Feng Jinbao, Wu Jinhui, Si Yu, Gao Yubin, Liu Ji, Wang Gao
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China.
School of Information Technology Application and Innovation, Yuncheng Vocational and Technical University, Yuncheng 044000, China.
Sensors (Basel). 2021 Nov 12;21(22):7520. doi: 10.3390/s21227520.
To study the law that governs the complex movements of the mechanism in the process of automatic weapon operation, the velocity tracking test technology of photon Doppler velocimetry is introduced to accurately measure velocity, displacement and acceleration, on the condition that there are long displacement and rapid velocity change. In the traditional way, out of interference signal time-frequency (TF) transformation draws TF distribution, and then by modulus maxima frequency extraction, comes to the law of velocity change. Due to the influence resulting from the change of fundamental signal as well as that of light intensity signal in the test, based on the TF distribution obtained by TF transformation, the traditional modulus maxima frequency extraction can extract frequency signals, but they show abnormal sudden changes at some moments, making the velocity discontinuous, unsmooth and unreal, which brings obvious errors to the subsequent calculation of acceleration and accurate displacement. Addressing the above-mentioned problems, this paper proposes a ridge extracting correction algorithm based on modulus maxima frequency extraction; this method, based on a large number of experiments where rodless cylinders are used to simulate the motion of a gun automatic mechanism, conducts a detailed calculation and analysis of the experimental results. A comparison of the two algorithms' processing results, in terms of the speed, displacement and acceleration, suggests that the ridge extracting correction algorithm successfully corrects the frequency selection error, which draws a more continuous and, therefore, effective curve of the velocity change, and by so doing, the error of the displacement test (within 1.36 m displacement) is reduced from more than 3.6% to less than 0.58%, and the uncertainty dropped 97.07%. All these show that the accurate measurement of velocity, displacement and acceleration, with sudden and rapid velocity changes considered, is realized successfully.
为研究自动武器工作过程中机构复杂运动的规律，引入光子多普勒测速仪的速度跟踪测试技术，在位移长、速度变化快的条件下精确测量速度、位移和加速度。传统方法是对干扰信号进行时频（TF）变换得出TF分布，再通过模量最大值频率提取得出速度变化规律。由于测试中基波信号变化以及光强信号变化的影响，传统模量最大值频率提取基于TF变换得到的TF分布能提取频率信号，但在某些时刻会出现异常突变，导致速度不连续、不光滑且不真实，给后续加速度计算和精确位移带来明显误差。针对上述问题，本文提出一种基于模量最大值频率提取的脊线提取校正算法；该方法基于大量用无杆气缸模拟火炮自动机构运动的实验，对实验结果进行了详细计算和分析。两种算法处理结果在速度、位移和加速度方面的比较表明，脊线提取校正算法成功校正了频率选择误差，绘制出更连续、有效的速度变化曲线，位移测试误差（位移在1.36 m以内）从3.6%以上降至0.58%以下，不确定度下降97.07%。所有这些表明，成功实现了在考虑速度突变和快速变化情况下对速度、位移和加速度的精确测量。
