Detection method for microleakage acoustic wave signals in natural gas pipelines based on chaotic oscillators

Abstract To address the issue of the low signal-to-noise ratio in detecting microleakage acoustic wave signals in natural gas pipelines, this paper combines the whale optimization algorithm-based variational mode decomposition (WOA-VMD) algorithm with the Duffing chaotic oscillator to propose a new method for detecting such signals. Firstly, the WOA-VMD algorithm is utilized to adaptively decompose the signal, thereby improving the signal decomposition capability. The cubic spline interpolation algorithm is then introduced to reconstruct the characteristic signal obtained from the decomposition. Subsequently, frequency transformation and array are employed to creatively enhance a Duffing chaotic oscillator, enabling the detection of signals with arbitrary frequencies and initial phases, which is applied to the detection microleakage acoustic wave signals in natural gas pipelines. Finally, through systematic simulation analysis and practical experimental verification, it is concluded that the proposed system exhibits strong anti-noise interference capabilities and can effectively detect multi-frequency and multi-phase signals even with the SNR as low as −76.99 dB.