Acoustic methods are commonly used to detect and locate leaks in pipelines, but they often overlook important multimodal characteristics of acoustic waves, limiting their applicability. Based on propagation theories regarding F(1,1) mode signal extraction, a new and easy-to-use method for leak detection and localization in pressurized pipelines is proposed. The F(1,1) mode signals are obtained using accelerometer pairs and mode separation method, which are then used to train detection models and to estimate the time difference of arrival (TDOA) for leak localization. Mode separation empowers the data-driven models with physically meaningful samples, aiming to broaden their applicability. The mode consistency between TDOA and velocity is achieved to ensure accurate leak localization. Experiments in buried water-filled ductile iron pipe (experiment A) and in fuel-filled iron pipe (experiment B) are conducted and the longest test distance reaches 72 m. The results validate that the employment of mode separation notably improves current leak detection and localization methods which primarily rely on original signals. The recognition rates rise about 3 %∼11 %, and the false alarm rates reduce about 1 %∼2 %, even when confronted with pipe junction interferences. Also, the leak localization errors are overall lower, with absolute errors below 2 m and relative errors less than 5 % of the test segment length for most cases.
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