Reliability parameters systematization and choice in metrological monitoring for repeated products

1983 ◽  
Vol 26 (1) ◽  
pp. 82-86
Author(s):  
V. V. Kreshchuk ◽  
M. M. Strunskaya
Keyword(s):  
Reliability Parameters ◽  
Metrological Monitoring

scholarly journals Modelling Reliability Characteristics of Technical Equipment of Local Area Computer Networks

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 955
Author(s):  
Vasyl Teslyuk ◽  
Andriy Sydor ◽  
Vincent Karovič ◽  
Olena Pavliuk ◽  
Iryna Kazymyra
Keyword(s):  
Large Scale ◽  
Computer Network ◽  
Network Reliability ◽  
Local Area ◽  
Technical Equipment ◽  
Time To Failure ◽  
Reliability Parameters ◽  
Reliability Characteristics ◽  
Global World ◽  
Level 2

Technical systems in the modern global world are rapidly evolving and improving. In most cases, these are large-scale multi-level systems and one of the problems that arises in the design process of such systems is to determine their reliability. Accordingly, in the paper, a mathematical model based on the Weibull distribution has been developed for determining a computer network reliability. In order to simplify calculating the reliability characteristics, the system is considered to be a hierarchical one, ramified to level 2, with bypass through the level. The developed model allows us to define the following parameters: the probability distribution of the count of working output elements, the availability function of the system, the duration of the system’s stay in each of its working states, and the duration of the system’s stay in the prescribed availability condition. The accuracy of the developed model is high. It can be used to determine the reliability parameters of the large, hierarchical, ramified systems. The research results of modelling a local area computer network are presented. In particular, we obtained the following best option for connecting workstations: 4 of them are connected to the main hub, and the rest (16) are connected to the second level hub, with a time to failure of 4818 h.

Voltage Sag Evaluation Method of a Real Distribution System Based on a Connection Number Model

2013 ◽  
Vol 341-342 ◽  
pp. 1363-1366
Author(s):  
Lang Bai ◽  
Le Yu
Keyword(s):  
Distribution System ◽  
Evaluation Method ◽  
Assessment Model ◽  
Voltage Sag ◽  
Voltage Sags ◽  
Connection Number ◽  
Reliability Parameters ◽  
Real Distribution ◽  
System Components ◽  
Simulation Results

The evaluation results of power system are greatly influenced by the reliability parameters and uncertainty of system components. The connection number assessment model and an approach have been presented to assess the occurrence frequency due to voltage sags. The proposed method had been applied to a real distribution system. Compared with the interval number method, the simulation results have shown that this method is simple and flexible.

Probabilistic Assessment of Wind Farm Active Power Based on Monte-Carlo Simulation

2013 ◽  
Vol 291-294 ◽  
pp. 536-540 ◽  
Author(s):  
Xin Wei Wang ◽  
Jian Hua Zhang ◽  
Cheng Jiang ◽  
Lei Yu
Keyword(s):  
Monte Carlo ◽  
Power Output ◽  
Wind Farm ◽  
Active Power ◽  
Assessment Methods ◽  
Probabilistic Methods ◽  
Model Parameters ◽  
Probability Assessment ◽  
Reliability Models ◽  
Reliability Parameters

The conventional deterministic methods have been unable to accurately assess the active power output of the wind farm being the random and intermittent of wind power, and the probabilistic methods commonly used to solve this problem. In this paper the multi-state fault model is built considering run, outage and derating state of wind turbine, and then the reliability model of the wind farm is established considering the randomness of the wind speed, the wind farm wake effects and turbine failure. The active wind farm output probability assessment methods and processes based on the Monte Carlo method. The related programs are written in MATLAB, and the probability assessment for active power output of a wind farm in carried out, the effectiveness and adaptability of built reliability models and assessment methods are illustrated by analysis of the effects of reliability parameters and model parameters on assessment results.

