基于大数据的水电机组不平衡故障预警技术研究

Research on Unbalance Fault Early Warning Technology of Hydroelectric Generator Uint Based on Big Data

以质量不平衡、电磁拉力不平衡、水力不平衡为代表的不平衡类故障是水电机组最常见的故障,对这类故障进行预测和早期预警迫在眉睫。传统的故障诊断技术往往局限于事后故障分析,而本文则通过对机组不平衡类故障的机理分析,针对各种不平衡故障,提出能反映故障发展水平的特征指标,并采用大数据分析技术,通过对特征指标的大数据挖掘分析,实现机组不平衡故障的早期预警。

The unbalance faults such as mass-unbalance fault, electromagnetic unbalance fault, hydraulic imbalance fault are themost common faults of hydro generating set, and it is urgent to forecast and early warning these faults. Traditional fault diagnosis techniques are often used to post fault analysis, so this paper puts forward the characteristic index that can reflect the fault severity according the analysis of the unbalance fault mechanism, and helps to realize early warning of unit＇s unbalanced failure through data mining of characteristic indexes based on big data analysis technology.