采用激光诱导击穿光谱技术对炉渣中的Ca、Mg含量进行了定量分析.由于炉渣成分复杂,建立的一元回归关系式往往得不到理想的结果,这时需要考虑多个自变量的回归分析问题.为了分析炉渣中Ca、Mg元素的含量,将炉渣中Mg、Ca、Fe、Si、Al的原子谱线强度以及Mg、Ca的离子谱线强度作为输入向量.由于不同谱线强度相差过大时,会使在计算出的权重系数中不同谱线所占的比重大不相同.为了消除不同谱线强度差距过大的影响,对光谱强度进行标准化处理,把所有谱线强度的值放在了一个相似的范围.综合对比分析了非线性多元函数定标、BP神经网络定标以及径向基网络(RBF神经网络)定标在炉渣成分分析中的作用,并重点分析了RBF神经网络定标相对于传统非线性定标方法的优势.
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