基于相关系数的核泵振动监测数据异常定位方法研究

Y. Wenmin, Hou Xiuqun, Li Yuanjiao, Jiang Qinglei, Bao Binbin
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引用次数: 0

摘要

核电厂积累了大量的过程监测数据,但大部分数据没有标记出特定的模式,无法直接应用于数据驱动的智能预警和故障诊断。现场报警阈值只能定位少部分异常振动数据,而忽略了大量未超过报警阈值但属于明显异常振动波动现象的数据。针对这一问题,本文提出了一种基于相关系数的异常振动数据定位方法。该方法以振动数据与对应时间的相关系数作为测量振动数据的波动指标,通过历史数据统计计算出波动阈值,从而定位异常振动数据。核泵振动监测数据表明,该方法能有效检测数据的异常波动,定位异常振动的起始点。
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Research on Anomaly Location Method for Nuclear Pump Vibration Monitoring Data Based on Correlation Coefficient
Nuclear power plants have accumulated a large amount of process monitoring data, but most of the data are not marked with specified patterns, which cannot be directly applied to the data-driven intelligent early warning and fault diagnosis. On-site alarm threshold can only locate a small number of abnormal vibration data, ignoring a large number of data that doesn't exceed alarm threshold but is obviously abnormal fluctuation of vibration phenomenon. To solve this problem, a method is proposed to locate abnormal vibration data based on correlation coefficient in this paper. This method takes the correlation coefficient of vibration data and corresponding time as the fluctuation index of measuring vibration data, and calculates the fluctuation threshold through historical data statistics, so as to locate abnormal vibration data. The vibration monitoring data of nuclear pump show that the proposed method can effectively detect the abnormal fluctuation of the data and locate the starting point of abnormal vibration.
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