Aim. To define and solve the problem of stability of the stationary quality indicator of a complex technical system. The random process of the system’s walking by its possible states is described with a homogeneous Markov process. The stability problem consists in defining such stationary (final) probabilities of the Markov process that implement the maximum and minimal values of the quality indicator, provided that the rate of state transitions have interval estimations and the rates are conditioned by the process of failures and recoveries of the system’s elements. The stationary quality indicator has a fairly standard form and is a scalar product of the final probability vector of the Markov process and the vector that characterises the “weight” of each state, where “weight” may be understood as various contensive characteristics of states.

Methods. The paper uses mathematical methods of optimal control of a Markov process using an income vector of a special form and linear programming.

Results. A method is proposed and substantiated for solving the problem of stability of a stationary indicator of the quality of operation of a complex technical system. A numerical algorithm for solving the above problem is presented as well. The paper gives an example of the solution of a problem of stability with quality indicator that is a “penalty” function.

Conclusion. The paper discusses the problem of numerical solution of the stability problem of a large dimensionality.

Aim. Reliability evaluation of a system or component or element is very important in order to predict its availability and other relevant indices. Reliability is the parameter which tells about the availability of the system under proper working conditions for a given period of time. The study of different reliability indices are very important considering the complex and uncertain nature of the power system. In this paper reliability evaluation of the meshed distribution system is presented. This paper also evaluates basic indices such as average failure rate, average outage time and average annual outage time. Along with basic indices, customer orientated indices such as system average interruption frequency index, system average interruption duration index and customer average interruption duration index of an electrical power distribution system is also evaluated. The electrical power distribution system taken for study is meshed distribution system in nature.

Aditya Tiwary. "Customer Orientated Indices and Reliability Evaluation of Meshed Power Distribution System" Reliability: Theory & Applications, vol. 15, no. 1, 2020, pp. 10-19. doi:10.24411/1932-2321-2020-11001

Aim. The problem of collective choice is the problem of combining several individual experts’ opinions about the order of preference of objects (alternatives) being compared into a single “group” preference. The complexity of collective choice consists in the requirement of processing the ratings of the compared alternatives set by different experts in their own private scales. The paper presents an original algorithm for processing expert preferences in respect to the problem of collective choice based on the concept of the overall “error” of the experts and measuring their contribution to the collective measure of their consistency. The presented materials include the necessary theoretical part consisting of basic definitions and rules, the definition of the problem and the method itself that is based on the majority rule, but in the group order of objects.

Aim. The paper aims to research the methods of evaluating dependability indicators based on the analysis of Big Data obtained in the course of monitoring the operation of technical systems and their components. A comparative analysis is performed of the efficiency of robust statistical methods of evaluating the dependability indicators of complex technical systems based on operation data.

Methods. The paper uses methods of mathematical statistics, specifically robust methods of evaluating the translation parameter of a noisy sample and numerical methods of statistical modeling. The authors consider five methods of evaluating the translation parameter: sample mean as a nonrobust method used for comparison; sample median as the simplest robust method of evaluating the translation parameter; two-stage evaluation procedure with truncation of outliers according to the three sigma rule; two-stage evaluation procedure with truncation of outliers using Tukey’s box-and-whisker plot; Huber’s robust method. The comparative analysis of the methods of evaluating system dependability indicators was conducted by means of statistical modeling in the R statistical computation package. Five distribution laws for generating an element’s time-to-failure and recovery time samples were considered: exponential distribution, Weibull distribution, log-normal distribution, gamma distribution and uniform distribution.

Results. Statistical analysis of Big Data associated with the operation of technical systems is complicated by the heterogeneity and noisiness of such data, as well as the presence of errors and outliers of varied nature. That is primarily due to the varied loads and operating conditions of each object. Herein this problem is examined as regards the problem of evaluating the dependability indicators of a structurally complex monotonic system with independent element recovery. The paper examines methods of rejecting anomalous data and robust evaluation of the sample position parameter and performs a comparative analysis of the efficiency of such methods for various distribution laws. It is shown that robust methods of evaluation enable significantly higher accuracy as compared to the standard sample mean. The two-stage procedure based on the truncation of outliers and Tukey’s box-and-whisker plot proved to be the most efficient.

Conclusions. The paper’s findings allow improving the accuracy of evaluation of dependability indicators based on complex technical system operation data. They can be used in Big Data processing and complex system dependability theory.

