基于智能监控的环保设施脱硫设备故障预警方法研究

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关键词：动态径向基函数（RBF）神经网络；动态RBF辨识器；环保设施；脱硫设备中图分类号：X773 文献标识码：A 文章编号：1008-9500（2025）05-0241-03DOI： 10.3969/j.issn.1008-9500.2025.05.073

Abstract： Thedesulfurizationequipment of environmental protection facilitiesare thecoredevices forcontroling flue gas pollution andachieving eficientremoval of sulfurdioxide in thechemical industry.This paper analyzes the keyfault modes during the operation of imestone gypsum wet flue gas desulfurization equipment and their impact on system performance， researchesonreal-time fault warning method based on dynamic Radial Basis Function （RBF）neural network and dynamic RBFidentifier，andpropossanintellgentmonitoringtechnologytatintegateseal-timemonitoing，onlinearidntification， anddynamic modeling，aiming toimprovethe operational safetyandfault predictionaccuracyof desulfurization equipment.

Keywords：dynamic Radial Basis Function （RBF）neural network;dynamic RBF identifier;environmental protection facilities; desulfurization equipment

二氧化硫（ SO2 ）是主要大气污染物之一，随着全球工业化进程加速，其高效脱除技术受到广泛关注。（剩余3185字）