小径管道机器人微惯性辅助定位系统优化分析及高精度定位方法研究

Pipeline leakage and explosion not only cause economic losses, but also pollute the environment and threaten the safety of civilian's lives and property, even lead to extremely bad social impact. Pipeline Inspection Gauge (PIG) could implement the pipeline defects (corrosions, cracks, etc) inspection effectively and localization precisely by carrying various pipeline defects inspection sensors and positioning sensors, which are used for pipeline integrity management. Actually, the urban underground pipeline usually present with small diameter and complicated in distribution, which is a great challenge for the positioning of PIG. So the research of related problems is still in exploring stage at home and abroad. This project aims to conduct optimal analysis for the micro-inertial aided positioning system and have in-depth research of its high-precision positioning method for the small-diameter PIG. At the begining, the influence mechanism of PIG rolling motion on micro-inertial positioning system is analyzed deeply, which implements the optimal analysis of micro-inertial aided positioning system and the selection of micro-inertial sensors. Then, the Pipeline Junction (PJ) identification method based on a novel artificial fish swarm algorithm is studied to improve the speed and accuracy of the PJ identification result. After that, a PIG positioning system that comprises of micro-inertial/odometer/PJ/pipeline segment length is proposed and also the application mechanism of Particle filter and its smoothing technology on the PIG positioning system is researched to improve the overall positioning precision for the small-diameter PIG. Finally, the related methods and research results are verified by indoor wheel robot and PIG, respectively.

管道泄漏爆炸不仅造成经济损失，更会污染环境、威胁人民生命财产安全，造成极坏社会影响。管道机器人通过携带各种管道缺陷（腐蚀、裂纹等）检测传感器和定位传感器实现管道缺陷有效检测及精确定位，指导管道完整性管理。城市地下管道口径小且分布复杂，对管道机器人定位带来了极大挑战，国内外对相关问题研究还处于探索阶段。本项目拟对小径管道机器人微惯性辅助定位系统进行优化分析并深入研究其高精度定位方法。首先深入分析管道机器人横滚运动对微惯性定位系统影响机理，实现微惯性辅助定位系统优化分析及微惯性传感器选型。其次研究基于新型人工鱼群算法的管道连接器辨识方法，提高管道连接器辨识速度和精度。然后提出基于微惯性/里程仪/管道连接器/管道段长度的管道机器人定位系统，并研究粒子滤波及其平滑技术在该定位系统中应用机理，提高系统整体定位精度。最后，分别采用室内轮式机器人及管道机器人对相关方法和研究结果进行验证。

管道泄漏爆炸不仅造成经济损失，更会污染环境、威胁人民生命财产安全，造成极坏社会影响。管道机器人通过携带各种管道缺陷（腐蚀、裂纹等）检测传感器和定位传感器实现管道缺陷有效检测及精确定位，指导管道完整性管理。城市地下管道口径小且分布复杂，对管道机器人定位带来了极大挑战，国内外对相关问题研究还处于探索阶段。本项目通过对小径管道机器人微惯性辅助定位系统进行优化分析并深入研究其高精度定位方法。首先，从不同管内运输介质（油、水及气等）角度深入分析管道机器人横滚运动对微惯性定位系统影响机理，通过对系统理论分析及测试验证指导微惯性传感器选型。其次，对基于新型人工鱼群算法的管道连接器辨识方法进行研究，弥补传统管道连接器辨识速度和精度方面不足。然后，提出基于微惯性/里程仪/管道连接器/管道段长度的管道机器人定位系统方案，并研究滤波优化技术在该定位系统中应用机理，提高系统整体定位精度。最后，分别采用测绘专用小径管道机器人及缆控检测用小径管道机器人分别在室内搭建的管道中对相关方法和研究结果进行验证。. 因此，本研究成果可实现管道内径10cm及以上管道检测定位精度达到米级，为城市小径管道缺陷检测及精确开挖提供重要的技术支撑，可有效避免在役城市管道因泄漏或爆炸导致的各类事故。