基于DPMM的核主泵振动状态预警方法研究

Research on Nuclear Main Pump Vibration Status Warning Method Based on DPMM

单门限阈值报警在核主泵的实际应用中存在反复穿越报警的问题,基于DPMM的核主泵状态预警方法通过多参数自动聚类和参数识别能有效解决该问题。该方法以主泵正常运行状态的数据为基准,学习得到预警阈值,根据主泵实时振动数据,计算得到实时预警指标,实时预警指标超阈值即实现预警。主泵故障案例数据少且报警数据稀疏,因此开发了一种基于相关系数的振动异常数据定位方法,获得了大量振动异常波动的数据,用于预警模型的开发和验证。经验证,状态预警准确率达到97%,预警提前时间最长达4 h。

Nuclear main pump warning method using single parametric threshold has the problem of repeatedly crossing the warning line in practice.Using multi characteristic parameters auto clustering and identification,nuclear main pump status warning method based on DPMM can deal with this problem.From normally vibrational data,warning threshold was studied.From real-time vibrational data,real-time warning index was calculated.Status warning was realized when real-time warning index beyond the warning threshold.Because of few fault cases and sparse alarm data,a method using correlation coefficient was proposed to locate abnormally vibrational data.Much fluctuant vibration data were obtained to develop and verify the warning method.The warning method has the accuracy of 97%and brings forward the warning time up to 4 h.