An analysis of detectable leakage rate for oil pipelines based on acoustic wave method

Abstract

Oil pipeline leakage will not only cause economic losses, but also pollute the environment, so the leakage detection of pipelines is very important. The acoustic wave method is widely used in pipeline leak detection, and the leak acoustic signal collected by the acoustic wave sensor often contains a lot of noise, which makes it impossible to accurately determine the inflection point of the signal curve and reduces the accuracy of pipeline leak detection. This paper proposes a denoising algorithm based on mutual information optimization complete ensemble empirical mode decomposition with adaptive noise combined with cross-spectral analysis. Compared with other methods, this method can accurately select the effective intrinsic modal function for signal reconstruction, the denoising effect is more obvious, and the original information is preserved to a greater extent. Acoustic waves are attenuated during the propagation process, and will be affected by factors such as pipe connection ports and elbows, making it impossible to accurately determine the amplitude of acoustic waves around the pipeline. According to the propagation characteristics of acoustic waves and various factors that affect the propagation of acoustic waves, this paper establishes a model for calculating the amplitude of acoustic waves, which can accurately determine the amplitude of acoustic waves everywhere in the pipeline. Finally, according to the model, the relationship between pipeline characteristics and detectable leakage rate is analysed. Field experiments show that the proposed model is accurate and the denoising algorithm is efficient. The minimum detectable leakage rate of the oil pipeline can reach 0.43% when the acoustic wave method is used for leak detection.