摘要
为实现极低信噪比下管道泄漏声波信号去噪,基于多通道信号的相关性,提出使用相关系数矩阵筛选变分模态分解所得模态分量。针对不同工况的泄漏信号,提出不依赖真值的去噪质量评价指标,将其作为多目标灰狼优化算法目标函数,基于Pareto前沿获取变分模态分解的最佳模态数K和惩罚因子η,实现多工况自适应去噪。搭建了输气管道泄漏多工况实验平台,在不同工况、不同输入信号信噪比(-8~4 dB)下验证所提方法的去噪效果。结果表明,该方法能有效抑制噪声,-8 dB时去噪信号信噪比提升2.84 dB以上。对比基于单目标优化的去噪方法,-8 dB下新方法的信噪比和相关系数分别提高了3.65 dB和31.26%。
To achieve denoising of pipe leak acoustic signal under the conditions of extremely low signal-to-noise ratio,based on the signal correlation among multiple channels,a correlation coefficient matrix is presented to determine the modes obtained by using the variational mode decomposition.For the leak signals under different conditions,the quality evaluation index for denoising that does not rely on the real value is presented to use it as the object function of the multi-objective grey wolf optimization algorithm.The best mode number K and penalty factorηof the variational mode decomposition are determined according to the Pareto front,achieving adaptive denoising under multiple conditions.An experimental rig of gas pipe leak under multiple conditions is established to evaluate the effectiveness of the proposed method under multiple conditions and with different signal to noise ratios(-8~4 dB)of input signals.The results show that this method can effectively suppress noises.Even in the case of-8 dB,the signal-to-noise ratio of denoised signals is amplified by more than 2.84 dB.Compared with the method based on single-objective optimization,at-8 dB,the signal-to-noise ratio and correlation coefficient of the new method are increased by 3.65 dB and 31.26%,respectively.
作者
薛生
谢晓贤
郑晓亮
王强
Xue Sheng;Xie Xiaoxian;Zheng Xiaoliang;Wang Qiang(School of Safety Science and Engineering,Anhui University of Science and Technology,Huainan 232001,China;Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining,Anhui University of Science and Technology,Huainan 232001,China;School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2024年第3期227-239,共13页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金重点项目(51934007)
十三五国家重点研发计划(2018YFF0301000)项目资助。
关键词
管道泄漏
自适应去噪
相关系数矩阵
多目标灰狼优化
PARETO
pipe leak
adaptive denoising
correlation coefficient matrix
multi-objective grey wolf optimization
Pareto