摘要
在传感器性能测试中,采样的信号经常受到各种噪声的干扰和污染,不能准确反映设备的运行状态,不宜直接用于数据处理与分析。为了对试验数据进行去噪预处理,根据具体传感器性能试验数据的特点,运用小波变换方法,确定了适合的小波去噪参数。引入重构因子比较几种常用的小波基,应用Matlab对仿真信号进行小波阈值去噪处理,依据平滑度确定了分解层数,为传感器性能试验数据预处理提供了的一种有效的小波阈值去噪方法。
In sensor performance test, signal of sampling is often subjected to interference and pollution of all kinds of noise , which can not accurately reflect operating status of equipment, and should not be directly used for data processing and analysis. In order to carry out de-noise preprocessing on test datas, according to characteristics of specific sensor test data, using wavelet transform method,preprocessing wavelet determine approperate wavelet denoising parameters. Introduce reconstruction factor,compare several kinds of commonly used wavelet basis,and then decomposition level is determined according to smoothness, simulation signal is processed by wavelet threshold de-noising use Matlab, which provide an effective wavelet threshold de-noising method for character test data preprocessing of sensor.
出处
《传感器与微系统》
CSCD
北大核心
2014年第6期143-146,共4页
Transducer and Microsystem Technologies
关键词
小波去噪
阈值
重构因子
平滑度
wavelet de-noising
threshold
reconstruction factor
smoothness
