针对光子相关光谱颗粒测量法在测量超细纳米颗粒时,容易受噪声影响,导致拟合误差较大的问题,提出了一种基于奇异值分解的光子相关光谱滤波方法。其处理步骤为:利用颗粒系的光强自相关函数数据构造Hankel矩阵H;对矩阵进行奇异值分解;根据奇异值的大小分布,确定噪声级别和重建参数r;从重建矩阵H1中提取经滤波后的光强自相数据,再通过传统方法进行拟合,得到颗粒的粒径分布。实验中采用30nm标准乳胶球单分散颗粒系,以及30nm和100nm标准乳胶球双分散颗粒系进行实验对比。结果证明:基于奇异值分解的光子相关光谱滤波法有效地提高了测量准确性。 Aiming at the problem that the photon correlation spectroscopy particle measurement method is very sensitive to noise when measuring ultrafine nanoparticles, the fitting error is large. A photon correlation spectral filtering method based on singular value decomposition is proposed. The processing steps are as follows: constructing a Hankel matrix H by using the light-intensity autocorrelation function data of the particle system; performing singular value decomposition on the matrix; determining the noise level and the reconstruction parameter r according to the size distribution of the singular values; After the light intensity of self-phase data, and then fitted by traditional methods to get the particle size distribution. Experiments using 30nm standard latex ball monodisperse particles, as well as 30nm and 100nm standard latex ball double-dispersion particles for experimental comparison. The results show that the photon correlation spectroscopy filter based on singular value decomposition effectively improves the measurement accuracy.