閱讀全文 | |
篇名 |
Research on Underwater Noise Features Based on Spectrum Analysis and Welch Algorithm
|
---|---|
並列篇名 | Research on Underwater Noise Features Based on Spectrum Analysis and Welch Algorithm |
作者 | Hui Zhou、Biyuan Yao、Kun Ye、Guiqing Li、Jin Guo |
英文摘要 | To explore the characteristics of underwater noise, we analyze the power spectrum and frequency of underwater noise with the sequence diagram, the period diagram, the density diagram and improved welch algorithm according to the 5-day noise data by root mean square. The results show that, first of all, spectrum analysis and welch algorithm simplify the calculation process and adapt to the impulsiveness and randomness of noise. Secondly, adopting different window functions in welch power spectrum estimation improves the spectral resolution of underwater noise prediction, which is insensitive to noise. Thirdly, in the spectrum analysis, the accuracy of experimental results from welch algorithm obviously outperforms sequence diagram, periodic diagram and density diagram. Compared with periodic diagram and density diagram, the improved welch algorithm will obtain smoother power spectrum estimation, reducing the resolution and random error of noise frequency in the segmentation process. Finally, when the number of sites is greater than 10, our simulation results are more accurate than that with periodic diagram method. |
起訖頁 | 713-721 |
關鍵詞 | Underwater noise’ features、Sequence diagram、Periodogram、Density graph、Welch algorithm |
刊名 | 網際網路技術學刊 |
期數 | 202105 (22:3期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
|
QR Code | |
該期刊 上一篇
| A Static Gesture Recognition Method Based on Improved SURF Algorithm and Bayesian Regularization BP Neural Network |