多尺度状态监测方法在灰污监测中的应用  

Application of the Multi-dimension State Monitoring Method in the Monitoring of Ash and Fouls

作　　者：刘继伟[1] 曾德良[2] 刘吉臻[2] 李青[2] 

机构地区：[1]天津理工大学中环信息学院自动化工程系,天津300380 [2]华北电力大学工业过程测控新技术与系统北京市重点实验室,北京102206

出　　处：《热能动力工程》2013年第6期590-595,658-659,共6页Journal of Engineering for Thermal Energy and Power

基　　金：国家自然科学基金重点项目(51036002);国家科技支撑计划(2011BAA04B03)

摘　　要：针对状态参数随时间流逝变化的复杂系统,提出一种基于大数据、异步信息融合的多尺度状态监测方法,构建对象状态参数反映设备运行状态。通过对某机组锅炉辐射受热面灰污程度检测的实例分析,利用所提出的多尺度状态监测方法,构建了污染度指数,消除了煤破碎变化等噪声对状态监测结果的干扰,有效反映了受热面积灰程度,取得了良好的效果。In the light of complex systems of which the state parameters was changing with time,put forward was a multi-dimensional state monitoring method based on the big data and asynchronous information fusion with the state parameters of the object being established to reflect the operating state of the equipment items. Through a case analysis of the ash deposition and fouling degree of the heating surfaces of a utility boiler,by employing the algorithm in question,a dual model and data fusion were used to enhance the modeling precision and multi-dimensionally analyze the noise caused by a change in the quality of coal when it is filtered. On this basis,the pollution degree index was established to effectively reflect the extent of the ash deposition on the heating surfaces.

关 键 词：大数据 状态监测 灰污检测 辐射受热面 

分 类 号：TK228[动力工程及工程热物理—动力机械及工程] O242[理学—计算数学]