摘要
基于炉膛火焰温度不同,与之相对应通过CCD摄取的炉膛火焰图像颜色也不同,提出了一种检测炉膛火焰温度的方法。将获取的炉膛火焰图像RGB模型转换为HSI颜色值,用H、S值作为BP神经网络输入,通过样本图像训练后,拟合H、S与温度T的非线性关系,计算得到炉膛火焰温度值。实验表明,计算温度与实际温度良好相符。
Based on the fact that different furnace flame images captured by the CCD correspond with the different temperature of the furnace flame, a temperature measurement method of the furnace flame images is presented in this paper.Transforming the RGB color model images captured by the CCD into HSI color model images, training this neural network and approximating the nonlinear relationship between the color and the temperature based on BP neural network, the temperature is calculated.The experimental results prove that the calculating temperature accords with the actual one and show that the method is feasible.
出处
《中国测试技术》
CAS
2005年第2期50-52,共3页
CHINA MEASUREMENT & TESTING TECHNOLOGY
