Prediction of rail defect development using parametric bootstrapping modified Weibull equations

The railroad industry has historically used the 2-Parameter Weibull equation to determine the rate of rail fatigue defect occurrences and to forecast the fatigue life of railroad rail. However, the 2-Parameter Weibull equation has significant limitations to include inability to analyze segments of track with limited number of rail defects. These limitations are addressed through modification of the traditional 2-Parameter Weibull equation with a novel approach developed from Parametric Bootstrapping. The result is a Parametric Bootstrapping modified Weibull (PBW) forecasting approach. This methodology is applied to rail segments with insufficient numbers of defects to allow for appropriate defect forecasting analysis. Thus, the PBW method provides reasonable estimates of the rate of defects for track segments that have little or no prior defect history. This approach allows for more track to be analyzed and forecasts the probability of rail defect occurrence as a function of key parameters such as cumulative traffic over the rail. A validation of the proposed methodology was performed. Comparison of the output results of over 300,000 track segments with over 200,000 rail defects showed a major improvement in percentage of segments with reasonable Weibull parameters (alpha and beta). This percentage increased from 11% of segments using traditional Weibull analysis to 77% of segments using Parametric Bootstrap modified Weibull approach. These results show that the PBW Analysis approach introduced here offers a more accurate and effective approach to determining the probability of developing future rail defects. This provides a benefit to railroads in planning maintenance of their expensive rail assets.

Automatic Judgment of Ultrasonic Detection for Solid Axle Inlaid Part

Ultrasonic detection is the most effective nondestructive method for axle inlaid part, which has high efficiency and wide coverage. In the process of rail vehicle running, the influence of the external environment and the interaction between wheel and axle cause uneven distribution of stress concentration and with fretting corrosion, which lead to the generation of fatigue crack, otherwise, the waveform of ultrasonic detection is complex, because the energy of non-defect is too high to identify the defect. In view of this phenomenon, the ultrasonic echo data is analyzed by wavelet transform method to extract the defect characteristic, which is used for automatically judgment. The results show that the fatigue defect can be identified effectively by using the defect characteristic that extracted by wavelet transform method.

Experimental studies of the influence of technological heredity on the damage to wheels of high hardness

The influence of technological heredity on the interaction of the wheel and rail is considered. The state of the surface of the samples for the presence of contactfatigue defects is estimated. A relationship is established between the maximum height of waviness on the surface of the roller and the rate of damage to its surface. The dependence of the number of loading cycles of the rollers on the height of the waviness and the distribution of the run of the wheels of increased hardness between the turnings are constructed, which is consistent with experimental data. Keywords wheel, rails, contact-fatigue processes, technological heredity, wear, fatigue defect, wheel of increased hardness. [email protected]