АНАЛИЗ БОЛЬШИХ ДАННЫХ НАДЕЖНОСТИ НЕВОССТАНАВЛИВАЕМЫХ МНОГОКАНАЛЬНЫХ СИСТЕМ

Abstract

Introduction: methods for analyzing big data of reliability of multichannel systems with a loaded reserve with nonrecoverable elements are considered. Big data contains information on the operating time to failure of elements, obtained by monitoring the operation of similar systems. The main problem that arises when analyzing big data is related to its variety and veracity. Reliability data of system elements correspond to different operating conditions and different laws of failure distribution. The exponential approximation of failure distributions greatly simplifies reliability analysis. However, it can lead to significant errors and requires a separate justification. Purpose: development of approaches to the analysis of heterogeneous big data of reliability of system elements characterized by different distributions of failures. Derivation of estimates of the accuracy of approximation of the distribution of failures by exponential laws and criteria for the possibility of such an approximation. Results: methods for calculating the mean time to failure of systems with a monotonic structure are described. An estimate of the error of exponential approximation of the distributions of failures of elements of a multichannel system is obtained. The relationship between the error of exponential approximation and the coefficient of variation of non-exponential distribution of failures is shown. The case of two channel systems is investigated in detail. For uniform, lognormal, gamma and Weibull distributions, the dependences of the average operating time to rejection of the coefficient of variation are plotted. Areas of variation of the coefficient of variation of these distributions are constructed, for which exponential approximations are justified. An algorithm for constructing the mean time to failure in the analysis of large reliability data of a non-recoverable two-channel system is presented. Practical relevance: analysis of reliability data obtained from monitoring the operation of similar systems eliminates costly reliability tests. The relationship between the sample coefficient of variation and the error of exponential approximation of failure distributions in the analysis of big data of system reliability is shown. This connection forms the basis of the criterion for the possibility of such an approximation.