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Two-dimensional Trend Analysis of Time Series of Complex Technical Objects Diagnostic Parameters

机译:复杂技术对象的时间序列二维趋势分析诊断参数

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An approach to assessing the relationship and differences of multidimensional trends is proposed and justified. The approach is based on construction of multidimensional arrays from time series of registration data of the diagnosed objects technical parameters. To identify the similarities and differences of time series trends, a pairwise joining of their samples with the same arguments is proposed. The unified time series has the counts in the form of complex numbers and is analysed by the proposed improved principal components method. The proposed method permits dividing the parameters of the object condition into groups that have trends of the same type, which allows localising faults and increasing the reliability of diagnostic conclusions about the technical condition of the object. The a priori statistical model of data generation adopted in the studies was chosen as a model of deviations of the diagnosed objects parameters from the nominal values.
机译:提出了一种评估多维趋势关系和差异的方法。该方法是基于从诊断的对象的注册数据的时间序列的多维阵列的构造。为了确定时间序列趋势的相似性和差异,提出了一种成对与相同参数的样本的连接。统一的时间序列具有复杂数字形式的计数,并通过所提出的改进的主要成分方法进行分析。所提出的方法允许将物体状况的参数划分为具有相同类型趋势的组的组,这允许本地化故障并提高关于对象技术条件的诊断结论的可靠性。选择在研究中采用的数据生成的先验统计模型作为从标称值诊断诊断的对象参数的偏差模型。

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