Dynamic detection and evaluation of wheel flats in heavy-haul railway wheelsets using wayside monitoring systems

In recent years, heavy-haul railways have become a critical direction for freight transport in China, with wheel flats in wheelsets posing significant threats to operational safety and infrastructure integrity. Traditional detection methods (e.g., manual inspection, TPDS) suffer from low efficiency or limited accuracy in characterizing flat features. To address this, this study develops a rigid-flexible coupling dynamic model for C80 wagons with K6 bogies, uniquely integrated with field data from the Truck Operation Detection System (TODS) to bridge simulation and engineering application gaps. Focusing on wheel-rail force responses under wheel flat conditions, we establish a quantitative mapping relationship between flat length, vehicle speed, and impact force through polynomial fitting of simulation data (10-80 km/h for empty/loaded vehicles). To validate feasibility, a 56-channel wayside monitoring system (TODS) is installed on a heavy-haul railway, calibrated via hydraulic loading to ensure measurement accuracy. Field tests (80,541 vehicles monitored) confirm that TODS can infer flat length from detected impact forces, with results consistent with TPDS alarms but offering finer characterization of flat dimensions. This work provides a practical solution for real-time wheel flat detection, enhancing maintenance efficiency and safety in heavy-haul operations.