Abstract:

Aiming at the problem that long-term aging makes heating pipelines prone to leakage under internal or external forces， and that traditional pulse-based methods suffer large errors under electromagnetic interference， temperature variation， and soil-moisture conditions， we propose a multi-aperture leak-detection method based on acoustic signals. Install acceleration sensors in the heating pipeline network in an axisymmetric manner to collect real-time sound signals carrying leaked sound waves. By using wavelet packet transform to decompose the collected acoustic signals， useful feature information for leak detection can be extracted and used as input for the Duffing oscillator function. By adjusting the phase of the built-in driving force to match the phase of the acoustic signal to be detected， the Duffing oscillator can be excited to a large-scale periodic state， which helps to distinguish weak acoustic signal features in noisy backgrounds and achieve more efficient multi aperture leak detection in heating pipelines network. The experimental results show that the algorithm can accurately distinguish and detect leaks in the heating pipeline network of all apertures based on the characteristics of sound waves， and can control the time within 0.32 ms when detecting leaks with an aperture of 2 mm. This indicates that the method proposed in this paper can detect multi aperture leaks in the heating pipeline network in a timely manner， ensuring the stable operation of the heating pipeline network.

Key words: acoustic signal, heating pipeline network, acceleration sensors, wavelet packet transform, Duffing oscillator, leak detection