基于模糊神经网络的COD软测量技术的研究

摘要

Monitors the water quality in view of the present sewage treatment process in the equipment and the technology is quite backward, the primitive laboratory chemical examination method will create the serious time lag. Cannot prompt feedback information and guarantee product quality, possibly create some serious consequences. Has used one kind based on the fuzzy neural network (FNN) the soft measuring technique method, uses the neural network fully misalignment mapping ability, learning capability, parallel processing ability and the fault -tolerant ability, as well as superiority and so on fuzzy logic system processing uncertainty ability. Both organic synthesis, composes in the function is more perfect and the formidable fuzzy neural network, carries on the modelling by this, realizes to the sewage treatment in the unpredictable water quality target -chemical oxygen demand (COD) online monitor.%针对现在污水处理过程中监测水质的设备与技术比较落后,原始的实验室化验方法会造成时间的严重滞后,不能及时的反馈信息保证产品的质量,可能会造成一些严重的后果；采用了一种基于模糊神经网络(FNN)软测量技术的方法,充分利用神经网络的非线性映射能力、学习能力、并行处理能力和容错能力,以及模糊逻辑系统处理不确定性的能力等优势；将两者有机结合起来,组成在功能上更加完善和强大的模糊神经网络,以此进行建模,实现对污水处理中难测水质指标一化学需氧量(COD)的在线监测.