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Improving Performance of Wilcoxon Criterion under Solving Problems with Typical Singularities in Measurements

机译:在解决测量中具有典型奇点的问题下提高Wilcoxon准则的性能

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The paper discusses the approach that supports measurement data treatment on significant events from electrical consumption load profile. The problem of detecting significant deviations in the accounting of electricity consumption is under consideration. The data available from power meters and intelligent sensors is used to classify the events in power supply process. This information is of high importance and can be utilized to predict violations. It leads to rapid decision-making and allows avoiding the penalties on behalf of the power distribution utilities. The data received from smart meters is usually represented in the form of so-called “load profiles”. The article introduces an approach for improving the solvability of the data discrimination problem through the non-parametric Wilcoxon sign ranks criterion under the cases with singularities in compared data samples of the type “vertical offset” and “scale”. The modified Wilcoxon criterion is considered as a tool for identifying deviations in the conduct of the technological process, which do not exceed the threshold values, but have a significant impact on the technical and economic indicators. The proposed method of identifying critical events, which uses the modified Wilcoxon criterion, makes it possible to determine both the fact of the presence of an event and to provide their identification. It is proved that the power of the proposed modified Wilcoxon test does not degrade comparing with the traditional Wilcoxon test. The executed example of processing the power consumption data of the petrochemical industrial enterprise allowed testing the effect of using the modified Wilcoxon criterion as a part of the computational procedure for the developed algorithm.
机译:本文讨论了一种方法,该方法支持针对电力消耗负载曲线中的重大事件进行测量数据处理。正在考虑检测用电量核算中的重大偏差的问题。功率计和智能传感器可提供的数据用于对供电过程中的事件进行分类。此信息非常重要,可以用来预测违规情况。它可以快速做出决策,并可以避免代表配电公司的处罚。从智能电表接收的数据通常以所谓的“负载曲线”形式表示。本文介绍了一种在“垂直偏移”和“比例”类型的比较数据样本中具有奇异性的情况下,通过非参数Wilcoxon符号等级准则改善数据歧视问题的可解决性的方法。经修改的Wilcoxon标准被认为是识别工艺过程中偏差的工具,该偏差不超过阈值,但会对技术和经济指标产生重大影响。所提出的使用改进的Wilcoxon准则来识别关键事件的方法,既可以确定事件的存在事实,也可以对其进行识别。事实证明,与传统的Wilcoxon检验相比,改进的Wilcoxon检验的功效不会降低。通过执行石化工业企业能耗数据处理示例,可以测试将改进的Wilcoxon准则用作所开发算法的计算过程的一部分的效果。

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