Reliability parameters estimation for radioelectronic equipment in case of change-point

Zaliskyi, Maksym; Соломенцев, Олександр; Kozhokhina, Olena; Herasymenko, Tetyana

doi:10.1109/sps.2017.8053676

Cited by 24 publications

(3 citation statements)

References 5 publications

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“…After deterioration detection, it is necessary to estimate the reliability parameters. The example of reliability parameters estimator for a quadratic model of failure rate trend was presented in [22].…”

Section: Electrical Control and Communication Engineeringmentioning

confidence: 99%

Method for Changepoint Detection With Sample Size Accumulation During Radio Equipment Operation

Соломенцев

Zaliskyi

Herasymenko

et al. 2020

Electrical, Control and Communication Engineering

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The operation system determines the efficiency of the intended use of radio equipment. The operation system includes radio equipment, documentation, operational resources, personnel, processes, data processing algorithms, etc. The operation process is associated with conditions of priori uncertainty of models, parameters, external factors, etc. The main element for monitoring is technical condition of radio equipment. In a general case, this condition can deteriorate. The problems of technical condition deterioration analysis can be considered in terms of changepoint study. The present paper concentrates on the problem of synthesis and analysis of method for changepoint detection during radio equipment operation. The detection algorithm is constructed based on Neyman–Pearson criterion with sample size accumulation. During algorithm synthesis the thresholds were calculated according to Bellman’s approach. The problem of synthesis and analysis was solved by two methods: analytically and using statistical modelling. The efficiency measures for this algorithm are the probability of correct detection and mean time of decision making. The proposed algorithm has advantages in mean time of decision making compared with CUSUM detection method.

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Section: Electrical Control and Communication Engineeringmentioning

confidence: 99%

Method for Changepoint Detection With Sample Size Accumulation During Radio Equipment Operation

Соломенцев

Zaliskyi

Herasymenko

et al. 2020

Electrical, Control and Communication Engineering

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“…Such changes can occur due to different reasons: personnel errors, aging of components and systems, etc. [9][10][11][12][13][14][15]. Statistical data processing algorithms estimate the time of possible failure with the aim of preventing it based on correct and timely operational actions.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Maintenance Task Interval of Aircraft Systems

Okoro¹,

Zaliskyi²,

Dmytriiev³

et al. 2022

IJCNIS

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Maintenance accounts for approximately 20% of the operational cost of aircraft; a margin higher than cost associated with fuel, crew, navigation, and landing fees. A significant percentage of maintenance cost is attributed to failures of aircraft components and systems. These failures are random and provide a database which can further be analyzed to aid decision-making for maintenance optimization. In this paper, stochastic mathematical models which can potentially be used to optimize maintenance task intervals of aircraft systems are developed. The initial data for this research are diagnostic variables and reliability parameters which formed the basis for selecting the probability density function for time between failures according to the exponential and Erlang models. Based on the probability density functions, the efficiency of the maintenance processes was calculated using average operational cost per unit time. The results of the analysis were further tested using the Monte Carlo simulation method and the findings are highlighted in this paper. The simulation results compared favorably with analytical results obtained using already existing Monte Carlo techniques to about 82% accuracy. The proposed mathematical optimization models determine the optimal aircraft maintenance task interval which is cost effective while considering safety and reliability requirements; our results can also be applied during the development, design, and operation phases of aircraft systems.

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“…For the purpose of operational efficiency providing, statistical data processing algorithms can be used (Solomentsev, Zaliskyi, & Zuiev, 2016). The values of determining parameters (Silkov & Delas, 2015) and values of reliability measures (Solomentsev et al, 2017) can be used as the source of initial data for processing. This data are results of monitoring of technical condition of equipment (Mironov et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Efficiency of Operational Data Processing for Radio Electronic Equipment

et al. 2020

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The paper deals with the statistical data processing algorithms in operation system of radio electronic equipment. The main purpose is analysis of data processing algorithm efficiency according to the analytical calculations and simulation results. During radio electronic equipment operation failures are possible. These failures affect on the equipment’s technical condition that can deteriorate. In case of condition-based maintenance, it is necessary to detect the time moment of deterioration beginning. Therefore, in this paper the deterioration detection algorithm was developed according to Neyman-Pearson criterion with a fixed sample size. The initial data are times between failures of radio electronic equipment, and these data can be identified by the exponential probability density function. The step-function model was chosen for failure rate change description. To estimate efficiency the operating characteristic was calculated. The simulation based on Monte-Carlo method confirmed the correctness of theoretical calculations.

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Reliability parameters estimation for radioelectronic equipment in case of change-point

Cited by 24 publications

References 5 publications

Method for Changepoint Detection With Sample Size Accumulation During Radio Equipment Operation

Method for Changepoint Detection With Sample Size Accumulation During Radio Equipment Operation

Optimization of Maintenance Task Interval of Aircraft Systems

Efficiency of Operational Data Processing for Radio Electronic Equipment

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