# Harmonic Detection Method Based on Parameter Optimization VMD-IWT Combined Noise Reduction
## 6 Conclusions  
Addressing the issues of insufficient accuracy and noise interference in existing harmonic detection methods, this paper introduces a novel harmonic detection approach that integrates parameter optimization with VMD and improved wavelet threshold denoising. The rime optimization algorithm is utilized to optimize the VMD parameters, thereby enhancing the signal decomposition performance. The effective component is selected using the correlation coefficient method, and then, combined with the improved wavelet threshold, the noisy effective component is denoised, and the signal is reconstructed. Finally, the Hilbert transform is employed to detect the amplitude and frequency information of the harmonic signal, effectively achieving accurate harmonic signal detection in power systems. Through simulation experiment analysis, the following conclusions are drawn:  
1. By utilizing the RIME optimization algorithm to optimize the VMD parameters (\(K\),\(\alpha\)), the issue of manually setting the \(K\) and \(\alpha\) values in the traditional VMD algorithm is effectively addressed. This approach achieves optimal signal decomposition, reduces the VMD decomposition error, demonstrates stronger adaptability, and has a faster optimization speed compared to PSO and WOA algorithms. 2. By introducing the Pearson correlation coefficient and improving wavelet threshold denoising, the effective signal and noise signal can be effectively separated from the mixed signal, while retaining the original characteristics of the signal. This improves the overall noise robustness of the algorithm, making it suitable for harmonic signal denoising. 3. In comparison with EMD, WT, and VMD methods, the proposed approach exhibits a remarkable noise reduction effect and demonstrates accurate detection of harmonic amplitude and frequency even in high-noise environments. Its detection performance surpasses that of traditional methods, showcasing significant advantages in accuracy. The method presented in this paper has hitherto been applied solely to simulations and harmonic data of a specific type of power equipment. Moving forward, the approach will be extended to monitoring data of diverse power equipment to explore the characteristics of more extensive power equipment monitoring signals. Taking into account the actual operational environment of power systems, future research endeavors aim to enhance the real-time processing capabilities of the algorithm and investigate the feasibility of hardware implementation, thereby fulfilling the requirements of real-time online monitoring. These studies are anticipated to foster the further evolution of harmonic detection technology and provide more robust technical underpinnings for the stable and secure operation of power systems. Conceptualization, J.X. ; methodology, J.X. ; software, J.X. ; validation, J.X. and W.H. ; writing--original draft preparation, J.X. and W.H. ; writing--review and editing, H.M.; visualization, W.H. All authors have read and agreed to the published version of the manuscript. This research is supported by the Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture (GJZJ20220802), and in part by the Doctoral Scientific Research Foundation of Beijing University of Civil Engineering and Architecture (ZF15054). Not applicable.