基于AT的锅炉燃烧温度场重建算法研究

Research on reconstruction algorithm of boiler combustion temperature field based on AT

为了监控燃烧状态,实现炉内温度分布的测量,提出了一种基于声学层析成像法(AT)的三层递进式网格化温度场重建算法.该算法在最小二乘法(LSM)确定稀疏网格温度信息的基础上,利用最小二乘支持向量机(LSSVM)建立温度场的细密网格模型,同时为了进一步提高重建精度,LSSVM重建模型的参数通过差分进化算法(DE)进行整定(简称为LLD算法),从而建立整个待测温度场的细致温度描述.通过对东方锅炉厂提供的三种不同类型的温度场进行重建,结果及误差分析表明LLD算法可以对待测燃烧区域温度分布信息进行全局性的描述,能实现温度场的高精度重建.

In order to monitor the combustion state and measure the temperature distribution in the furnace,a three-layer progressive grid temperature field reconstruction algorithm based on acoustic tomography(AT)is proposed.The algorithm first computes the sparse grid temperature information with the least squares method(LSM),and then uses the least squares support vector machine(LSSVM)to establish a fine grid model for the temperature field.In order to further improve the reconstruction accuracy,the parameters of the LSSVM reconstruction model are tuned by the differential evolution algorithm(DE)(Referred to as the LLD algorithm)to establish a detailed temperature description of the entire measured temperature field.Through the reconstruction of three different types of temperature fields provided by Dongfang Boiler Industry Group,the results and error analysis show that the LLD algorithm can describe the temperature distribution information of the measured combustion zone globally and achieve high-precision reconstruction of the temperature field.