基于自适应卡尔曼滤波的双惯导采煤机定位方法

杨金衡, 宋单阳, 田慕琴, 宋建成, 许春雨

杨金衡，宋单阳，田慕琴,等.基于自适应卡尔曼滤波的双惯导采煤机定位方法［J］.工矿自动化，2021,47（7）：14-20.. DOI: 10.13272/j.issn.1671-251x.2021030113
引用本文: 杨金衡，宋单阳，田慕琴,等.基于自适应卡尔曼滤波的双惯导采煤机定位方法［J］.工矿自动化，2021,47（7）：14-20.. DOI: 10.13272/j.issn.1671-251x.2021030113
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YANG Jinheng, SONG Danyang, TIAN Muqin, SONG Jiancheng, XU Chunyu. Double inertial navigation shearer positioning method based on adaptive Kalman filter[J]. Journal of Mine Automation, 2021, 47(7): 14-20. DOI: 10.13272/j.issn.1671-251x.2021030113
Citation: YANG Jinheng, SONG Danyang, TIAN Muqin, SONG Jiancheng, XU Chunyu. Double inertial navigation shearer positioning method based on adaptive Kalman filter[J]. Journal of Mine Automation, 2021, 47(7): 14-20. DOI: 10.13272/j.issn.1671-251x.2021030113
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基于自适应卡尔曼滤波的双惯导采煤机定位方法

  • 1.

    太原理工大学 矿用智能电器技术国家地方联合工程实验室， 山西 太原030024

  • 2.

    太原理工大学 煤矿电气设备与智能控制山西省重点实验室， 山西 太原030024）

基金项目: 

山西省专利推广实施资助专项（20210532）

详细信息

  • 中图分类号: TD679

Double inertial navigation shearer positioning method based on adaptive Kalman filter

  • 1.

    National and Provincial Joint Engineering Laboratory of Mining Intelligent Electrical Apparatus Technology, Taiyuan University of Technology, Taiyuan 030024, China

  • 2.

    Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control, Taiyuan University of Technology, Taiyuan 030024, China

摘要

    摘要
  • 摘要: 基于惯导的采煤机定位方法存在误差累计、姿态角及位置漂移等固有缺陷，虽然引入误差补偿技术和多传感器组合定位技术可在一定程度上减小误差，但效果有限。针对上述问题，提出了一种基于自适应卡尔曼滤波的双惯导采煤机定位方法。实时同步采集安装在采煤机上的2套惯导系统的加速度和姿态角，以惯导系统的位置作为状态量，惯导系统之间的距离和夹角为观测量，建立了双惯导定位模型，以克服单惯导定位误差累计的缺点。然而，双惯导系统输出存在较大差异时会导致双惯导定位模型出现状态突变，降低定位模型准确度，因此采用自适应卡尔曼滤波算法，通过计算基于残差的卡方检验值评估双惯导定位模型是否发生状态突变，并采用三段模糊判别函数动态调整过程噪声的协方差矩阵，以降低状态突变对定位精度的影响。仿真和实验结果表明，自适应卡尔曼滤波相比扩展卡尔曼滤波的抗干扰能力更强，有效减小了状态突变时的估计误差；基于自适应卡尔曼滤波的双惯导采煤机定位方法的定位误差比单惯导的定位误差在各方向上均有所减小。
    Abstract: The shearer positioning method based on inertial navigation has inherent defects such as error accumulation, attitude angle and position drift. Although the introduction of error compensation technology and multi-sensor combination positioning technology can reduce the error to a certain extent, the effect is limited. In order to solve the above problems, a dual inertial navigation shearer positioning method based on adaptive Kalman filtering is proposed. The acceleration and attitude angle of the 2 inertial navigation systems installed on shearer are collected synchronously in real time, the position of the inertial navigation system is used as the state quantity, and the distance and angle between the inertial navigation systems are used as observed quantities. The dual inertial navigation positioning model is established to overcome the shortcomings of accumulated single inertial navigation positioning errors. However, the large difference in the output of the dual inertial navigation system can lead to sudden changes in the state of the dual inertial navigation positioning model and reduce the accuracy of the positioning model. Therefore, the adaptive Kalman filtering algorithm is used to evaluate whether the dual inertial navigation positioning model has sudden changes in the state by calculating the residual-based chi-square test value. And the covariance matrix of the process noise is dynamically adjusted by using a three-segment fuzzy discriminant function to reduce the impact of sudden changes in the state on the positioning accuracy. The simulation and experimental results show that the adaptive Kalman filter has stronger anti-interference ability than the extended Kalman filter, and reduces the estimation error effectively when the state changes suddenly. The positioning error of the dual inertial guidance shearer positioning method based on adaptive Kalman filter is reduced in all directions than that of the single inertial guidance shearer positioning method.
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出版历程
  • 刊出日期:  2021-07-19

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