Drive-by interlayer damage detection methodology for heavy-haul railway bridge using axle box acceleration
Interlayer degradation in heavy-haul railway (HHR) bridges under rising axle loads and transport volumes threatens structural safety. Traditional visual inspection and fixed-sensor structural health monitoring are impractical for large bridge inventories. This paper proposes a drive-by inspection methodology that combines vertical axle box acceleration (ABA) with hybrid filtering for rapid interlayer damage detection in multi-span HHR bridges. The framework introduces a Hilbert-transform-based instantaneous amplitude quartic index (IAQI) to enhance damage localization accuracy. The hybrid filtering integrates bandpass filtering targeting sleeper-passing frequency components to suppress track irregularity effects, and a statistical diagnostic tool to discriminate interlayer damage from sleeper-related driving components. Numerical analyses and a field test on an 18-span, 609.5-m simply supported HHR bridge validate the method. Results demonstrate effective detection under combined beam damage, irregularity, and noise. The field test identified five interlayer damage locations requiring on-site confirmation. The method offers a new strategy to improve inspection efficiency and ensure operational safety of HHR bridges.