大数据处理技术在海上风电机组预知维护中的应用

Application of Big Data Processing Technology in Predictive Maintenance of Offshore Wind Turbine

海上风电机组目前的主要检修模式是定检及事后维修,在制定维修策略时还会受到风、浪、潮汐及维修船只等特殊因素的影响,运行维护更加困难。同时风电机组装有大量传感器,其数据可以直观地反映出各个设备及系统的实时状态。利用大数据处理技术,采集、存储并分析这些数据,开展故障预警及健康分析推进海上风电机组运检模式逐渐向预知维护转变。本文主要介绍了大数据技术采集风电机组海量数据存储、分析、应用等方面的技术架构及流程,随后介绍大数据技术在海上机组诊断预警、备品备件中的应用场景,最后结合应用实际,对大数据处理技术在风电机组日常维护、故障预警等方面的实际应用效果进行了简要总结。

At present,the main maintenance mode of offshore wind turbine is regular inspection and post maintenance.When formulating maintenance strategy,it will also be affected by special factors such as wind,wave,tide and maintenance ships,which makes operation and maintenance more difficult.The wind turbine is equipped with a large number of sensors,and its data can intuitively reflect the real-time state of each equipment and system.Use big data processing technology to collect,store and analyze these data,carry out fault early warning and health analysis,and promote the gradual transformation of offshore wind turbine operation inspection mode to predictive maintenance.This paper mainly introduces the technical framework and process of big data technology acquisition,massive data storage,analysis and application of wind turbine units,then introduces the application scenarios of big data technology in offshore unit diagnosis and early warning and spare parts,and finally,combined with the application practice,the application of big data processing technology in the daily maintenance The practical application effect of fault early warning is briefly summarized.