A filtering method for underground manipulator communication signal
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摘要: 多自由度机械臂在煤矿井下作业时，其通信信号易受到脉冲、电磁干扰等外部因素的影响，降低信号传输可靠性，影响多自由度机械臂的灵活性和控制精度。为提高井下多自由度机械臂通信信号质量，提出了一种基于改进时频峰值滤波的井下机械臂通信信号滤波方法。根据机械臂通信信号的载波节点提取载波特征，基于希尔伯特变换理论提取传输周期特征。利用小波分解求解每一级小波变换系数，获取通信信号扰动频率，完成通信信号特征分类。引入相位补偿因子改进时频峰值滤波，根据比例因子和削减因子计算削减门限阈值，调整固定窗口长度，并采用改进时频峰值滤波滤除通信信号中的噪声，实现多自由度机械臂通信信号噪声抑制。以3自由度机械臂为试验对象，设置脉冲宽度为8 μs、波特率为120 bit/s，通信信号传输时间间隔为2 ms、信号幅度为1，向通信信号加入30 dB高斯白噪声。试验结果表明：经基于改进时频峰值滤波的井下机械臂通信信号滤波方法处理后的通信信号输出信噪比为94 dB，误码率基本稳定在0.6%，丢帧率均值由滤波前的2.9%降至0.8%，有效提高了多自由度机械臂通信信号质量和传输可靠性。Abstract: When a multi-degree-of-freedom manipulator operates in underground coal mines, its communication signal is easily affected by external factors such as pulses and electromagnetic interference. It reduces the reliability of signal transmission and affects the flexibility and control precision of the multi-degree-of-freedom manipulator. To improve the communication signal quality of underground multi-degree-of-freedom manipulator, a filtering method for underground manipulator communication signal based on improved time-frequency peak filtering is proposed. The method extracts carrier features based on the carrier nodes of the manipulator communication signal, and extracts transmission period features based on Hilbert transform theory. The method uses wavelet decomposition to solve the wavelet transform coefficient of each level, obtains the disturbance frequency of communication signals, and completes the classification of communication signal features. The method introduces phase compensation factors to improve time-frequency peak filtering. The reduction threshold is calculated according to the scaling factor and reduction factor, so as so adjust the fixed window length. The improved time-frequency peak filtering is used to filter the noise in communication signals. Thus the noise suppression of the multi-degree-of-freedom manipulator communication signal is achieved. A 3-degree-of-freedom manipulator is taken as the experimental object. The pulse width is set to be 8 μs. The Baud rate is 120 bit/s, the communication signal transmission interval is 2 ms, and the signal amplitude is 1. 30 dB Gaussian white noise is added to the communication signal. The experimental results show that the output signal-to-noise ratio of the communication signal processed by the filtering method for underground manipulator communication signal based on improved time-frequency peak filtering is 94 dB. The bit error rate is basically stable at 0.6%, and the average frame loss rate is reduced from 2.9% before filtering to 0.8%. The method effectively improves the communication signal quality and transmission reliability of the multi-degree-of-freedom manipulator.
