Wan Miao, Wang Zhongbin, Si Lei, Tan Chao, Wang Hao
School of Mechatronic Engineering, China University of Mining & Technology, No. 1 Daxue Road, Xuzhou 221116, China.
CRRC Zhuzhou Locomotive Co., Ltd., Zhuzhou 412001, China.
Comput Intell Neurosci. 2020 Oct 13;2020:8876918. doi: 10.1155/2020/8876918. eCollection 2020.
The shearer is one of the core equipment of the fully mechanized coal face. The fast and accurate positioning of the shearer is the prerequisite for its memory cutting, intelligent height adjustment, and intelligent speed adjustment. Inertial navigation technology has many advantages such as strong autonomy, good concealment, and high reliability. The accurate positioning of the shearer based on inertial navigation can not only determine its operating position but also measure the direction of movement. However, when inertial navigation is used to locate the shearer in motion, the cumulative errors will occur, resulting in inaccurate positioning of the shearer. The accuracy of the initial alignment is directly related to the working precision of the inertial navigation system. In order to improve the efficiency and accuracy of initial alignment, an improved initial alignment method is proposed in this paper, which uses a fruit fly-optimized Kalman filter algorithm for initial alignment. In order to improve the filtering performance, the fruit fly-optimized Kalman filter algorithm uses an improved fruit fly algorithm to realize the adaptive optimization of system noise variance. Finally, simulation and experiments verify the effectiveness of the fruit fly-optimized Kalman filter algorithm.
采煤机是综合机械化采煤工作面的核心设备之一。采煤机的快速准确定位是其记忆割煤、智能调高和智能调速的前提条件。惯性导航技术具有自主性强、隐蔽性好、可靠性高等诸多优点。基于惯性导航的采煤机精确定位不仅能够确定其运行位置,还能测量运动方向。然而,当利用惯性导航对运动中的采煤机进行定位时,会产生累积误差,导致采煤机定位不准确。初始对准的精度直接关系到惯性导航系统的工作精度。为了提高初始对准的效率和精度,本文提出一种改进的初始对准方法,该方法采用果蝇优化的卡尔曼滤波算法进行初始对准。为了提高滤波性能,果蝇优化的卡尔曼滤波算法采用改进的果蝇算法实现系统噪声方差的自适应优化。最后,通过仿真和实验验证了果蝇优化卡尔曼滤波算法的有效性。