摘要
提出了一种基于经验模态分解(EMD)的矿用通风机故障诊断的新方法,该方法通过EMD 把时间序列信号分解成不同特征的固有模态函数(IMF),然后通过对选取表征通风机故障的 IMF 分量进行频谱分析,就可提取通风机故障信号的特征,进而判断出通风机的故障。工程应用表明,该方法能有效地识别通风机故障。
A new method of fault diagnosis for the mine ventilator based on the empirical mode decomposition （EMD） is presented. This method decomposes the original time series data into intrinsic mode function （IMF） with different features by using the EMD. The frequency spectrum analysis is applied to the selected IMF which stands for the ventilator faults; and the signal feature of ventilator faults can be extracted, so the fault can be further diagnosed. The experimental result shows that this method can effectively diagnose the faults of mine ventilator.
出处
《矿山机械》
北大核心
2008年第17期17-19,共3页
Mining & Processing Equipment
