基于捷联惯导的管道地理坐标内检测关键技术的研究
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摘要
管道运输是经济的血脉,管道的安全对经济的发展至关重要。定期进行管道安全的检测与维护是防止重大事故,保证管道安全的主要方法。管道内检测是一种国际通行的检测方法,基于内检测的管道地理坐标测量可以检测整个管道的地理位置信息,并为检出的管道缺陷提供具体位置,对管道检测具有重要意义。为实现该技术,论文对若干关键技术问题进行研究,进行了以下工作并得出相关的结论：
分析了内检测条件下各种定位方法的可行性,将捷联惯导系统(Strapdown Inertial Navigation System, SINS)应用到管道地理坐标测量中,实现了在封闭环境下对整个管道地理坐标的测量。根据测量条件,选择微机电系统(Micro-Electro-Mechanical Systems, MEMS)型器件作为惯性测量单元(Inertial Measurement Unit, IMU)。分析了IMU输出信号的误差源,建立了输出信号的误差模型。动态信号误差远大于静态信号,标准差为静态信号的9倍多,研究信号预处理算法解决动态信号的噪声问题,利用五点三次平滑算法去除动态信号的高频误差,利用阈值去噪法去除动态信号的脉冲噪声。实验结果表明,利用预处理算法可以将动态信号的标准差降低为原来的十分之一,不影响其中的有用信号成分。
分析了捷联惯导算法的计算原理,利用里程轮速度校正kalman滤波估计方法解决算法的误差发散问题。采用矩阵分解方法保证kalman滤波方差矩阵的非负定性,最终解决迭代计算引起的发散问题。设计了模拟地理坐标测量系统的实验平台。实验结果表明,里程校正的kalman滤波方法解决了惯导算法的误差发散问题,在使用较低精度的惯性测量器件,且测量环境比较恶劣的情况下,每100m距离间隔的管道测量的绝对误差为5m。论文设计的方法对测量系统具有一定的实用性。
分析了惯性测量单元的初始对准原理,针对对准角度过大引起的非线性问题,采用先进行粗对准,再进行精对准的方法,将精对准的误差角限定为小角度范围；在精对准中,利用Unscented粒子滤波算法(Unsented particle filter,UPF)方法解决非线性模型的滤波问题。仿真计算结果表明,采用论文的初始对准方法进行方位对准的误差角可以达到33角秒,对准精度高于Unsented kalman滤波(Unsented kalman filter, UKF)和扩展kalman滤波(Extended Kalman Filter, EKF),计算时间略长于这两种算法。
针对计算的管道轨迹在终止点上偏离实际位置的问题,选择前后双向kalman滑动滤波的终止点校正算法,对所有测量信息进行平滑估计,将实际的终止点位置引入定位计算中。实验结果表明,经终止点校正后,计算的终止点与实际重合,提高定位精度到每100m相对误差1.8%,该方法具有一定的实用性。
Pipeline transportation is the vein of the economy, and the safety of the pipeline is vital to economic development. Periodic testing and maintenance of the pipeline safety is the main method to prevent major accidents and ensure pipeline safety. Inner inspection is an internationally accepted method, pipeline geographic coordinate measurement based on inner inspection can provide the specific location of the pipeline, complete the test information of the pipeline, which has great importance to pipeline's testing. To realize the technology, this paper study some key technical problems, it performs the following work and receives relevant conclusions:
After the detailed analysis on the feasibility of various positioning methods at the inner inspected condition, it applies the SINS technique to the pipeline's geographic measurement, and it realizes the whole pipeline geographic coordinate measurement in a closed environment. It selects the MEMS devices as the IMU according to the measurement conditions. It establishes the error model after the analysis on the error source of the IMU's output signal. Dynamic signal error is much larger than the static signal, and its standard deviation is9times more than the static signal's. Study the signal preprocessing algorithm to solve the dynamic signal noise problem. It utilizes the five points three times smoothing algorithm to remove high-frequency dynamic signal error, and the threshold method to remove impulse noise dynamic signal. Experimental results show that through the preprocessing algorithm the standard deviation of the dynamic signal is reduced to one-tenth of the original, and it does not affect one of the useful signal components.
After analysis on the calculation principle of SINS algorithm, it utilizes the odometer speed correction kalman filtering estimation method to solve the algorithm's calculated error accumulating problem. After analysis the algorithm of the kalman filtering, it utilizes the matrix factorization method to ensure the covariance matrix of non-negative qualitative, and finally solves the divergence problem caused by the iterative calculating. The paper designs the experimental platform simulated geographic coordinate measurement system. The experimental results show that the odometer correction kalman filtering method resolves the SINS error accumulated problem. In the case of using the lower precision inertial measurement devices and the measurement of the environment is relatively harsh, the measuring absolute error is5m every100meters distance of the pipeline. Paper design of the measurement system has a certain practicality.
After analysis on the initial alignment principle of the inertial measurement unit, the paper utilizes the method that first process the coarse alignment then the fine alignment, it resolve the nonlinear problem caused by the too large alignment angle, as the fine alignment error angle is limited to a small range of angle; it utilizes the UPF to resolve the nonlinear model filtering problem in the fine alignment. The simulation results show that the alignment error angle of orientation can reach33second of arc through the method mentioned above. Alignment accuracy is higher than the UKF and the EKF, and the computation time is slightly longer than the two algorithms.
