，我們在驗證了自行實現的去嵌入演算法後，討論了兩個實際應用中常遇到的問題。第一個問題是先前提到的夾具不匹配修正，在PCB中，待測物與校正套件之間的不匹配特別常見，這是所有校正演算法面臨的主要挑戰。商用軟體都有相應功能，但並未公開演算法細節。因此，我們提出了解決方法，並且校正結果與商用軟體相當。第二個問題是金屬表面粗糙度，隨著頻率上升，電流更加集中在表面，金屬表面粗糙度也變得更加重要。但在實際應用中，獲取粗糙度得過程是非常繁瑣的。因此，我們將文獻中提出的估計粗糙度的流程應用於實際量測數據，並在過程中發現了一些值得進一步研究的問題。
總之，我們從參考阻抗的角度入手，剖析了幾個經常被忽視但非常重要的問題，特別是其對校正演算法的影響。在論文的結論部分，我們提及了工作的不足之處，並提出了未來研究和改進的潛在方向。

摘要(英)

Various calibration algorithms exist for de-embedding, with the 2x-thru algorithm being widely used in PCB transmission line applications due to its simplicity. However, the issue of reference impedance alignment with this algorithm has not been extensively studied. This thesis focuses on this overlooked problem, validating our self-implemented de-embedding algorithms through real measurements and simulations.
We also address two other important practical aspects: impedance correction for 2x-thru de-embedding and surface roughness of PCB transmission lines. Impedance correction involves aligning the reference impedance of the 2x-thru (Cal-Kit) with the fixture of the device under test (DUT). We propose a solution to address this challenge, achieving correction results comparable to commercial de-embedding tools.
Regarding surface roughness, a critical factor in PCB channel characterization, we estimate its scale using S-parameters after 2x-thru calibration. Accurate calibration is essential for robust roughness characterization. During this estimation process, we identify and discuss issues related to the variability of roughness across different sides of the copper surface in a stripline, incorporating this variability into our estimation process for broader applicability.
To summarize, we begin by examining the reference impedance and subsequently address several overlooked yet significant issues within the calibration algorithm. In the conclusion of this thesis, we acknowledge the limitations of our work and propose potential directions for future research and improvement.

關鍵字(中)

★ 校正演算法

關鍵字(英)

★ de-embedding algorithm

論文目次

摘要 I
Abstract II
誌謝 III
Outline IV
List of Figures V
List of Tables VIII
Chapter 1 Introduction: De-embedding Calibration Algorithm 1
1.1 General Introduction 1
1.2 TRL/TL De-embedding 3
1.3 Comparison of De-embedding Methods 9
1.4 Objectives and Organization of this Thesis 10
Chapter 2 2x-thru Implementation and Validation 12
2.1 2x-thru De-embedding Theory 12
2.2 Implementation on Simulation Data 16
2.3 Implementation on Measurement Data 25
Chapter 3 The Issue of Reference Impedance 33
3.1 Meaning of Reference Impedance 33
3.2 Impedance Estimation 37
Chapter 4 Impedance-corrected 2x-thru De-embedding 42
4.1 Basics of Impedance-Corrected De-embedding 42
4.2 The Proposed Process Detail 44
4.3 Validation by Simulation Data 55
4.4 Implementation on the Measurement Data 62
Chapter 5 Application to Surface Roughness Estimation 75
5.1 Fundamentals of Surface Roughness Estimation 75
5.2 Implementation of Surface Roughness Model 80
5.3 Test Result and Discussion 85
Chapter 6 Conclusions and Future Works 97
Reference 99

參考文獻

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指導教授

周求致(Chiu-Chih Chou)

審核日期

2023-7-19

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