| 基于雨声识别的雨量测量方法 |
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| 引用本文： | 丁苑,行鸿彦.基于雨声识别的雨量测量方法[J].气象科技,2019,47(1):35-40. |
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| 作者姓名： | 丁苑 行鸿彦 |
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| 作者单位： | 南京信息工程大学气象灾害预报预警与评估协同创新中心;南京信息工程大学江苏省气象探测与信息处理重点实验室 |
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| 基金项目： | 国家自然科学基金（61671248， 41605121）、江苏省重点研发计划项目（BE2018719）和江苏省“信息与通信工程”优势学科计划资助 |
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| 摘 要： | 针对传统雨量测量耗时长,维护不方便的问题,本文在分析声信号识别技术的基础上,提出了基于雨声识别的雨量测量方法,模拟人耳听觉中对频域划定的非线性性和对同一频率群声信号作叠加评价的机理,将傅里叶变换后的能量谱通过梅尔(Mel)滤波器,提取雨声的梅尔频率倒谱系数(MFCC)作为雨声信号的特征向量。在此基础上,构建一个三层BP神经网络,将归一化后的样本数据用于神经网络训练,最后将测试样本用于对雨量的识别。试验结果表明,在少量样本训练的基础上神经网络即能有效识别雨量大小,为声信号识别技术应用于更为精准的雨量测量提供了理论依据。
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| 关 键 词： | 雨声信号 特征提取 BP神经网络 雨量识别 |
| 收稿时间： | 2018/2/9 0:00:00 |
| 修稿时间： | 2018/10/23 0:00:00 |
Rainfall Measurement Based on Rain Sound Recognition |
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| Ding Yuan and Xing Hongyan.Rainfall Measurement Based on Rain Sound Recognition[J].Meteorological Science and Technology,2019,47(1):35-40. |
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| Authors: | Ding Yuan and Xing Hongyan |
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| Abstract: | Aiming at the problem of long time consuming and inconvenient maintenance of traditional rainfall measurement, based on the analysis of acoustic signal recognition technology, this paper proposes a rainfall measurement method based on sound recognition to simulate the non linearity of frequency domain demarcation and the mechanism of superimposing acoustic signals in the same frequency group in human ears. The Fourier transformed energy spectrum is passed through a Mel filter, and then the Mel Frequency Cepstral Coefficients of the rain sounds are extracted as the eigenvector of rain sound signals. On this basis, a three layer BP neural network is constructed, and the normalized sample data are used for neural network training. Finally, the test samples are used to identify the rainfall. Experimental results show that neural network can effectively identify the amount of rainfall on the basis of a small amount of sample training, which provides a theoretical basis for the application of acoustic signal recognition technology for more accurate rainfall measurement. |
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| Keywords: | rain signal feature extraction BP neural network rainfall identification |
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