臺灣博碩士論文加值系統

本研究探討麥克生干涉(Michelson Interference, MI)感測器的非理想干涉訊號解調，透過電光調變器(Electro-Optic Modulation, EOM)模擬非理想干涉訊號中光源強度干擾的影響，當採用傳統解調方法，如相位生成載波(Phase Generated Carrier, PGC)中微分交叉相乘( Differentiation and Cross Multiplication, DCM)，會有相位延遲、調變深度問題，這些問題會造成解調後的待測訊號波形失真。
為了改善這些問題，以採用了深度學習(Deep Learning, DL)中的Pixel2Pixel生成對抗網路(Generative Adversarial Network, GAN)方法實現解調，將模擬麥克生干涉感測器的非理想干涉訊號與目標訊號作為樣本圖像進行訓練模型，再以經過訓練模型生成的圖像與目標圖像做成功率的判斷。將非理想干涉訊號結果與傳統麥克生干涉感測器的理想干涉訊號做比較與分析。

This research explores the demodulation of non-ideal interference signals from the Michelson Interference (MI) sensor and simulates the impact of light intensity disturbance on the non-ideal interference signal using Electro-Optic Modulation (EOM). Traditional demodulation methods, such as Differentiation and Cross Multiplication (DCM) in Phase Generated Carrier (PGC), may lead to phase delay and modulation depth issues, these issues will result in waveform distortion in the measured demodulated signal.
In order to address these issues, the Pixel2Pixel Generative Adversarial Network (GAN) method in Deep Learning (DL) is employed for demodulation. This method involves combining the non-ideal interference signal from the simulated Michelson interference sensor with the target signal to create a sample image for training the model. Subsequently, the model generates an image, which is then compared with the target image to evaluate efficiency. Compare and analyze the non-ideal interference signal results with the ideal interference signal of the traditional Michelson interference sensor.

摘要…i
Abstract…ii
誌謝…iii
目錄…iv
表目錄…vi
圖目錄…vii
第一章 緒論…1
1.1前言…1
1.2研究動機與目的…1
1.3文獻探討…2
1.4論文架構…7
第二章 光纖感測器基本理論與解調系統介紹…8
2.1 光纖感測器基本介紹…8
2.1.1 光纖感測器的分類…9
2.1.2 光纖感測器的相位變化…9
2.1.3 相位調變…10
2.2 光纖感測理論分析…12
2.3 光纖感測解調技術…14
2.3.1反正切演算法解調技術…14
2.3.2 微分交叉相乘法解調技術…15
2.3.3模擬光源強度干擾影響下的震動訊號微分交叉相乘法解調技術…16
2.3.4相關解調技術…16
第三章 Pixel2PixelGAN背景與原理介紹…18
3.1Pixel2PixelGAN介紹…18
3.2生成器架構…20
3.3鑑別器架構…21
3.4卷積層結構…22
第四章 實驗內容與結果…24
4.1實驗架構…24
4.2實驗結果…28
4.2.1 麥克生干涉感測器訊號的PGC-DCM與PGC-Atan解調技術實驗…28
4.2.2 麥克生干涉感測器訊號解調系統與Pixel2PixelGAN結合解調技術…32
4.2.3 低光源強度干擾的PGC-DCM與PGC-Atan解調技術實驗…35
4.2.4 低光源強度干擾的Pixel2PixelGAN解調技術…39
4.2.5 高光源強度干擾的麥克生干涉感測器訊號解調系統的PGC-DCM與PGC-Atan解調技術實驗…42
4.2.6 高光源強度干擾的Pixel2PixelGAN解調技術…46
第五章 結論…49
參考文獻…50
Extended Abstract…53

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