Algorithms and Instrument for Rapid Detection of Rail Surface Defects and Vertical Short-Wave Irregularities Based on FOG and Odometer

Defects and vertical short-wave irregularities significantly influence the maintenance of the railway tracks and the train safety, and hence, they need to be detected and eliminated in the early stages of formation. We studied the principles and algorithms to detect the defects and to measure the vertical short-wave irregularities by using a fiber optical gyroscope and an odometer, and the associated software was also developed. The principles of deformation index, namely, the ratio of angular rate to velocity and the method to determine the threshold of defects detection, are expatiated. The influence of the transfer function in measuring the vertical irregularities has long been a tough issue. The relation between the characteristics of deformation index and the wavelength of irregularities is studied by converting the deformation index from the time domain to the spatial domain. The post-processing module utilizes the results of the spectrum analysis of the deformation index to determine the wavelength of the track irregularities and eliminate the influence of the transfer function. To improve the accuracy of the calculation results, we analyzed the characteristics of the output of the gyroscope and the odometer and designed a series of targeted error-elimination methods. The forward and reverse dead-reckoning method is utilized to reduce the error accumulation, especially a high frequency noise when calculating the magnitude of the vertical short-wave irregularities. The experimental results show that the repeatability is 0.038 mm when the chord length is 1 m and 0.65 mm when the chord length is 10 m. The accuracy is 0.05 mm when compared with the results obtained using a ruler of 1 m. The moving speed of the instrument was approximately 0.6-1.2 m/s during the experiment. Both the accuracy and the efficiency can fulfill the requirements for the measurement of the short-wave irregularities.