摘要
采用奇异谱分析方法对轴承温度信号在相空间进行重构,并利用重构吸引子轨道矩阵的奇异谱特性来分离温度信号的趋势成分,从而得到轴承温度的变化趋势特征.在此基础上开发了水电机组轴承故障预测系统,该系统包括数据采集、趋势分析和故障预测3部分.试验结果表明,该系统能早期预测轴承温升趋势,提取温度信号中的故障特征,对烧瓦故障作出早期预警,可用于水电机组的状态分析、状态评估和故障预测.
The SSA （ Singular Spectrum Analysis） was used to reconstruct the temperature signals of bearings in the phase space. According to the singular spectrum characteristic of the reconstructed attractor track matrix,the temperature signals were separated into two independent components： the trend and the noise. The trend feature of bearing temperature was then obtained from the original signal. On this basis, a fault prediction system for the bearing of hydroelectric generating set was developed. This system includes three subsystems respectively for data collection, trend prediction and fault diagnosis. Test results show that the proposed system can predict the increase trend of bearing temperature early, extract the fault characteristics contained by the original signal, give an advance warning to prevent the faults at the burning tile, and can be applied to the state analysis, state assessment and fault prediction of hydroelectric generating sets.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第9期51-54,72,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(50379015)~~
关键词
水电机组
奇异谱分析
轴承温度
温度趋势
故障预测
hydroelectric generating set
singular spectrum analysis
bearing temperature
temperature trend
fault prediction
