工业锅炉智慧检修维保系统研究  

Research onintelligent maintenance system of industrial boiler

作　　者：刘利亚 吴爽 万江 王胜利 LIU Liya;WU Shuang;WAN Jiang;WANG Shengli(Beijing Capital Airport Power and Energy Co.,Ltd.)

机构地区：[1]北京首都机场动力能源有限公司

出　　处：《区域供热》2022年第5期41-50,116,共11页District Heating

摘　　要：目前企业对工业锅炉设备的管理主要采取传统的周期性维保和故障检修方式,对设备状态的预判性不足,并且传统的故障检修主要依据人工经验排查故障点,效率低且故障处置的时效性无法得到保障。尝试将新一代信息技术与锅炉设备的检修维保工作相结合,利用大数据、物联网等技术,搭建智慧检修维保系统的基本架构,利用历史运行数据及典型故障处置信息构建数据模型,以便更准确地分析锅炉设备的全生命周期过程。针对设备维护保养和突发故障检修重点工作,提出了基于案例推理(Case-Based Reasoning, CBR)的故障诊断方法及基于设备全生命周期的状态维护方案,通过数据挖掘技术不断提升锅炉系统故障预测及诊断、健康状态评估能力,为故障处置的及时性和维护保养的精准性提供参考,对进一步提升工业锅炉系统安全性能具有重要意义。At present, enterprises mainly adopt the traditional periodic maintenance and troubleshooting methods for the management of industrial boiler equipment, and the prediction of equipment status is insufficient.Moreover, the traditional troubleshooting is mainly based on manual experience to identify fault points, which is inefficient and the timeliness of fault disposal cannot be guaranteed.This paper attempts to integrate new information technology with the maintenance of boiler equipment, build the basic architecture of intelligent maintenance system by using big data, IoT and other technologies, and build a data model by historical operation data and typical fault handling information, so as to analyze the whole life cycle process of boiler equipment more accurately.Aiming at the key tasks of equipment maintenance and sudden fault repair, this paper puts forward the fault diagnosis method based on case-based reasoning(CBR) and the state maintenance scheme based on the whole life cycle of equipment, and continuously improves the ability of boiler system fault prediction and diagnosis and health state evaluation through data mining technology, so as to provide reference for the timeliness of fault disposal and the accuracy of maintenance.It is of great significance to further improve the safety performance of industrial boiler system.

关 键 词：智慧检修维保 数据挖掘 故障诊断 状态维护 

分 类 号：TK221[动力工程及工程热物理—动力机械及工程]