摘要
针对传统Prony算法易受噪声干扰且同一区域内多路电能质量信号存在相关性的特点,文中提出了一种基于多路信号联合去噪的Prony谐波检测算法,实现在较强噪声条件下的谐波准确检测。首先,采用中心频率法和轨迹相似度法改进多元变分模态分解(MVMD)算法;其次,利用改进的MVMD算法联合分解相关联的多路信号,提取出主导模态分量并重组为适宜Prony分析的稳定信号;最后,对稳定信号进行Prony分析得到初步的谐波参数,通过阈值筛选和人工鱼群全局寻优,得到准确的谐波检测参数。仿真实验表明,改进的MVMD去噪算法的输出信噪比为37.3,高于VMD去噪法(33.2)和小波去噪法(32.8),去噪效果更优;文中算法谐波检测结果的误差总体小于传统Prony算法,具有谐波检测准确度高、同时计算多路信号的特点。
Aiming at the characteristics that the traditional Prony algorithm is easily interfered by noise and there is correlation between multiple power quality signals in the same area, in this paper, the Prony harmonic detection algorithm based on multi-channel signal joint denoising is proposed to achieve the accurate detection of harmonics under strong noise conditions. Firstly, the central frequency method and trajectory similarity method are used to improve the multivariate variational mode decomposition algorithm.Then, the improved MVMD algorithm is used to jointly decompose the associated multi-channel signals, extract the dominant mode components, and reorganize them into stable signals suitable for Prony harmonic analysis. Finally, Prony analysis is performed on the stable signals to obtain preliminary harmonic parameters, and the threshold screening and artificial fish swarm global optimization are carried out to obtain the accurate harmonic detection parameters. Simulation experiments show that the output signal-noise ratio of the improved MVMD denoising algorithm is 37.3, which is higher than VMD denoising method(33.2) and wavelet denoising method(32.8),and the denoising effect is better;The error of the harmonic detection result of the algorithm in this paper is generally less than that of the traditional Prony algorithm. It possesses the characteristics of high harmonic detection accuracy and simultaneous calculation of multi-channel signals.
作者
宋朝霞
李开成
贺才郡
董宇飞
范伟欣
Song Zhaoxia;Li Kaicheng;He Caijun;Dong Yufei;Fan Weixin(School of Electrical and Electronic Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《电子测量技术》
北大核心
2022年第21期47-53,共7页
Electronic Measurement Technology
基金
国家自然科学基金(52077089)项目资助。
