چارچوبی برای تشخیص تنش و ارزیابی ناحیه گسل با استفاده از داده‌های حسگر توزیع‌شده آکوستیکی نوری (DAS)

The current study offers a useful application procedure for stress extraction and analysis from Distributed Acoustic Sensing (DAS) data. The key highlight of this research work is the direct application of DAS data to make quantitative assessments about localized stress values and to investigate the effectiveness of human activities (construction and traffic) on faults—most importantly, applying these techniques has been unexplored in past research works on DAS [1]. During the data processing section, the raw data from the DAS (intensity of Ray-leigh backscattering) undergoes preprocessing and trending. Later on, applying the Hilbert signal analysis technique, these signals are demodulated and unambiguously phased to extract phase change values. Then again, after applying strain (or strain rate), these values are transformed into stress values using the corresponding shear moduli values of the optical fiber [3]. The results show that the stress values triggered by construction and traffic activity are distinguishable and can be measured; besides that, these values are adjustable based on distance and geological conditions. These stress values can be successfully traced to locate susceptible faults and danger zones to act as indicators for implementing geological and urban planning techniques. The current application procedure has great potential to be fully operative to implement continuous monitoring techniques in various environments.