张坤, 孙政贤, 刘亚, 李玉霞, 杜明超, 马英, 魏训涛, 徐亚军, 王鑫, 余铜柱, 丁超. 基于信息融合技术的超前液压支架姿态感知方法及实验验证[J]. 煤炭学报, 2023, 48(S1): 345-356. DOI: 10.13225/j.cnki.jccs.2022.0621
引用本文: 张坤, 孙政贤, 刘亚, 李玉霞, 杜明超, 马英, 魏训涛, 徐亚军, 王鑫, 余铜柱, 丁超. 基于信息融合技术的超前液压支架姿态感知方法及实验验证[J]. 煤炭学报, 2023, 48(S1): 345-356. DOI: 10.13225/j.cnki.jccs.2022.0621
ZHANG Kun, SUN Zhengxian, LIU Ya, LI Yuxia, DU Mingchao, MA Ying, WEI Xuntao, XU Yajun, WANG Xin, YU Tongzhu, DING Chao. Research and experimental verification of attitude perception method of advanced hydraulic support based on information fusion technology[J]. Journal of China Coal Society, 2023, 48(S1): 345-356. DOI: 10.13225/j.cnki.jccs.2022.0621
Citation: ZHANG Kun, SUN Zhengxian, LIU Ya, LI Yuxia, DU Mingchao, MA Ying, WEI Xuntao, XU Yajun, WANG Xin, YU Tongzhu, DING Chao. Research and experimental verification of attitude perception method of advanced hydraulic support based on information fusion technology[J]. Journal of China Coal Society, 2023, 48(S1): 345-356. DOI: 10.13225/j.cnki.jccs.2022.0621

基于信息融合技术的超前液压支架姿态感知方法及实验验证

Research and experimental verification of attitude perception method of advanced hydraulic support based on information fusion technology

  • 摘要: 超前耦合支护系统空间姿态动态监测方法融合了众多的先进感知传感器,而单一感知传感器间相对独立,无法融合由于复杂扰动变化引起的超前液压支架组的空间姿态动态信息和相对位置信息反馈。采用多传感器系统协同作业的原理,结合超前液压支架组相对位置调整、移架和顶底板变形引起的2种典型空间姿态变化情况,提出一种基于信息融合技术的超前液压支架组姿态感知方法。采用超声波测距传感器测量超前液压支架组与巷帮相对位置动态信息,将小于安全距离进行位置调整过程中所引发的超前液压支架组空间姿态变化视为航向角度的动态变化,实现超前液压支架组位置调整、移架过程的空间姿态感知。采用九轴姿态传感器感知支架顶梁、底座和连杆机构的姿态动态变化信息,利用卡尔曼滤波算法融合单个姿态传感器各轴姿态数据,抑制测量过程中噪声的影响,利用自适应加权融合算法将所有姿态传感器具有相同变化趋势的同轴数据进行融合,实现对超前液压支架组空间姿态数据的动态融合感知。最后使用超前液压支架组空间姿态感知实验台对所提出的超前液压支架组空间姿态感知方法进行实验验证分析。实验结果表明:横滚角融合结果最大误差为0.024 3°,最小误差为0.001 6°,平均绝对误差为0.004 8°,偏航角融合结果最大误差为0.027 6°,最小误差为0.001 2°,平均绝对误差为0.004 7°,验证了所提出的姿态感知方法的准确性。

     

    Abstract: The spatial attitude dynamic monitoring method of advanced coupling support system integrates many advanced sensing sensors,and the single sensing sensor is relatively independent,which cannot fuse the spatial attitude dynamic information and relative position information feedback of advanced hydraulic support group caused by complex disturbance changes. Based on the principle of cooperative operation of multi-sensor system,combined with two typical spatial posture changes caused by the relative position adjustment of advanced hydraulic support group,frame shifting and roof and floor deformation,a posture perception method of advanced hydraulic support group based on information fusion technology is proposed. The ultrasonic ranging sensor is used to measure the dynamic information of the relative position between the advanced hydraulic support group and the roadway side. The spatial attitude change of the advanced hydraulic support group caused by the position adjustment process less than the safe distance is regarded as the dynamic change of the heading angle,so as to realize the spatial attitude perception of the position adjustment and the frame shifting process of the advanced hydraulic support group. The nine-axis attitude sensor is used to perceive the attitude dynamic change information of the top beam,the base and the linkage mechanism of the support. The Kalman filter algorithm is used to fuse the attitude data of each axis of a single attitude sensor to suppress the influence of noise in the measurement process. The adaptive weighted fusion algorithm is used to fuse the coaxial data with the same change trend of all attitude sensors,so as to realize the dynamic fusion perception of the spatial attitude data of the advanced hydraulic support group. Finally,the spatial attitude perception experiment platform of the advanced hydraulic support group is used to verify and analyze the proposed spatial attitude perception method of the advanced hydraulic support group. The experimental results show that the maximum error of roll angle fusion is 0.024 3°,the minimum error is 0.001 6°,and the average absolute error is 0.004 8°. The maximum error of yaw angle fusion is 0.027 6°,the minimum error is 0.001 2°,and the average absolute error is 0.004 7°. The accuracy of the proposed attitude perception method is verified.

     

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