Master'sOpen Access

Doğrudan algılama bir fiber optik dağıtık akustik sensörün geliştirilmesi ve karakterizasyonu

2018
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Advisor: Prof. Dr. Ekmel Özbay ; Doç. Dr. İbrahim Tuna Özdür

Abstract (EN)

Phase-sensitive optical time domain reflectometer (phi-OTDR) based distributed acoustic sensor (DAS) systems have attracted increasing attention in recent years due to their remarkable advantages in a wide range of industrial and military applications such as health monitoring and security of civil infrastructures, railways, oil and gas pipelines, borders, and so on. They measure vibrations and detect perturbations along a section of fiber. Different approaches have been adopted to realize the phi-OTDR systems and process the data from these sensors. In this thesis, a direct detection DAS based on phi-OTDR architecture with long sensing range and high signal-to-noise ratio (SNR) is demonstrated. Testing and characterization of critical system components is conducted before integrating them into the system. The results of laboratory tests are presented, in which the detected traces are successively analyzed in order to localize and investigate the perturbation events along the test fi bers. The field tests are demonstrated with different external events such as digging, walking, and motor vibration. Considering the random nature of Rayleigh backscattered light and fading effect encountered in these tests, a new performance metric, which is Mean SNR, is proposed for assessing and comparing the system performances. Besides, statistical characteristics of the SNR of the vibration events in different distances for both laboratory tests and fi eld tests is experimentally measured. The photon statistics of Rayleigh backscattered signal in a phi-OTDR based fi ber sensor in the presence of ampli fied spontaneous emission noise is theoretically modeled and experimentally demonstrated, as well.

Author

Dr. Faruk Uyar

How to Cite

Faruk Uyar (Master Thesis). Doğrudan algılama bir fiber optik dağıtık akustik sensörün geliştirilmesi ve karakterizasyonu, 2018, Bilkent University.

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