基于光纤捷联惯导的长壁工作面采煤机运行姿态感知研究

Intelligent mining is demand and inevitable direction of the development of China’s coal industry, so three-dimensional running posture of shearer is the necessary and basic information for intelligent mining. Perception of the location and posture of shearer has been preliminarily realized in the extensive studies. However, the measurement accuracy still cannot meet the requirements, which hinders the development of intelligence workface. To solve the issues of measurement accuracy of shearer running posture in longwall mining, the F-SINS, which is advanced, is employed, as well as the rotating modulation and MSIF(multi-sensor information fusion). The study will be conducted in three administrative levels of element, SINS, and system, with the scientific problems as error compensation and multi-sensor information fusion, based on the research of certain application circumstance of strong vibration and frequently changed temperature. The errors analysis and compensation models of FIMU under certain error source conditions of the shearer will be built and the transformation error effect of single-axis rotation modulating FIMU will be studied. Thus, the character of the errors transmission in single-axis rotating modulation of the constant drift will be discussed, then the optimum calculation structure and algorithms for shearer running posture could be known. The space and time registering model of the sensors information based on the character of the multi-sensors system will be established and the optimum posture information fusion algorithms will be developed. This research could help to realize a high-accuracy sensing of the shear running posture, and provide research foundation and theoretical reference for the forecasting of production status and intelligent controlling in longwall mining.

智能化开采是我国煤炭工业发展的需求和必然方向，基于三维空间尺度的采煤机运行姿态是实现智能化开采的必需性基础信息。已有工作初步实现了采煤机的定位定姿，但测量精度尚还欠缺，阻碍了综采工作面智能化的发展。项目引入先进的光纤捷联惯导，综合采用旋转调制、多传感器信息融合的方法，着眼于将光纤惯性导航应用于采煤机运行姿态高精度感知时的元件级、捷联惯导级与系统级三个层面，针对采煤机强振动、频变温特殊应用条件下的误差补偿、多传感器信息融合进行基础科学问题的研究：建立采煤机特定误差源下光纤惯性测量组件的误差分析与补偿模型；探讨光纤惯组单轴旋转调制在噪声干扰时的转位误差效应，研究捷联惯导元件常值漂移等误差的传播特性，确立最佳姿态解算结构与算法；建立基于多传感器结构特征的时空配准模型，开发最佳的姿态估计融合算法。项目可实现采煤机运行姿态的高精度感知，为综采工作面的生产状态预测及智能化控制提供研究基础与理论参考。

煤矿智能化开采是国家能源技术创新战略，是实现煤炭工业高质量发展的核心技术支撑和必由之路，精准获取采煤机在井下工作面的实时姿态信息是实现煤矿智能化开采的必要前提。针对采煤机实时姿态信息精度不足的问题，基于光纤捷联惯导、旋转调制、多传感器信息融合等基础理论与前沿技术，提取了采煤机误差源特征，建立了光纤惯性测量组件的误差补偿模型；掌握了采煤机FIMU单轴旋转调制的误差传播特性，探明了强振动、频变温环境下单轴旋转转位机构的转位误差效应；提出了多传感器协同工作的量测信息预处理算法，优化了采煤机运行姿态估计的多传感器信息融合算法。解决了将光纤捷联惯导应用于采煤机运行姿态的高精度感知所面临的具体问题，为采煤机定位、预测滚筒割煤位置和工作面的三维延伸方向提供了理论基础，实现了提高采煤机运行姿态感知精度的目的。同时，项目针对采煤机特定的应用条件，开发了针对性的FIMU的误差补偿模型和多传感器信息融合算法，补充了相关领域的研究成果。项目成果提升了煤矿安全生产效率和智能化开采水平，技术优势、经济效益和社会效益显著，具有广阔的应用前景，为煤矿安全生产的稳定好转提供原动力，对提高我国煤矿智能化开采技术水平具有重要意义。