Citation

Jabidin, Hafiz Zulhazmi (2025) Investigation of combined moving average and moving differential algorithm for distributed acoustic sensing. Masters thesis, Multimedia University.

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Abstract

Distributed Acoustic Sensing (DAS) is widely used in various applications, such as oil and gas exploration, perimeter security, earthquake monitoring, and railway surveillance. The DAS system detects small variations in the backscattered light within the optical fibre because any acoustic or vibrational energy induces strain on the fibre, which alters the refractive index. The small variation in the backscattered light pattern can then be analysed, allowing us to localise and quantify the acoustic or vibrational events throughout the fibre’s length. The analysis was done using digital signal processing (DSP). In this study, moving average and moving differential (MAMD) methods were specifically utilised and optimised to achieve the best signal-tonoise ratio (SNR) for disturbances characterised by multiple frequency components. The DAS system design uses phase-sensitive optical time domain reflectometry (ΦOTDR), employing direct and coherent detection systems. The experiment was conducted in a laboratory setting, where a wireless speaker simulated a disturbance with multiple frequency components. Results indicate that the DAS system detected the simulated disturbances on the fibre under test (FUT). To the best of our knowledge, this study represents the first attempt to optimise the MA-MD algorithm for detecting mixed-frequency acoustic signals. Optimising the MA-MD method demonstrated that the optimal SNR depends on specific window and interval size ranges. The maximum SNR achieved by the coherent detection DAS is 7.93 dB when the window and interval size are set to 10 and 110, respectively. Meanwhile, the maximum SNR for the direct detection DAS is 7.53 dB when the window and interval size are set to 2 and 5, respectively. When optimised, the MA-MD enhanced the SNR by a minimum of 0.1 dB and a maximum of 0.4 dB compared to the standard and normalised differential methods in both detection schemes. This study demonstrates how optimising the MAMD method enhances the DAS system SNR performance for more effective detection of disturbance with multiple frequency components, providing insights for real-world applications. In addition, the study also provides valuable insight into SNR performance comparison between direct and coherent detection DAS.

Item Type:	Thesis (Masters)
Additional Information:	Call No.: QA76.58 .H34 2025
Uncontrolled Keywords:	Parallel algorithms
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75-76.95 Calculating machines
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	19 Jan 2026 03:43
Last Modified:	19 Jan 2026 03:43
URII:	http://shdl.mmu.edu.my/id/eprint/15187

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