基于惯性传感器数据融合的管线三维可视化研究
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太原理工大学 电力系统运行与控制山西省重点实验室,太原理工大学电气与动力工程学院,太原理工大学 电力系统运行与控制山西省重点实验室

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TP249

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山西省自然科学基金项目(201601D102039) 国家自然科学青年基金(51505317)


Research on Pipeline 3D Visualization Based on Inertial Sensor Data Fusion
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Shanxi Key Laboratory of power system operation and control,Taiyuan University of Technology,,Shanxi Key Laboratory of power system operation and control,Taiyuan University of Technology

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    摘要:

    受施工技术与管线设计等因素影响,一般管线的三维轨迹通常和设计轨迹有部分误差,而精确了解管线的空间位置又十分重要。本文提出一种基于Arduino平台的六轴陀螺仪姿态解算与融合及管线轨迹可视化算法。首先从六轴陀螺仪收集加速计数据和角速度数据,分别计算出姿态角,并对加速计解算的姿态角进行滑动加权滤波,将滤波后的姿态角与角速度计解算的姿态角经卡尔曼滤波进行融合,得出高精度的翻滚角、偏航角、俯仰角,最后通过融合后的数据求得采样点坐标,绘制出三维轨迹。实验结果证明:该算法不仅能够有效消除陀螺仪传感器的误差,而且测出的三维轨迹曲线与实际管线轨迹基本吻合,有很高的精确度。本文研究的算法有很强的实用性。

    Abstract:

    Due to factors such as construction technology and pipeline design, the three-dimensional trajectory of the general pipeline is usually partially offset from the design trajectory, and it is very important to accurately understand the spatial position of the pipeline. This paper presents a six-axis gyro attitude reconciliation and fusion algorithm and pipeline trajectory visualization algorithm based on Arduino platform. Firstly, accelerometer data and angular velocity data of the six-axis gyroscope are collected, and the attitude angles are respectively calculated, and the sliding angle-weighted filtering is performed on the attitude angles calculated by the accelerometer, and the attitude angles of the filtered attitude angle and the angular velocity are calculated. Filtering is carried out to obtain a high-precision roll angle, yaw angle and pitch angle. Finally, the coordinates of the sampling point are obtained from the fused data, and a three-dimensional trajectory is drawn. The experimental results show that the algorithm can not only effectively eliminate the error of the gyro sensor, but also the measured three-dimensional trajectory curve is basically consistent with the actual pipeline trajectory, and has high accuracy. It can be seen that the algorithm studied in this paper has a strong practicality.

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引用本文

李瑞通,赵庆生,王旭平. 基于惯性传感器数据融合的管线三维可视化研究[J]. 科学技术与工程, 2018, 18(34): .
LI Rui-tong,,WANG Xu-ping. Research on Pipeline 3D Visualization Based on Inertial Sensor Data Fusion[J]. Science Technology and Engineering,2018,18(34).

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  • 收稿日期:2018-06-30
  • 最后修改日期:2018-09-25
  • 录用日期:2018-09-27
  • 在线发布日期: 2018-12-20
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