Reliability Parameters Forecasting for Transmission Lines Based on Principal Component Regression

2013 ◽  
Vol 291-294 ◽  
pp. 2381-2386 ◽  
Author(s):  
Wen Xia Liu ◽  
Ji Kai Xu ◽  
Hong Yuan Jiang ◽  
Yong Tao Shen
Keyword(s):  
Principal Component Analysis ◽  
Transmission Lines ◽  
Principal Component Regression ◽  
Principal Component ◽  
Forecasting Accuracy ◽  
Factors Affecting ◽  
Reliability Parameters ◽  
Impacting Factors ◽  
Simulation Results

It is the foundation for evaluating the reliability of transmission lines to obtain and analyze the original reliability parameters. However, these parameters depend on long- term statistic and calculation. In the case of lacking such parameters in a new project , this paper proposes a method of Principal Component Analysis to obtain the principal component of the impacting factors ,in which various factors affecting reliability parameters are taken into account. Through this method, we can use PCR to obtain the failure rate of the unknown transmission lines on the base of the known credible lines’ rates. The simulation results show that the proposed approach possesses higher forecasting accuracy and provides references for the power system dispatching departments and transmission lines maintenance departments.

Effects of the Cooling Rate on the Acoustic Properties of Pb-10Sn Solder

2012 ◽  
Vol 729 ◽  
pp. 356-360
Author(s):  
Endre Harkai ◽  
Tamás Hurtony ◽  
Péter Gordon
Keyword(s):  
Sound Velocity ◽  
Cooling Rate ◽  
Acoustic Microscopy ◽  
Acoustic Properties ◽  
Scanning Acoustic Microscopy ◽  
Cooling Rates ◽  
Reliability Parameters ◽  
Microscopy Characterization ◽  
The Given

Microhardness and sound velocity were measured in case of differently prepared solder samples. The used Pb-10Sn solder samples were melted then cooled down applying different cooling rates. These procedures caused variant microstructure thus different microhardness and sound velocity values. The sound velocity was measured by means of scanning acoustic microscopy. Characterization of solder materials by acoustic microscopy gives the possibility to non-destructively estimate mechanical and reliability parameters of the given material.

Field Reliability Estimation of Agricultural Tractors Based on Warranty Data

2021 ◽  
Vol 64 (2) ◽  
pp. 705-714
Author(s):  
Zhilin Zhao ◽  
Fang Cheng
Keyword(s):  
Regression Model ◽  
List Type ◽  
Reliability Parameters ◽  
Light Gradient ◽  
Manufacturing Company ◽  
Agricultural Tractors ◽  
Warranty Claims ◽  
Field Reliability ◽  
Usage Context ◽  
Usage Rates

HighlightsA LightGBM regression model for predicting tractor usage rates was established based on warranty data and considering agricultural tractors’ usage context (region and season) and was then interpreted using SHAP.The field reliability of tractors was estimated based on the usage of failed and unfailed tractors, after unfailed tractors’ usage was imputed using the LightGBM regression model.The proposed methodology was validated by predicting warranty claims using estimated reliability parameters.The proposed methodology was demonstrated using warranty data from a tractor manufacturing company in China.Abstract. Warranty data provide a valuable source of information for assessing the reliability of products in operation (called the field reliability). However, warranty data consist of failure information only. The unavailability of usage data for unfailed products makes it difficult to estimate the reliability of durable products such as agricultural tractors, for which usage is a greater concern than age for reliability analysis. Several studies have proposed methods to address this problem, but they did not include information on the usage context. This study proposes a methodology to estimate the field reliability of agricultural tractors from warranty data considering the tractors’ usage context. First, by taking features representing tractors’ usage context as the input, a usage rate regression model was established using a light gradient boosting machine (LightGBM). The usage of unfailed tractors was then generated. Finally, parametric estimates of the tractors’ reliability were determined based on the usage of failed and unfailed tractors. By interpreting the LightGBM model using SHapley Additive exPlanations (SHAP), it was found that tractors that were used more days in October and April had higher predicted usage rates. To validate the effectiveness of the proposed methodology, the estimated reliability parameters were used to predict the warranty claims of six types of tractors. The results showed that the proposed methodology performed the best in four cases and close to the best in two other cases when compared with two other baseline methods. The proposed methodology was demonstrated using warranty data from an agricultural tractor manufacturing company in China and can be applied to improve understanding of tractor reliability. Keywords: Field reliability, LightGBM, SHAP, Usage context, Warranty data.

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