叶方平, 方朝阳, 徐显金, 李秀红, 袁建明. 基于图像透光率的粉尘浓度测量算法研究[J]. 应用光学, 2022, 43(3): 496-502. DOI: 10.5768/JAO202243.0303005
引用本文: 叶方平, 方朝阳, 徐显金, 李秀红, 袁建明. 基于图像透光率的粉尘浓度测量算法研究[J]. 应用光学, 2022, 43(3): 496-502. DOI: 10.5768/JAO202243.0303005
YE Fangping, FANG Chaoyang, XU Xianjin, LI Xiuhong, YUAN Jianming. Dust concentration measurement algorithm based on image transmittance[J]. Journal of Applied Optics, 2022, 43(3): 496-502. DOI: 10.5768/JAO202243.0303005
Citation: YE Fangping, FANG Chaoyang, XU Xianjin, LI Xiuhong, YUAN Jianming. Dust concentration measurement algorithm based on image transmittance[J]. Journal of Applied Optics, 2022, 43(3): 496-502. DOI: 10.5768/JAO202243.0303005

基于图像透光率的粉尘浓度测量算法研究

Dust concentration measurement algorithm based on image transmittance

  • 摘要: 为了实时在线监测颗粒物料在装卸和运输过程中所产生粉尘的浓度,提高粉尘浓度测量结果的精确性与可靠性,提出了一种基于图像透光率特征值计算的粉尘浓度测量算法。通过搭建粉尘浓度视觉测量实验平台,采集粉尘图像,再提取粉尘图像的透光率特征,以暗通道理论为基础,结合图像饱和度与亮度信息对粉尘图像透光率值进行计算,并采用多项式拟合的方式建立了粉尘浓度与图像透光率之间的映射关系,实现了粉尘浓度的高效率、高精度测量。研究结果表明:该算法不仅能有效地测量出粉尘浓度,且平均相对误差仅为7.77%,精确度得到有效提高,测量范围更大。

     

    Abstract: In order to monitor the dust concentration of particle materials in the process of handling and transportation online in real time and improve the accuracy and reliability of dust concentration measurement results, an improved dust concentration measurement algorithm based on the eigenvalue calculation of image transmittance was proposed. First, the experimental platform of vision measurement of dust concentration was established, and the dust images were collected. Then, the characteristics of transmittance of dust images were extracted. Based on the dark channel theory, the image transmittance of dust images was calculated by combining the information of image saturation and image brightness. Finally, the mapping relationship between dust concentration and image transmittance was established by the polynomial fitting method. And the high-efficiency and high-precision measurement of dust concentration was realized. The research results show that the proposed algorithm can not only effectively measure the dust concentration, but also the average relative error is only 7.77%. The accuracy is effectively improved and the measurement range is further expanded.

     

/

返回文章
返回