Research on Dynamic Detection Data Mileage Deviation Correction Algorithm Based on Track Static Detection Data
During dynamic detection of track geometry state,the dynamic errors of photoelectric encoder,wheel spin and slip and the errors written into the detection system by the operator will inevitably cause mileage deviations in the de-tection data,resulting in waveform misalignment.Direct use of the data with mileage deviations will affect the evaluation accuracy of track quality state and the reliability of line status deterioration trend analysis,unable to ensure the effect of on-site maintenance of the line.In this paper,a dynamic detection data mileage deviation correction method was pro-posed based on static detection data,along with a principal point iteration correction(PPIC)algorithm.In the experi-ment,the PPIC algorithm and the existing most stable segment similar waveform matching(SSWM)algorithm were used to process simulated data and measured data of high-speed railway.The results show that,the PPIC algorithm,after cor-rection,significantly improves the consistency of the dynamic and static detection waveforms,the mean difference and measurement uncertainty of dynamic and static detection irregularity,as well as the correlation coefficient of dynamic and static detection data.The correction effect of the PPIC algorithm is better than that of SSWM.The mileage deviation cor-rection accuracy of the PPIC algorithm is better than a static detection interval(0.125 m),which can effectively correct the mileage deviation of dynamic detection data.
high-speed railwaytrack detectiontrack alignment and longitudinal levelmileage deviation
万方数据
维普
