Research On The Modle Of Continuous Motion Measurement Of Railway Subsidence

The stability of railway structure is an important guarantee for the safe operation of trains, railway subsidence affect the normal operation of the various indicators seriously. In view of the shortcomings of the existing methods of subsidence detection, the method of railway subsidence based on multi-sensor information fusion is proposed. The method can accurately detect the changes of the railway, and provide the theoretical support for the detection of the changes in the railway under the moving mode, and provide the basis for the guidance line maintenance and the safety of driving.The subsidence of the railway is changed during a certain period of time, settlement measurement under continuous motion. In the same reference coordinate system, the difference of the space coordinates of each point in the same track line. In the course of a measurement, the measurement of the railway spatial linear, therefore, this paper mainly studies the method of the railway spatial linear. Firstly, the basic principle of the inertial navigation system is discussed in this paper. Through the acceleration of the double integral and attitude matrix updating of the inertial measurement unit(IMU), the displacement is calculated and the results are in line with the actual results; Secondly, the compensation method is proposed for the detection of the inertial measurement unit at low speed, In this method, the displacement of the railway is calculated by using the image information of the visual sensor in motion state. Through the three axis Euler angle of the gyroscope output, the attitude matrix is updated, the displacement direction is described,and the displacement curve is calculated. The simulation results show that the linear error of the railway space is not more than 0.6437mm;And then the important guarantee of the high precision fusion of multi-sensor information, the inertial measurement unit and the calibration method of the vision sensor are improved. After the inertial and visual sensor position in solution, using two axis angle sensor output Euler angle calculation of third axis and three axis rotation angle between the visual and IMU calibration obtained to optimizeweighted fusion. After the inertial and visual sensor position in solution, using two axis angle sensor output Euler angle calculation of third axis and three axis rotation angle between the visual and IMU calibration obtained to optimize weighted fusion, the theoretical and experimental results show that the rotation matrix of the proposed algorithm has higher precision and the maximum error is less than 0.02mm;In the end, the method of measuring the accumulated error of the long distance continuous motion measurement using the extended Kalman filter is studied, the simulation results show that the model can decrease with the increasing of the measurement range and can meet the requirements of the long distance error correction; The experimental platform and design scheme of the railway subsidence are set up, Halcon software is utilized to control camera continuous shooting railway circuit diagram in the state of motion, based on C# language,the data acquisition of inertial measurement unit is realized, and the model is verified by the Euler angles of the inertial measurement unit and the continuous acquisition of the visual sensor and the image input to the program.Movement state, the detection method based on multi-sensor information has higher accuracy than the single sensor detection. The detection of the railway spatial linear information is also more complete, and the existing detection method can not take full advantage of multiple sensor information to realize the advantages of complementary advantages, for the application of this model to the practice, it provides theoretical support for reducing the development costs of rail inspection equipment.