| Aiming at the difficulties of urban underground pipeline positioning and the high price of pipeline locator,this paper designs a pipeline positioning system combining low-cost microinertial unit(MMU),mileage wheel and photoelectric speed sensor for urban underground pipeline positioning.In order to reduce the influence of the measurement information containing isolated outliers generated by the photoelectric speed sensor due to the unstable speed measurement on the pipeline positioning accuracy in the working process of the pipeline positioning system,a robust Kalman based on the maximum correlation entropy and the M estimation criterion is proposed.Filtering to increase the robustness of the system.At the same time,in order to reduce the influence of speckled outlier measurement information generated by the slipping of the mileage wheel during the pipeline positioning system on the pipeline positioning accuracy,an adaptive information distribution factor algorithm based on the fault detection function is proposed to increase the pipeline positioning The efficiency of system fault detection,thereby further improving the system’s tolerance.Design and implement the MIMU/mileage wheel/photoelectric speed sensor data fusion algorithm,and build the pipeline locator hardware for experimental verification.The main work content can be summarized as:1.Analyze the working principle of the existing pipeline locator and the advantages and disadvantages of the sensors carried by the pipeline locator.The pipeline positioning scheme of MIMU/mileage wheel/photoelectric speed sensor multi-sensor combined positioning is determined.2.Derive the error equations of MIMU,mileage wheel and photoelectric speed sensor,analyze the source of the error,and give the corresponding error compensation method.3.The federated filtering algorithm is used to perform information fusion on MIMU/mileage wheel/photoelectric speed sensor.In the federated filtering algorithm,the influence of the information distribution factor on the failure of the sub-filter on the overall filtering is analyzed.4.Aiming at the measurement information containing isolated outliers generated by the photoelectric speed sensor due to the instability of speed measurement,a robust Kalman filter based on the maximum correlation entropy and the M estimation criterion is proposed to increase the robustness of the system.Aiming at the measurement information containing speckled outliers generated by the mileage wheel slip,an adaptive information allocation factor algorithm based on the fault detection function is proposed to improve the efficiency of fault detection in the sub-filter,and the speckled outliers generated by the mileage wheel slip are proposed.Information is isolated in time to reduce its impact on the system’s global estimation accuracy.5.Select the appropriate model of MIMU,mileage wheel and photoelectric speed sensor,design the corresponding peripheral circuit,and build the corresponding hardware platform.to write the corresponding data solving program.And conduct physical experiments to verify the accuracy of the pipeline positioning system. |
