A Hybrid Deep Learning Approach: Integrating Short-Time Fourier Transform and Continuous Wavelet Transform for Improved Pipeline Leak Detection
A hybrid deep learning approach was designed that combines deep learning with enhanced short-time Fourier transform (STFT) spectrograms and continuous wavelet transform (CWT) scalograms for pipeline leak detection. Such detection plays a crucial role in ensuring the safety and integrity of fluid tra...
Main Authors: | Muhammad Farooq Siddique, Zahoor Ahmad, Niamat Ullah, Jongmyon Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-09-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/19/8079 |
Similar Items
-
Perception of power quality disturbances using Fourier, Short-Time Fourier, continuous and discrete wavelet transforms
by: M. S. Priyadarshini, et al.
Published: (2024-02-01) -
Leak Detection in Pipelines Using Wavelet Transform and Cepstrum Analysis Methods
by: Priyandoko Gigih, et al.
Published: (2021-06-01) -
Continuous wavelet transform on local fields
by: Ashish Pathak
Published: (2016-06-01) -
A Method for Pipeline Leak Detection Based on Acoustic Imaging and Deep Learning
by: Sajjad Ahmad, et al.
Published: (2022-02-01) -
Pipeline leak diagnosis based on leak-augmented scalograms and deep learning
by: Muhammad Farooq Siddique, et al.
Published: (2023-12-01)