Study on a High-Pressure Pipeline Micro-Leakage Detection Method Based on Background-Oriented Schlieren Measurement and Feature Matching

Online detection of micro-leakage in complex high-pressure gas pipeline networks is difficult to achieve using conventional methods. A high-pressure pipeline micro-leakage detection method based on background-oriented schlieren measurement and feature matching was proposed in this study to address this issue. Through the BOS measurement, the density distribution of the leakage fields was reconstructed through cross-correlation calculation and Poisson equation solving, which was further compared with numerical simulation results under specific operating conditions. The morphological characteristics of the jet field at different leakage pressures were revealed by comparing the density fields from different experimental conditions. Subsequently, the displacement field data were compressed into one-dimensional feature representations for structure-oriented matching of leakage-field characteristics, with temporal smoothing and a dual-threshold hysteresis strategy incorporated to improve matching robustness. The results show that the error in the peak density remains below 10%, which indicates good consistency between the background-oriented schlieren measurements and the numerical simulations. Meanwhile, the one-dimensional feature curve accelerates computation while retaining the dominant characteristics of the leakage field. The proposed framework achieves an area under the ROC curve of 0.992 and an average precision of 0.998. At the selected threshold of 0.650, the overall evaluation metric reaches 0.972, reflecting a favorable balance between sensitivity and reliability. Furthermore, the temporal stabilization strategy improves alarm continuity and suppresses chattering during detection.