Development of Time Series Disorder Detection Algorithms Based on Nonparametric Hypothesis Testing Criteria

Authors

  • Геннадий [Gennadiy] Федорович [F.] Филаретов [Filaretov]
  • Зинеддин [Zineddin] Бучаала [Bouchaala]

DOI:

https://doi.org/10.24160/1993-6982-2021-3-67-77

Keywords:

time series disorder, disorder detection, nonparametric detection methods, igns criterion, series criterion, Ramachandran–Ranganathan criterion, detection algorithm probabilistic characteristics, synthesis of a monitoring procedure

Abstract

The solution of the problem of detecting, in the online mode, a spontaneous change in the probabilistic characteristics (“disorder” or “breakdown”) of a time series is given. It is pointed out that there is a growing interest in the development of so-called nonparametric disorder detection methods, i.e., methods the application of which does not require the knowledge of the probability distribution function of the controlled process values. It is stated that the majority of the known versions of such methods are based on using a number of standard nonparametric criteria transformed for solving disorder detection problems. It is proposed to use the signs criterion, the series criterion, and the Ramachandran–Ranganathan criterion as a basis for construction of disorder detection algorithms. The methodical aspects of studying the statistical properties and efficiency of the disorder detection algorithms built on their basis are considered. The simulation method was used as a study tool. The plan of carrying out simulation experiments was developed separately for each of the proposed algorithms, taking into account their individual characteristics, but based on the general requirement of fully reproducing the monitoring algorithm performance dynamics under real conditions, when a disorder can appear at any time and there is a transient in the values of the decisive function. By using a simulation experiment for each of the algorithms under consideration, data on their statistical characteristics were obtained and systematized in a scope sufficient for synthesizing a monitoring procedure with the specified properties.

Author Biographies

Геннадий [Gennadiy] Федорович [F.] Филаретов [Filaretov]

Dr.Sci. (Techn.), Professor of Control and Intelligent Technologies Dept., NRU MPEI, e-mail: gefefi@yandex.ru

Зинеддин [Zineddin] Бучаала [Bouchaala]

Ph.D-student of Control and Intelligent Technologies Dept., NRU MPEI, e-mail: bouchaala.zinouzin@gmail.com

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Для цитирования: Филаретов Г.Ф., Бучаала З. Разработка алгоритмов обнаружения разладки временных рядов на основе непараметрических критериев проверки гипотез // Вестник МЭИ. 2021. № 3. С. 67—77. DOI: 10.24160/1993-6982-2021-3-67-77.
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For citation: Filaretov G.F., Bouchaala Z. Development of Time Series Disorder Detection Algorithms Based on Nonparametric Hypothesis Testing Criteria. Bulletin of MPEI. 2021;3:67—77. (in Russian). DOI: 10.24160/1993-6982-2021-3-67-77.

Published

2020-11-27

Issue

Section

System Analysis, Management and Information Processing (05.13.01)