Research on Industrial Boiler Fault Monitoring and Detection Based on Data Mining
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,in-dustrial boiler is one of the indispensable equipment in industrial production,mainly to provide heat source and power source for industrial pro-duction,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 in-dustrial production safety,and even cause serious casualties and property losses,so it is necessary to carry out real-time monitoring of the op-erating status of industrial boilers through modern technical means,and take timely treatment measures when failure occurs.Based on the in-troduction 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 enter-prises.
data miningdeep learningindustrial boilerfault monitoring
万方数据
维普