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图 4 信噪比和误码率对比试验结果
Figure 4. Comparative experiment results of signal-to-noise ratio and bit error rate
表 1 计算机配置
Table 1. Computer configuration
项目 参数 硬件 CPU i3 2120 主频/GHz 3.3 物理内存/GiB 32 软件 操作系统 Windows 10 开发语言 Python 语料提取工具 NLP 向量训练工具 Fast Text 数据库处理工具 SQL Server 2019 
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[1] 刘送永,徐海乔,张德义,等. 多自由度自动喷浆机械臂运动分析及路径优化[J]. 煤炭学报,2020,45(增刊2):1079-1088.LIU Songyong,XU Haiqiao,ZHANG Deyi,et al. Motion analysis and path optimization of multi-DOF automatic shotcrete manipulator[J]. Journal of China Coal Society,2020,45(S2):1079-1088. [2] 杨鹏民. 基于嵌入式Linux与深度视觉的井下多轴机械臂系统设计[J]. 煤炭工程,2022,54(12):90-96.YANG Pengmin. Design of underground multi-axis mechanical arm system based on embedded Linux and deep perception[J]. Coal Engineering,2022,54(12):90-96. [3] 马宏伟,张烨,王鹏,等. 多机械臂煤矸石智能分拣机器人关键共性技术研究[J]. 煤炭科学技术,2023,51(1):427-436.MA Hongwei,ZHANG Ye,WANG Peng,et al. Research on key generic technology of multi-arm intelligent coal gangue sorting robot[J]. Coal Science and Technology,2023,51(1):427-436. [4] 李正楠,殷玉枫,张锦,等. 多关节机械臂反演滑模神经网络干扰观测器控制[J]. 机械设计,2021,38(3):126-131. doi: 10.13841/j.cnki.jxsj.2021.03.019LI Zhengnan,YIN Yufeng,ZHANG Jin,et al. Disturbance observer control of the multi-joint manipulator based on the backstepping sliding mode's neural network[J]. Journal of Machine Design,2021,38(3):126-131. doi: 10.13841/j.cnki.jxsj.2021.03.019 [5] 张润梅,罗谷安,袁彬,等. 多关节机械臂干扰观测器的自适应滑模控制[J]. 机械科学与技术,2021,40(10):1595-1602.ZHANG Runmei,LUO Gu'an,YUAN Bin,et al. Adaptive sliding mode control of disturbance observer for multi-joint manipulator[J]. Mechanical Science and Technology for Aerospace Engineering,2021,40(10):1595-1602. [6] 丁力,姚勇,巢渊,等. 面向水质采样的绳驱动空中机械臂抗干扰控制[J]. 农业机械学报,2022,53(8):452-458.DING Li,YAO Yong,CHAO Yuan,et al. Disturbance rejection control for cable-driven aerial manipulator applied on water samples[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(8):452-458. [7] 阙红波,高扬,吴成攀,等. 基于扩展卡尔曼滤波和希尔伯特−黄变换瞬时频率的齿轮啮合刚度辨识算法[J]. 科学技术与工程,2021,21(8):3104-3111.QUE Hongbo,GAO Yang,WU Chengpan,et al. Gear meshing stiffness identification algorithm based on extended Kalman filter and Hilbert-Huang transform instantaneous frequency[J]. Science Technology and Engineering,2021,21(8):3104-3111. [8] 刘高辉,刘军. 基于扩展粒子滤波算法的单载波通信信号载波跟踪方法研究[J]. 微电子学与计算机,2021,38(12):61-68.LIU Gaohui,LIU Jun. Research on the carrier tracking method of single-carrier communication signal based on extended particle filter algorithm[J]. Microelectronics & Computer,2021,38(12):61-68. [9] 赵永梅. VMD和小波阈值重构的电力电缆局部放电信号去噪法[J]. 西安科技大学学报,2021,41(4):739-746.ZHAO Yongmei. Denoising method of cable partial discharge signals based on VMD and wavelet threshold reconstruction[J]. Journal of Xi'an University of Science and Technology,2021,41(4):739-746. [10] 邓云云,陈克安,李豪,等. 噪声主观评价中的白噪声标准样本法及其应用[J]. 西北工业大学学报,2022,40(4):746-754. doi: 10.1051/jnwpu/20224040746DENG Yunyun,CHEN Ke′an,LI Hao,et al. The white noise standard sample method and application for subjective noise evaluation[J]. Journal of Northwestern Polytechnical University,2022,40(4):746-754. doi: 10.1051/jnwpu/20224040746 [11] 邓黎,李伯中,金炜,等. 