为了减少船舶低频震荡对传输信号的干扰、保证通信和导航信号稳定传输，提出一种船舶低频震荡传输信号控制技术。采集船舶低频震荡传输信号，采用离散傅里叶变换提取幅度谱以分离低频分量；依据该低频分量，再利用多通道窄带FX-Newton算法生成低频分量的反相控制量，实现船舶低频震荡传输信号主动振动抵消；结合船舶六自由度运动参数，分步骤进行时延、相位及幅度补偿，实现船舶低频震荡传输信号控制。测试结果表明，该方法能将低频分量有效约束在10.5 Hz以下，主动振动抵消后信号振幅大幅下降且差异缩小，相位畸变系数均低于允许上限（0.05），控制后信号幅值显著收敛并趋于平稳，有效抑制了低频震荡干扰，提升信号传输稳定性，满足船舶导航、勘探等场景对信号的严苛需求。
To reduce the interference caused by low-frequency vibrations of ships on transmitted signals and ensure the stable transmission of communication and navigation signals, a ship low-frequency vibration transmission signal control technology is proposed. The low-frequency vibration transmission signals of the ship are collected, and the discrete Fourier transform is used to extract the amplitude spectrum to separate the low-frequency components; Based on these low-frequency components, the FX-Newton algorithm is used to generate the inverse control quantities for the low-frequency components, achieving active vibration cancellation of the ship's low-frequency vibration transmission signals; combined with the ship's six degrees of freedom motion parameters, delay, phase, and amplitude compensation are performed in steps to achieve control of the ship′s low-frequency vibration transmission signals. Test results show: This method effectively constrains the low-frequency components below 10.5 Hz. After active vibration cancellation, the signal amplitude significantly decreases, and the phase distortion coefficient remains below the permissible upper limit (0.05). The controlled signal amplitude converges significantly and stabilizes, effectively suppressing low-frequency oscillation interference and enhancing signal transmission stability, thereby meeting the stringent requirements for signals in ship navigation and exploration scenarios.
2025,47(18): 175-179 收稿日期：2025-3-11
DOI：10.3404/j.issn.1672-7649.2025.18.029
分类号：U665.12
基金项目：2025年度广西高校中青年教师科研基础能力提升项目（2025KY1532）
作者简介：洪东（1985 – ），男，硕士，副教授，研究方向为软件工程、大数据技术、模型构建及算法
参考文献：
[1] 杨晨, 余一平, 樊陈, 等. 基于已知激励响应的低频振荡信息在线辨识[J]. 电力自动化设备, 2023, 43(1): 193-201.
YANG C, YU Y P, FAN C, et al. Online identification of low-frequency oscillation information based on known excitation response[J]. Electric Power Automation Equipment, 2023, 43(1): 193-201.
[2] 段子越, 孟永庆, 宋博阳, 等. 基于模块化多电平矩阵换流器的柔性低频输电系统大信号稳定性分析[J]. 高电压技术, 2023, 49(9): 3741-3751.
DUAN Z Y, MENG Y Q, SONG B Y, et al. Large signal stability analysis of flexible low frequency transmission system based on modular multilevel matrix converter[J]. High Voltage Engineering, 2023, 49(9): 3741-3751.
[3] 曹以龙, 张旭源, 陈博, 等. 基于波形变换的超低频正弦电源控制策略研究[J]. 电力电子技术, 2023, 57(3): 56-60.
CAO Y L, ZHANG X Y, CHEN B, et al. Research on control strategy of ultra-low frequency sinusoidal power supply based on waveform transformation[J]. Power Electronics, 2023, 57(3): 56-60.
[4] 王轶楷, 谢锐. 基于CEEMDAN和改进小波模极大值的高低频混合信号去噪算法[J]. 中北大学学报(自然科学版), 2023, 44(4): 366-373.
WANG Y K, XIE R. High and low frequency mixed signal denoising algorithm based on CEEMDAN and improved wavelet modulus maximum[J]. Journal of North University of China (Natural Science Edition), 2023, 44(4): 366-373.
[5] 姜鑫, 易皓, 卓放, 等. 基于直流电压同步的构网型变流器低频振荡分析与阻尼控制[J]. 电力系统自动化, 2024, 48(16): 30-39.
JIANG X, YI H, ZHUO F, et al. Low-frequency oscillation analysis and damping control for grid-forming converters based on dc voltage synchronization[J]. Automation of Electric Power Systems, 2024, 48(16): 30-39.
[6] 聂彬, 赵英亮, 聂鹏飞, 等. 基于线性Radon变换的超声混叠信号分离研究[J]. 中北大学学报(自然科学版), 2023, 44(3): 299-304+324.
NIE B, ZHAO Y L, NIE P F, et al. Separation study of ultrasonic mixed signals based on linear radon transform[J]. Journal of North University of China (Natural Science Edition), 2023, 44(3): 299-304+24.
