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Dynamic statistical process control limits for power quality trend data

机译:电能质量趋势数据的动态统计过程控制限制

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Statistical process control (SPC) is a well-known method to monitor behavior and control of process parameters through statistical analysis. In power quality (PQ), we can apply this method to PQ parameters such as harmonics, imbalance, and flicker to analyze when values are outside a normal range. However, the normal range for these PQ parameters can vary depending on known conditions relating to time of day, day of the week, or even time of year. To have a tighter set of continuous control during these periods, a dynamic set of limits would be preferred over one static limit to highlight unknown abnormalities. This paper analyzes methods to create dynamic statistical process control limits for PQ data.
机译:统计过程控制(SPC)是一种众所周知的方法,用于通过统计分析来监视行为和控制过程参数。在电能质量(PQ)中,我们可以将此方法应用于PQ参数(例如谐波,不平衡和闪烁),以分析值何时超出正常范围。但是,这些PQ参数的正常范围可能会根据与一天中的时间,一周中的某天甚至一年中的某个时间有关的已知条件而有所不同。为了在这些时间段内获得更严格的连续控制,相对于一个静态极限,动态极限值将更为可取,以突显未知异常。本文分析了为PQ数据创建动态统计过程控制限制的方法。

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