The paper selects the before and after-two directions kalman smooth filtering termination point correction algorithm, that utilizes the offline features of the positioning calculation to resolve the calculated trajectory of the pipeline on the termination point deviating from the actual location problem. The algorithm smoothed estimates of all the measurement information, the actual termination point position is introduced into the positioning calculation. Experimental results show that the termination calculation point is coincident with the actual point after the algorithm. It improves positioning accuracy to a relative error of1.8%per100m, and the method has a certain practicality.
分析了内检测条件下各种定位方法的可行性,将捷联惯导系统(Strapdown Inertial Navigation System, SINS)应用到管道地理坐标测量中,实现了在封闭环境下对整个管道地理坐标的测量。根据测量条件,选择微机电系统(Micro-Electro-Mechanical Systems, MEMS)型器件作为惯性测量单元(Inertial Measurement Unit, IMU)。分析了IMU输出信号的误差源,建立了输出信号的误差模型。动态信号误差远大于静态信号,标准差为静态信号的9倍多,研究信号预处理算法解决动态信号的噪声问题,利用五点三次平滑算法去除动态信号的高频误差,利用阈值去噪法去除动态信号的脉冲噪声。实验结果表明,利用预处理算法可以将动态信号的标准差降低为原来的十分之一,不影响其中的有用信号成分。
分析了捷联惯导算法的计算原理,利用里程轮速度校正kalman滤波估计方法解决算法的误差发散问题。采用矩阵分解方法保证kalman滤波方差矩阵的非负定性,最终解决迭代计算引起的发散问题。设计了模拟地理坐标测量系统的实验平台。实验结果表明,里程校正的kalman滤波方法解决了惯导算法的误差发散问题,在使用较低精度的惯性测量器件,且测量环境比较恶劣的情况下,每100m距离间隔的管道测量的绝对误差为5m。论文设计的方法对测量系统具有一定的实用性。
分析了惯性测量单元的初始对准原理,针对对准角度过大引起的非线性问题,采用先进行粗对准,再进行精对准的方法,将精对准的误差角限定为小角度范围；在精对准中,利用Unscented粒子滤波算法(Unsented particle filter,UPF)方法解决非线性模型的滤波问题。仿真计算结果表明,采用论文的初始对准方法进行方位对准的误差角可以达到33角秒,对准精度高于Unsented kalman滤波(Unsented kalman filter, UKF)和扩展kalman滤波(Extended Kalman Filter, EKF),计算时间略长于这两种算法。
针对计算的管道轨迹在终止点上偏离实际位置的问题,选择前后双向kalman滑动滤波的终止点校正算法,对所有测量信息进行平滑估计,将实际的终止点位置引入定位计算中。实验结果表明,经终止点校正后,计算的终止点与实际重合,提高定位精度到每100m相对误差1.8%,该方法具有一定的实用性。
Pipeline transportation is the vein of the economy, and the safety of the pipeline is vital to economic development. Periodic testing and maintenance of the pipeline safety is the main method to prevent major accidents and ensure pipeline safety. Inner inspection is an internationally accepted method, pipeline geographic coordinate measurement based on inner inspection can provide the specific location of the pipeline, complete the test information of the pipeline, which has great importance to pipeline's testing. To realize the technology, this paper study some key technical problems, it performs the following work and receives relevant conclusions:
After the detailed analysis on the feasibility of various positioning methods at the inner inspected condition, it applies the SINS technique to the pipeline's geographic measurement, and it realizes the whole pipeline geographic coordinate measurement in a closed environment. It selects the MEMS devices as the IMU according to the measurement conditions. It establishes the error model after the analysis on the error source of the IMU's output signal. Dynamic signal error is much larger than the static signal, and its standard deviation is9times more than the static signal's. Study the signal preprocessing algorithm to solve the dynamic signal noise problem. It utilizes the five points three times smoothing algorithm to remove high-frequency dynamic signal error, and the threshold method to remove impulse noise dynamic signal. Experimental results show that through the preprocessing algorithm the standard deviation of the dynamic signal is reduced to one-tenth of the original, and it does not affect one of the useful signal components.
After analysis on the calculation principle of SINS algorithm, it utilizes the odometer speed correction kalman filtering estimation method to solve the algorithm's calculated error accumulating problem. After analysis the algorithm of the kalman filtering, it utilizes the matrix factorization method to ensure the covariance matrix of non-negative qualitative, and finally solves the divergence problem caused by the iterative calculating. The paper designs the experimental platform simulated geographic coordinate measurement system. The experimental results show that the odometer correction kalman filtering method resolves the SINS error accumulated problem. In the case of using the lower precision inertial measurement devices and the measurement of the environment is relatively harsh, the measuring absolute error is5m every100meters distance of the pipeline. Paper design of the measurement system has a certain practicality.
After analysis on the initial alignment principle of the inertial measurement unit, the paper utilizes the method that first process the coarse alignment then the fine alignment, it resolve the nonlinear problem caused by the too large alignment angle, as the fine alignment error angle is limited to a small range of angle; it utilizes the UPF to resolve the nonlinear model filtering problem in the fine alignment. The simulation results show that the alignment error angle of orientation can reach33second of arc through the method mentioned above. Alignment accuracy is higher than the UKF and the EKF, and the computation time is slightly longer than the two algorithms.
The paper selects the before and after-two directions kalman smooth filtering termination point correction algorithm, that utilizes the offline features of the positioning calculation to resolve the calculated trajectory of the pipeline on the termination point deviating from the actual location problem. The algorithm smoothed estimates of all the measurement information, the actual termination point position is introduced into the positioning calculation. Experimental results show that the termination calculation point is coincident with the actual point after the algorithm. It improves positioning accuracy to a relative error of1.8%per100m, and the method has a certain practicality.
引文
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