基于数据挖掘的工业锅炉故障监测检测研究

Research on Industrial Boiler Fault Monitoring and Detection Based on Data Mining

数据挖掘是一种从大规模数据集中发现有用信息和模式的过程,以自动或半自动的方式分析数据,从中提取有价值的知识、模式、趋势和规律。工业锅炉作为一种重要的热能动力设备,是工业生产中不可或缺的设备之一,主要为工业生产提供热源及动力源,目前工业锅炉的设计正向着节能化、高效化、智能化、模块化的方向发展。工业锅炉的长期使用运行,难免会出现各种各样的故障,故障出现会影响锅炉运行以及工业生产安全,甚至会造成严重的人员伤亡及财产损失,因此需要通过现代化技术手段对工业锅炉运行状态进行实时监测,出现故障时及时采取处理措施。介绍工业锅炉的组成以及常见故障基础上,探讨数据挖掘流程以及基于数据挖掘的工业锅炉故障监测检测方法,能够提升工业企业的锅炉安全运行效率以及监管水平。

Data mining is a process of discovering useful information and patterns from large-scale data sets,analyzing the data in an automatic or semi-automatic way,and extracting valuable knowledge,patterns,trends and rules from it.As an important thermal power equipment,industrial boiler is one of the indispensable equipment in industrial production,mainly to provide heat source and power source for industrial production,the current design of industrial boiler is towards the direction of energy saving,high efficiency,intelligent,modular development.Long-term operation of industrial boilers,it is inevitable that there will be a variety of failures,failure will affect the boiler operation and industrial production safety,and even cause serious casualties and property losses,so it is necessary to carry out real-time monitoring of the operating status of industrial boilers through modern technical means,and take timely treatment measures when failure occurs.Based on the introduction of the composition and common faults of industrial boilers,the data mining process and the fault monitoring and detection method of industrial boilers are discussed based on data mining,which can improve the safe operation efficiency and supervision level of industrial enterprises.