光纤非线性补偿中低通滤波器对DBP算法的影响[J]. 光通信技术,2021,45(7):10-13.DENG Li,LI Bozhong,JIN Wei,et al. Influence of low pass filter with optical fiber nonlinear compensation on DBP algorithm[J]. Optical Communication Technology,2021,45(7):10-13. [12] 陈建国,黄宇,严南. 基于频谱修正的通信噪声信号峰值检测系统[J]. 科技通报,2021,37(4):33-36,41.CHEN Jianguo,HUANG Yu,YAN Nan. Simulation of software secret data loss prevention transmission based on mobile gateway[J]. Bulletin of Science and Technology,2021,37(4):33-36,41. [13] 章小宝,陈巍. 基于时域有限差分的通信干扰信号广域监测[J]. 计算机仿真,2021,38(10):227-231.ZHANG Xiaobao,CHEN Wei. Wide-area monitoring of communication interference signals based on finite difference time domain[J]. Computer Simulation,2021,38(10):227-231. [14] 王永杰. 船岸通信技术下舰船导航信号非线性滤波[J]. 舰船科学技术,2022,44(20):139-142.WANG Yongjie. Nonlinear filtering of ship navigation signal based on ship shore communication technology[J]. Ship Science and Technology,2022,44(20):139-142. [15] 林家锴,衣文索. 基于M−Z干涉结构的低频信号相位解调方法[J]. 光通信技术,2022,46(4):94-96.LIN Jiakai,YI Wensuo. Phase demodulation method of low frequency signal based on M-Z interference structure[J]. Optical Communication Technology,2022,46(4):94-96. [16] 张霄霄,梁兴东,王杰,等. 融合失配处理和LMS滤波的雷达通信一体化OFDM信号距离旁瓣抑制技术[J]. 信号处理,2021,37(9):1727-1738.ZHANG Xiaoxiao,LIANG Xingdong,WANG Jie,et al. Range sidelobe suppression using mismatching and LMS adaptive filter for radar communication integrated OFDM signal[J]. Journal of Signal Processing,2021,37(9):1727-1738. [17] 朱雨男,王彪,张岑. 基于深度神经网络的水声FBMC通信信号检测方法[J]. 声学技术,2021,40(2):199-204. doi: 10.16300/j.cnki.1000-3630.2021.02.008ZHU Yunan,WANG Biao,ZHANG Cen. DNN based signal detection for underwater acoustic FBMC communications[J]. Technical Acoustics,2021,40(2):199-204. doi: 10.16300/j.cnki.1000-3630.2021.02.008 [18] 李冬霞,陈佩,刘海涛,等. 测距仪干扰信号频域特性研究[J]. 中国民航大学学报,2021,39(2):16-20,41.LI Dongxia,CHEN Pei,LIU Haitao,et al. Frequency-domain characteristics of DME interference signal[J]. Journal of Civil Aviation University of China,2021,39(2):16-20,41. [19] 陈晓威,杨文革. 基于时变白化滤波器的DSSS系统干扰盲检测[J]. 系统工程与电子技术,2021,43(7):1981-1988.CHEN Xiaowei,YANG Wenge. Blind jamming detection based on time variant whitener for DSSS systems[J]. Systems Engineering and Electronics,2021,43(7):1981-1988. [20] 王伟屹,赵晔. 卡尔曼滤波算法下电力通信自动化监测系统设计[J]. 西安工程大学学报,2021,35(5):50-55. doi: 10.13338/j.issn.1674-649x.2021.05.008WANG Weiyi,ZHAO Ye. Design of power communication automatic monitoring system based on Kalman filter algorithm[J]. Journal of Xi'an Polytechnic University,2021,35(5):50-55. doi: 10.13338/j.issn.1674-649x.2021.05.008 [21] BRAUN S, GAMPER H, REDDY C K A, et al. Towards efficient models for real-time deep noise suppression[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Toronto, 2021: 656-660. [22] HALIMEH M M, HAUBNER T, BRIEGLEB A, et al. Combining adaptive filtering and complex-valued deep postfiltering for acoustic echo cancellation[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Toronto, 2021: 121-125. -
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