基于小波去噪的称重雨量数据分析

Analysis of Weighing Rainfall Data based on Wavelet Denoising

称重雨量计在测量降雨过程中,存在风、温度等许多因素的干扰,导致最后测出的数据质量不理想,算出的降雨量误差过大。为了提高数据的准确性,结合噪声干扰的特点,采用小波分析方法对其进行滤波去噪处理。随机选择一天的称重雨量数据,通过对比分析确定了小波基函数、分解层数、阈值选取方法和阈值重调方法,并结合翻斗雨量计数据进行验证,结果表明,小波去噪方法能有效去除叠加在称重雨量数据中的噪声,去噪后的数据变得更加平滑,信噪比明显提高。同时,该算法易于实现,计算量小,在称重雨量数据的除噪中具有较高的实用价值。

Weighing rain gauge in measuring rainfall,there are many factors interfere with the wind,temperature and so on,leading to the final measured data quality is not ideal,the calculated rainfall error is too large.In order to improve the accuracy of the data,combined with the characteristics of noise interference,wavelet analysis method is used to filter the noise.This paper randomly selected weighing rainfall data,through comparative analysis to determine the wavelet function,the number of decomposition levels,the threshold selection method,and the threshold returning method,and combined with tipping-bucket rain gauge data validation,the result shows that:the wavelet denoising method can effectively remove the noise in the weighing rainfall data,so that the data becomes smoother,and the signal to noise ratio significantly improved after denoising.Meanwhile,the algorithm is easy to implement,small amount of calculation,which is highly applicable in weighing the rainfall data of denoising.