Features of assessing the condition of complex objects

O. Ivanets, L. Kosheva, E. Volodarsky
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Abstract

In practice, complex objects are characterized by several parameters that can be correlated. Such facilities include most of the facilities / subjects of diagnosis in medicine, ecology, biology, meteorology, climatology, in assessing the quality of raw materials, all types of fuels and others. Assessment of the state of complex objects is carried out by ensuring the maximum completeness of the information about the parameters of the studied object by measuring the parameters that correlate with the studied parameter. The degree of commonality of the processes of measurement and diagnosis in terms of information is significant, which leads to the need for their joint study and to obtain relationships that are fair in both measurements and control, which increases the reliability of diagnosis. Since the controlled parameters, in the general case, can change over time, it is necessary, based on the assumption of the influence of only random variables, to introduce the norms of possible deviations. Going beyond these norms is the basis for decisionmaking. However, independent monitoring of individual indicators may, if correlated, lead to erroneous decisions. To prevent this, it is proposed to use statistical methods with multiparameter criteria to assess and diagnose the stability of complex objects. The paper proposes the use of T ^ 2 - Hotelling statistics to diagnose the state of complex objects. The physiological state of the human body was chosen as the object of study.
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评估复杂物体状态的特征
在实践中,复杂的目标由几个可以相互关联的参数来表征。这些设施包括医学、生态学、生物学、气象学、气候学、评估原材料质量、所有类型燃料和其他方面的大多数诊断设施/科目。对复杂对象状态的评估是通过测量与被研究对象参数相关的参数来确保被研究对象参数信息的最大完整性。测量和诊断过程在信息方面的共性程度是显著的,这导致它们需要共同研究,并获得在测量和控制方面公平的关系,从而增加诊断的可靠性。由于受控参数在一般情况下会随时间而变化,因此有必要在假设仅受随机变量影响的基础上引入可能偏差的规范。超越这些规范是决策的基础。然而,对个别指标的独立监测如果相互关联,可能会导致错误的决定。为了防止这种情况,提出了采用多参数标准的统计方法来评估和诊断复杂目标的稳定性。本文提出利用T ^ 2 -霍特林统计量来诊断复杂物体的状态。选择人体的生理状态作为研究对象。
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