Research of precision improving algorithm of shearer positioning based on UWB
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摘要: 针对在矿井中采用UWB定位系统获取采煤机位置坐标时精度较低等问题,提出了一种基于UWB的采煤机定位精度提升算法,该算法利用信息过滤算法处理多种信号值的能力对UWB定位结果进行过滤,利用神经网络算法评估优化的能力对采煤机位于刮板输送机机头位置某个时间段内的数据信息进行评估,实现对采煤机的精确定位。实验结果表明,对定位结果进行过滤处理后,三维精度可达7 cm左右,经神经网络算法处理后,定位精度可提升至2~3 cm。Abstract: In view of problem of low precision of using UWB positioning system to obtain position coordinates of shearer, a precision improving algorithm of shearer positioning based on UWB was put forward. The algorithm uses ability of analysis of various signal values of information filter algorithm to filter UWB positioning results, and uses ability of optimal solution of neural network algorithm to evaluate positioning information during certain period when the shearer stays at the head position of scraper conveyer, in order to realize accurate shearer positioning. The experiment results show that after using information filter algorithm to process positioning results, the 3D accuracy can reach 7 cm, and after the application of neural network algorithm, the positioning accuracy can reach 2~3 cm.
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Key words:
- coal mining /
- shearer positioning /
- UWB /
- information filter /
- neural network
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