Aim. The paper analysed the damage rate of the electric power networks of AO Tyvaenergosbyt between 2014 and 2022 and preventively evaluates emergency shutdowns in the company’s networks in 2023. The author provides a brief historical reference regarding the company’s foundation, a description of the structure of its power supply network. The damage rate of elements, as well as main electrical equipment of the company’s power supply network were examined. The quantity of electrical power undersupplied to customers as the result of emergency shutdowns was analysed. The number of failures was classified depending on the amount of undersupplied electrical power. The paper studied the applicability of certain methods of prediction of the number of emergency shutdowns for the obtained interpolated series of preceding failures. The most appropriate method was established that was used for preventively evaluating the damage rate of the examined power networks for each month of 2023.

Methods. The paper uses methods of mathematical analysis, general scientific methods of research, properties and capabilities of the MATLAB graphic interface and Excel tables. Statistical and cybernetical methods of prediction were considered for the purpose of predictive model development. The probability of failures within the examined power networks was evaluated. Equations were obtained for autoregression failure models that enable predictive evaluation of failure by months.

The Results of the study may prove to be useful to the experts of Tyvaenergosbyt, as well as other power grid companies that are developing advanced emergency prevention activities aimed at improving the reliability of power supply.

Conclusion. The approach to predictive evaluation of emergency shutdowns proposed in the paper showed that the most efficient method of predicting failures in a company’s power networks is the method of autoregression models using interpolation of data on preceding failures. The probability of prediction fulfilment is 95%.

Aim. The paper aims to demonstrate a unique method of evaluating the authenticity of as-built survey maps using Microsoft Excel and verification results. The authenticity of the horizontal and vertical deviations of building structures documented in geodetic designs is evaluated by comparing the diagram of control point value distribution with a normal probability plot (Gaussian distribution). The verification of the developed method presented in the paper is based on a quantile plot, as well as calculations using three different methods involving the analysis of the parameters and statistical characteristics of the sought sample.

Methods. The paper used the cameral method of evaluating as-built survey maps, as well as methods of mathematical statistics for verifying the research findings.

Results. The hypothesis of normal distribution of the sample of control point deviations of the examined building structures was verified and confirmed using the following methods: quantile plotting; verification of the three sigma rule; analysis of the index of skewness and kurtosis; verification of the hypothesis of normal distribution per Pearson’s chi-squared test. That allows ensuring the reliability and verifiability of the results as regards the registration control of as-built drawings. The paper also substantiates the practical applicability of the method of evaluating the authenticity of asbuilt survey maps developed by the authors.

Aim. The paper describes a research of gender-specific personality features of flight school students. The eventual task was to research the effect of the identified gender-specific features of the male and female students on their academic and flight training performance.

Methods. The research employed standardised character research methods: L.N. Sobchik’s version of MMPI and the 16-factor personality inventory. The resulting data were analysed using descriptive statistics of Microsoft Office 2007 Excel, Student’s Т-score for unconjugated samples (statistical significance if p < 0.05).

Results of the research. It has been established that the academic and flight training performance are affected by both identical and differing personal qualities of male and female students.

Conclusion. The conducted research identified gender-related personality features that correlated with the academic and flight training performance of male and female students that manifest themselves as sets of personal attributes. The identified personal attributes of male and female students may have either a positive, or a negative effect on their academic and flight training performance.

Aim. The paper proposes approaches to the organisation of testing of digital systems through malfunction imitation for the purpose of ensuring compliance of international and Russian failure and fault resistance standards for the purpose of efficient (in terms of time) detection of software defects as part of mass production of products. The paper proposes a structure and operating algorithm of a hardware and software test bed for malfunction simulation intended for testing a system’s devices. The test bed collects and processes data for fuzzing, hardware error identification, as well as defines the scope of testing.

Methods. The paper used basic systems approach, classical methods of the probability theory and mathematical statistics, decision theory, methods of hardware and software testing and development, mathematical theory of fuzzy sets and fuzzy logic.

Results. Malfunction simulation algorithms were developed for the purpose of testing hardware and software systems using fuzzing that ensure probabilistic estimation of the termination time of testing with a specified accuracy.

Conclusions. The above set of algorithms allows detecting system defects in the process of software and hardware integration into a single system that cause new malfunctions (emergence) that cannot be taken into consideration at the design stage.