Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Article Citation - WoS: 9Citation - Scopus: 12Intensity and Phase Stacked Analysis of a 40-Otdr System Using Deep Transfer Learning and Recurrent Neural Networks(Optica Publishing Group, 2023) Kayan, Ceyhun Efe; Gümüş, Abdurrahman; Yüksel Aldoğan, Kıvılcım; Yüksel Aldoğan, Kıvılcım; Gümüş, Abdurrahman; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyDistributed acoustic sensors (DAS) are effective apparatuses that are widely used in many application areas for recording signals of various events with very high spatial resolution along optical fibers. To properly detect and recognize the recorded events, advanced signal processing algorithms with high computational demands are crucial. Convolutional neural networks (CNNs) are highly capable tools to extract spatial information and are suitable for event recognition applications in DAS. Long short-term memory (LSTM) is an effective instrument to process sequential data. In this study, a two-stage feature extraction methodology that combines the capabilities of these neural network architectures with transfer learning is proposed to classify vibrations applied to an optical fiber by a piezoelectric transducer. First, the differential amplitude and phase information is extracted from the phasesensitive optical time domain reflectometer (40-OTDR) recordings and stored in a spatiotemporal data matrix. Then, a state-of-the-art pre-trained CNN without dense layers is used as a feature extractor in the first stage. In the second stage, LSTMs are used to further analyze the features extracted by the CNN. Finally, a dense layer is used to classify the extracted features. To observe the effect of different CNN architectures, the proposed model is tested with five state-of-the-art pre-trained models (VGG-16, ResNet-50, DenseNet-121, MobileNet, and Inception-v3). The results show that using the VGG-16 architecture in the proposed framework manages to obtain a 100% classification accuracy in 50 trainings and got the best results on the 40-OTDR dataset. The results of this study indicate that pre-trained CNNs combined with LSTM are very suitable to analyze differential amplitude and phase information represented in a spatiotemporal data matrix, which is promising for event recognition operations in DAS applications. (c) 2023 Optica Publishing GroupArticle Citation - WoS: 3Citation - Scopus: 3Current Sensing Using a Phase-Sensitive Optical Time Domain Reflectometer: Feasibility Study(Elsevier, 2022) Wuilpart, Marc; Şirin, Şamil; Yüksel Aldoğan, Kıvılcım; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyA novel method for distributed current sensing using an FBG-assisted Phase-OTDR with Mach-Zehnder Interferometer is proposed. The detrimental effect of the intrinsic linear birefringence of the sensing fiber is solved by calibration. An FBG pair is written at the two ends of the spun fiber coil to eliminate phase fading and increase the measurement accuracy. A simulation tool was developed to reveal the feasibility of the approach by investigating the impact of the detector noise as well as the effects of bending- and FBG-induced linear birefringence on the sensing performance.Conference Object Ф-otdr Sorgulayıcı Tabanlı Titreşim Algılayıcılar için Simülasyon Aracı Geliştirilmesi(Institute of Electrical and Electronics Engineers Inc., 2019) Şirin, Şamil; Yüksel Aldoğan, Kıvılcım; Yüksel Aldoğan, Kıvılcım; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyBu çalışmada, faza duyarlı zaman bölgesinde optik yansıtıcı ünitesi tarafından sorgulanan fiber optik titreşim sensörü simülasyon aracı geliştirilmesi amacıyla, literatürde yakın zamanda önerilen modüler bir yaklaşım uygulanmıştır. Geliştirilen model kullanılarak, demodüle edilen faz bilgisi üzerindeki faz sönümleme etkisi incelenmiştir.