信号模型函数参数e域在异常情况检测中的应用

L. Suchkova, A. Yakunin
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引用次数: 0

摘要

研究了不服从统计规律的噪声和干扰引起的测量误差的估计问题的解决方法。该信号的模型以复合多参数准定模型函数的形式呈现,并以固定的测量间隔为背景函数。背景函数由函数的任意集合描述,这些函数的变化范围受e层的限制。该模型提供了接近于单位置信值的信号参数区间估计的计算。介绍了基于e区模型和非线性模型函数的参数区间误差计算方法。如果背景函数的取值范围是有限的,这种技术允许计算信号实现的特定参数的区间估计。结果表明,在参数空间中定义的e区域表征了控制对象的状态。基于基于模型函数参数空间中的e域从特定信号实现中诊断对象状态的发展算法,提出了一种异常情况识别方法。基于基于模型函数参数空间中的e区域从信号的实现中诊断对象状态的算法,提出了一种异常情况识别方法。介绍了e区域在电能和其他能源消耗过程监测中的实际应用结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of E-Regions of the Parameters of the Model Function of the Signal for the Extraordinary Situations Detection
Methods of solution of a problem of an estimation of uncompensated errors of the measurements caused by presence of noises and interferences, that not submitting to statistical regularities are investigated. The model of the signal presented in the form of a composition multiparameter quasidetermined model function and fixed on interval of measurement a background function is considered. The background function is described by an arbitrary ensemble of functions whose range of variation is limited by the E-layer. The proposed model provides the calculation of interval estimates of signal parameters for confidence values close to unity. The technique of calculation of interval errors of parameters on the basis of model of E-areas and nonlinear model function is described. This technique allows calculating interval estimations of parameters for a particular of a signal realization, provided that the range of values of the background function is limited. It is shown that defined in the space of parameters E-regions characterize the state of the control object. Based on the developed algorithm for diagnosing the state of an object from the particular signal realisation using E-regions in the space of parameters of a model function, an approach to identifying abnormal situations is proposed. Based on the developed algorithm for diagnosing the state of an object from the implementation of a signal using E-regions in the space of parameters of a model function, an approach to identifying abnormal situations is proposed. The results of practical application of E-regions for monitoring the process of power consumption of electric energy and other energy resources are presented.
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