基于数据融合的光散射法与β射线粉尘检测技术研究
Study on light scattering method based on data fusion and β-ray dust detection technology
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摘要: 使用光散射法长时间测量粉尘浓度时,会因光学镜头被污染造成测量精度下降。在分析光散射与β射线检测粉尘原理的优缺点基础上,提出一种基于光散射与β射线法相融合的粉尘检测技术,使用卡尔曼滤波数据融合算法提高测量精度,并采用Matlab软件进行数值模拟分析。结果表明:卡尔曼滤波数据融合算法使样本数据方差减小55.5%;融合算法测量值相对平均误差ξ≤ 10.00%,比单一使用光散射法的相对平均误差减小3.16%。Abstract: When the light scattering method is used to measure the dust concentration for a long time,the measurement accuracy will be decreased due to the pollution of the optical lens. Based on the analysis of the advantages and disadvantages of the principle of light scattering and β-ray dust detection,a dust detection technology based on the fusion of light scattering and β-ray method was proposed. Kalman filter fusion algorithm was used to improve the measurement accuracy,and Matlab software was used for numerical simulation analysis. The results show that the Kalman filter data fusion algorithm can reduce the error variance of sample data by 55. 5%. The relative average of the fusion algorithm is ξ≤ 10. 00%,which is 3. 16% less than that of the single light scattering method.