基于大数据平台的水轮发电机组故障诊断系统

水轮发电机组是水电站的关键设备，它的运行状况直接关系到水电站的安全生产。目前对水轮发电机组运行状况的掌握大都通过装设的状态监测系统运行数据的分析比对和计划检修相结合的方式，但往往都是故障已经发生后才能予以发现，不能提前对设备运行工况进行预判。本文详细介绍了一种基于大数据平台的水轮发电机组故障诊断系统，该系统主要由数据处理平台、模型算法平台、可视化展示平台三部分组成，是一种基于大数据平台和互联网技术的典型应用。其主要通过挖掘水电厂现有计算机监控系统、状态监测系统等信息系统的实时及历史数据，再经过一系列关联算法提取这些数据中蕴含的丰富的价值信息来实现对机组的运行状况监视、健康评价、趋势预警、故障诊断、检修指导等。

Fault diagnosis System of Hydro Generator based on Big Data Platform

Hydro generator is the key equipment of hydropower station, its running state is directly related to the safety production of hydropower station. At present, in order to master the running status of hydro generator, we mostly by analysis of the running data of the state monitoring system and scheduled maintenance check. Usually, faults can only be found after they have occurred, and the running state of equipment cannot be predicted in advance. This paper introduces a fault diagnosis system of hydro generator based on big data platform. The system consists of data processing platform, model algorithm platform and visual display platform, is a typical application based on big data platforms and Internet technology. It mainly excavates the real-time and historical data of the existing information systems such as the computer monitoring system and the state monitoring system, and then extracts the rich value information contained in these data through a series of association algorithms to realize the running status monitoring, health evaluation, trend warning, fault diagnosis and maintenance guidance of the unit.