煤矿掘进装备光纤惯导在井下掘进工作面易受振动与电磁等多源异构噪声干扰，导致掘进装备位姿检测准确性降低。因此，为消除噪声干扰对组合惯导定位检测影响，提出了一种改进经验模态分解(EMD) 的光纤惯导多源异构噪声降噪方法。首先，根据井下掘进工作面环境噪声特性，分析多源异构噪声构成。然后，利用改进的EMD 降噪方法对光纤惯导多源异构噪声进行降噪，该方法通过计算连续均方误差(CMSE) 自适应筛选出有效本征模态函数(IMF)，并通过设定阈值函数对各层有效IMF 分量进行优化，重构优化后的有效IMF 分量，从而获得降噪后的信号。为验证改进EMD 方法的降噪效果，运用小波降噪方法、变分模态分解(VMD) 降噪方法和改进EMD 降噪方法进行了降噪对比试验，结果表明：改进EMD 降噪方法降噪效果优于小波降噪和VMD 降噪方法。为验证改进EMD 方法对掘进装备位姿检测准确性的提升效果，对降噪前以及利用3 种降噪方法降噪后的光纤惯导与位移传感器组合定位结果进行对比分析，结果表明：改进EMD 方法对光纤惯导信号降噪后组合定位的位姿误差最小，且相较于降噪前大幅降低，与降噪前相比，俯仰角误差从0.113 1°下降到0.028 6°，横滚角误差从0.010 1°下降到0.003 8°，航向角误差从2.705 1°下降到0.027 2°，北向位置误差从36.887 2 m 下降到0.082 2 m，东向位置误差从0.499 0 m 下降到0.016 1 m，天向位置误差从0.914 1 m 下降到0.014 3 m。提出的改进EMD 降噪方法能够有效地滤除煤矿掘进装备光纤捷联惯导

信号的多源异构噪声，为煤矿掘进装备精确定位奠定了良好基础。

The optical fiber inertial navigation of coal mine excavation equipment is easy to be disturbed by multi-source heterogeneous noise such as vibration and electromagnetism in the underground excavation face, which leads to the reduction of the accuracy of position and attitude detection of excavation equipment. Therefore, in order to eliminate the influence of noise interference on the positioning and detection of integrated inertial navigation, a multi-source heterogeneous noise reduction method of optical fiber inertial navigation based on improved empirical mode decomposition (EMD) is proposed. Firstly, according to the environmental noise characteristics of underground heading face, the composition and characteristics of multi-source heterogeneous noise are analyzed. Then, the improved EMD noise reduction method is used to reduce the multi-source heterogeneous noise of optical fiber inertial navigation. This method adaptively selects the effective eigenmode function (IMF) by calculating the continuous mean square error (CMSE), optimizes the effective IMF component of each layer by setting the threshold function, and reconstructs the optimized effective IMF component, so as to obtain the signal after noise reduction. In order to verify the noise reduction effect of the improved EMD method, the comparative experiments of wavelet noise reduction method, variational modal decomposition (VMD) noise reduction method and improved EMD noise reduction method are carried out. The results show that the noise reduction effect of the improved EMD noise reduction method is better than that of wavelet noise reduction and VMD noise reduction method. In order to verify the improvement effect of the improved EMD Method on the pose detection accuracy of tunneling equipment, the combined positioning results of optical fiber inertial navigation and displacement sensor before noise reduction and after noise reduction by three noise reduction methods are compared and analyzed. The results show that the pose error of the combined positioning after noise reduction of optical fiber inertial navigation signal by the improved EMD method is the smallest, and it is greatly reduced compared with that before noise reduction, The Pitch angle error decreased from 0.113 1° to 0.028 6°, the Roll angle error decreased from 0.010 1° to 0.003 8°, the Yaw angle error decreased from 2.705 1° to 0.027 2°, the North position error decreased from 36.887 2 to 0.082 2 m, the East position error decreased from 0.499 0 to 0.016 1 m, and the Upward position error decreased from 0.914 1 to 0.014 3 m. The improved EMD noise reduction method proposed in this paper can effectively filter the multi-source heterogeneous noise of optical fiber strapdown inertial navigation signal of coal mine excavation equipment, which lays a good foundation for the accurate positioning of coal mine excavation equipment.