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The application and analysis of H filter based on SLAM in detection and location of underwater oil pipeline leakage

机译:基于SLAM的H 滤波器在水下输油管道泄漏检测与定位中的应用与分析

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Aiming at improving the positioning accuracy of the submarine oil pipeline leak location, a new positioning algorithm SINS combined SLAM is proposed. When AUV is navigation positioning, it can realize the tracking of Submarine oil pipeline's simultaneous localization and mapping, and use the location information of map features in the submarine oil pipeline to correct method of SINS which has more advantage and makes the system error not accumulate with time. By setting specific pipeline mathematical function, collecting its two-dimensional position information with sensors,the actual graphics was built, and processing the marked accurate leakage point from image to achieve accurate positioning purposes; Using the extended H filter (EHF) to do simulation experiment on position information acquired by SINS/SLAM integrated navigation. Which show data association of noise and observation are robust to model uncertainties, and filtering accuracy reaches 0.1% of total distance. The oil pipeline leak location precision is also guaranteed, and passive navigation for underwater pipeline tracking detection is feasible.
机译:为了提高海底输油管道泄漏位置的定位精度,提出了一种结合SLAM的SINS定位算法。在水下航行器进行导航定位时,可以实现海底输油管道同时定位和制图的跟踪,并利用海底输油管道中地图要素的位置信息来校正捷联惯导系统的方法,该方法具有更多的优点,并且不会累积系统误差。时间。通过设置特定的流水线数学函数,利用传感器采集其二维位置信息,建立实际图形,并对图像中标记出的准确泄漏点进行处理,以达到准确定位的目的。使用扩展H滤波器(EHF)对SINS / SLAM组合导航获取的位置信息进行仿真实验。显示噪声和观测值的数据关联对不确定性模型具有鲁棒性,并且滤波精度达到总距离的0.1%。输油管道泄漏定位精度也得到保证,用于水下管道跟踪检测的被动导航是可行的。

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