Research on hidden damage detection principle and optimization in moving carriages based on enhanced infrared imaging method (<italic>invited</italic>)

ObjectiveIn current coal transportation, cracks in parts such as railway carriage pillars are easily covered by coal dust or blocking glue, which are difficult to identify with the naked eye. Traditional manual detection methods are inefficient and inaccurate, while photothermal infrared enhanced imaging technology is suitable for hidden damage detection of moving carriages due to its advantages of long-distance, large-range and non-contact. However, the infrared detection mechanism for hidden damage of carriages in motion is unclear, and there is a lack of determined detection process parameters. This study aims to solve these problems and develop a feasible and optimized hidden damage detection method for moving carriages.MethodsA physical model of railway carriages was constructed to simulate the infrared imaging detection effect of hidden damage in moving carriages under photothermal pulse excitation. Taking carriage pillars as the research object, the changes in the surface radiation field after photothermal excitation were studied under conditions such as photothermal radiation field and air convection, considering parameters including excitation time, defect area ratio, defect depth, carriage moving speed, relative distance between the detector and the carriage, and the presence of covering materials. The relationship between the temperature field and time was analyzed, and the peak radiation temperature and temperature difference at defects were studied to verify the feasibility of hidden damage detection based on photothermal pulse enhanced infrared imaging. Meanwhile, an experimental platform for photothermal infrared enhancement was built to verify the simulation results and the proposed method. The enhanced imaging effect of pillar defects under different conditions was studied, and the quality of the formed images was analyzed using indicators such as information entropy, contrast, clarity and edge strength.Results and DiscussionsThe simulation results show that the temperature of the pillar surface and defect center increases linearly with time, and the pillar surface temperature is always higher than the defect center temperature. For key parameters: when the defect depth increases by 0.01 m, the temperature difference increases by an average of 0.068 K; when the defect area ratio decreases from 1% to 0.1%, the temperature difference between the defect surface and pillar surface decreases from 0.493 K to 0.376 K; when the moving speed increases from1.5 m/s to 5.5 m/s, the temperature difference decreases from 0.895 K to 0.326 K; when the detection distance increases from 1 m to 1.6 m, the temperature difference decreases from 0.895 K to 0.559 K. The optimal detection conditions are determined as: moving speed ≤3.5 m/s, relative distance ≤1.3 m, and priority detection of defects with depth ≥0.02 m and area ratio ≥0.2%. Experimental verification shows that defects with area ratio greater than 0.8% can be continuously detected, while those less than 0.15% are difficult to be stably identified. Coverings such as foam rubber, coal ash and sand will interfere with the detection effect, which can be mitigated by increasing the excitation power. The radiation characteristic changes of hidden damage areas obtained by simulation are in good consistency with the experimental results.ConclusionsThe proposed hidden damage detection method for moving carriages based on photothermal infrared imaging is feasible, with the advantages of high efficiency, high accuracy and low cost. It can be applied to the actual hidden damage detection of moving carriages and can also be extended to the internal defect detection of other moving plates. The research results provide a reliable technical means for solving the problem of hidden damage detection of moving carriages in coal transportation, and have important promotion and application value.