摘要
针对高斯函数温度场重建算法在复杂温度场图像重建中精度较低问题,提出一种基于高斯函数级数与正则化方法相结合的复杂温度场重建算法,通过在温度场重建中加入火焰先验信息,实现在较少测量数据下炉内复杂温度场的重建。仿真结果表明,该算法比高斯函数温度场重建算法具有较高精度和抗干扰能力,而重建速度相当,可望将该算法用于电站锅炉炉膛的二维温度场重建。
Because the image reconstruction algorithm by Gaussian functions has a low accuracy in complex temperature field, a new algorithm is proposed. The new algorithm is based on combination of Gaussian functions series and regularization method. The new reconstruction of complex temperature field can be realized with fewer measured data by employing priori flame information. Simulation results show that the new algorithm has a higher accuracy and anti-jamming ability in comparison with that of Gaussian functions, yet with a same speed in reconstruction. And therefore it is expected to be used in the 2-D temperature field reconstruction for power plant boilers.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2004年第5期212-215,220,共5页
Proceedings of the CSEE
基金
辽宁省教育厅科学研究计划项目(202023083)
