FOG Applied To Track Smoothness Detection

The train driving high speed and safe must have a highly comfort to support it,in order to ensure that the track is highly smooth,we need to have corresponding track detection technology and checking instrument to check the track in the track laying,fine regulation and operation,guaranteeing each index of the track within the range of limit difference.The purpose of this paper is to rely on the technology of fiber optic gyro and traditional measuring instruments to solve the high-speed railway,passenger dedicated line and sky train fine regulation and surveying the track smoothness,the next period,it can be extended to check and repair the integrated solutions of existing lines.This paper first analyzes the domestic and foreign track irregularity detection technique at present,summed up the track irregularity inspection system to measure several elements;according to the characteristics and functions of each measurement elements,respectively formulate the sensor measurement scheme and list the sensors;on the basis,according to the function of each sensor device,I design the program block diagram of the data acquisition system to test the track smoothness,and studied emphatically the fiber optical gyro angle measurement system which was used to test track ride.Based on the working principle,structure and signal transmission process of fog,analysied the reason which maybe cause the output error of the gyroscope and listed several common error indexes.To deal with the errors within the fiber optic gyro output data used Pauta rule,smoothing filter and low-pass filter,and evaluated the filtering effect by comparing the data distribution before and after the filtering.Because the image cant reflect the gain effect of filtering,we introduce the Allan variance analysis method to identify and quantify the random error term of gyroscope output data.The quantized random error value can express the gain effect of the filter intuitively.After pre processing,output error of gyroscope output is partly eliminated and partly reduced,but the compensation for error of gyroscope output data needs further processing.In this paper,established time series model to realize the real-time compensation of errors,then introduced Kalman filtering to deal with the error within the output data in motion state,because Kalman filter has the characteristics of no time delay,first prediction and re measurement.Then the Kalman filter is combined with the ARMA model which is used for the dynamic measurement of the whole system.