用小波变换提高散斑能见度光谱测量法的灵敏度

摘要

On the basis of analyzing the noise characteristics of passive layer particles, a square-wave signal with low SNR was simulated. Based on the variation law, a Mallat fast algorithm was used to analyze the wavelet signals with low SNR and analyzed the characteristics of the noise. An algorithm designed to suppress interference noise in the passive layer particle temperatures. The simulation on the designed algorithm shows that the algorithm can filter the noise in the signal. By constructing a roller experiment device,the particle temperature of the passive layer of the roller is measured, and the measurement data is analyzed. The change of internal particle temperature state is effectively measured, and the practicality of denoising the passive layer particle temperature signal using wavelet transform is proved.%在分析被动层颗粒温度含噪特点的基础上模拟了低信噪比的方波信号，根据变化规律，采用Mallat快速算法分析低信噪比的方波信号，并根据噪声分布特性设计了用于抑制被动层颗粒温度中干扰噪声的算法。对所设计算法进行仿真实验，结果表明，该算法可以最大限度地滤除信号中的噪声。通过搭建滚筒实验装置，测量滚筒被动层的颗粒温度，对测量数据进行分析，有效地测出了内部颗粒温度状态变化，表明了小波变换能有效提高测量被动层颗粒温度的信噪比。