Study on infrasonic leakage monitoring and signal processing for product oil pipeline

Objective With the total length of oil and gas transmission pipelines increasing due to booming development, pipeline leakage monitoring has emerged as one of the critical technologies to ensure the safe and stable operation of these pipelines. Infrasonic monitoring has garnered significant attention due to its high sensitivity, high positioning accuracy, and low maintenance costs. However, its engineering application in product oil pipelines requires further discussion. Methods Based on the basic principle of infrasonic monitoring, an experimental setup for liquid pipeline leakage monitoring was independently constructed, aimed to analyze the characteristics of signals acquired by infrasonic sensors across different leak hole sizes, pipe pressures, and distances from these sensors to the leak points. The signal processing effects of wavelet transforms at 1–9 layers on the db and sym wavelet bases were analyzed. Subsequently, a random forest classification model was established, incorporating fifteen time-domain features and four frequency-domain features of the signals. The model parameters were optimized, using the Area Under Curve (AUC) of the Receiver Operating Characteristic (ROC) curve as an objective function. Furthermore, the experimental data were processed and classified, utilizing the method based on Wavelet Transform-Random Forest (WT-RF). Results The proposed approach was applied to a product oil transmission pipeline section of PipeChina South China Pipeline Co. Ltd., resulting in the following findings. Following an 8-layerdecomposition on the sym2 wavelet basis, the infrasound signals exhibited distinct recognizable characteristics in both the time and frequency domains. The random forest identification model, supported by positioning information, showcased a zero false alarm rate and missing alarm rate under leakage conditions of the production pipeline. At a 91 km monitoring interval along the product oil pipeline, the positioning error was about 800 m, facilitating reliable monitoring up to a leak rate of 0.001 6 m3/s, with the minimum detectable leak rate recorded at 0.000 46 m3/s. Conclusion This study showcases the favorable experimental efficacy of infrasonic leakage monitoring technology for product oil pipelines, emphasizing extremely low false alarm rates and missing alarm rates, alongside small positioning errors. The findings of this study offer valuable technical support and serve as a reference for the application of this technology in product oil pipelines.