Calculation Of Reliability Indices Research Articles

Reliability evaluation of community integrated energy systems based on fault incidence matrix

• An analytical reliability evaluation method for CIESs based on fault incidence matrix (FIM) is proposed. • The energy-bus-based unified reliability evaluation model of CIESs is presented to describe the energy flows of the system in a unified matrix form. • The case study is performed based on a practical CIES to demonstrate the advantages of the FIMs in reliability index calculation and vulnerability identification. Reliability evaluation is essential for the planning, operation, and analysis of community integrated energy systems (CIESs). However, it is still challenging to quantify the reliability of CIESs accurately and efficiently because of the diverse energy characteristics and energy conversion relationships. In this paper, a reliability evaluation method for CIESs based on fault incidence matrix (FIM) is proposed to analytically demonstrate the impact of equipment failures on system energy supply. The energy-bus-based unified reliability evaluation model of CIESs is presented to describe the energy flows of the system in a unified matrix form. Three types of FIMs are constructed to reveal the different consequences of device failures on energy supply. The reliability indices of a CIES can be directly calculated through simple algebraic and Boolean operations based on the FIMs, improving the calculation efficiency significantly. The FIMs make it easy to identify the vulnerability segments of the system, which is desirable in the practice of device maintenance or upgrade to improve the reliability of the CIES. Case studies are conducted on a typical CIES to verify the effectiveness and feasibility of the proposed method.

Multistate Reliability Analysis of Recessive Fault of Mechanical Meta-Action Unit Based on Markov Process

In order to clearly express the reliability dynamic change process of mechanical meta-action units with recessive fault on continuous time series, this paper proposes a reliability analysis method for multistate systems with recessive failures of mechanical meta-action units based on the fusion of vibration signal analysis and Markov process. By analyzing the vibration signal, five major recessive fault types of mechanical meta-action units are determined. By analyzing the experimental data and based on the average time of the first occurrence of five major recessive faults, a performance level state representation model of mechanical meta-action unit based on fault importance weight is established. Then, based on the repairable characteristics of the mechanical element action unit, the two-way state transition model and state probability differential equation of mechanical meta-action units are established, and the state probability of each state is obtained. Next, under the condition of determining the initial state, the change process curves of the instantaneous availability, instantaneous average performance, and instantaneous average performance deficit of the mechanical meta-action unit are obtained by solving the reliability index calculation formula. Finally, this paper takes the worm rotation meta-action unit as an example to verify the law and probability of the state transition of the mechanical meta-action unit, and the performance level change accompanying the state transition process, by analyzing the failure modes and causes of recessive faults, the corresponding reliability control measures are formulated, and the control effects before and after reliability control are analyzed. The research results show that this method can effectively improve the accuracy of the state probability when calculating the state probability of each state, and compared with the discrete Markov model, when studying the reliability of complex multistate systems, this method can dynamically describe the change process of state probability, instantaneous availability, instantaneous average performance, and instantaneous average performance deficit in real time under the condition of continuous time-dependent variables. It has certain guiding significance for the reliability analysis of mechanical element action units in the long-term range.

Scalability of the Positive and Negative Syndrome Scale in first-episode schizophrenia assessed by Rasch models.

ObjectiveHistorically, assessment of the psychometric properties of the Positive and Negative Syndrome Scale (PANSS) has had several foci: (1) calculation of reliability indexes, (2) extraction of subdimensions from the scale, and (3) assessment of the validity of the total score. In this study, we aimed to examine the scalability and to assess the clinical performance of the 30‐item PANSS total score as well as the scalability of a shorter version (PANSS‐6) of the scale.MethodsA composite data set of 1073 patients with first‐episode schizophrenia or schizophrenia spectrum disorder was subjected to Rasch analysis of PANSS data from baseline and 4–6 weeks follow‐up.ResultsThe central tests of fit of the Rasch model failed to satisfy the statistical requirements behind item homogeneity for the PANSS‐30 as well as the PANSS‐6 total score. For the PANSS‐30, Differential Item Functioning was pronounced both for the 7‐point Likert scale rating categories and when dichotomizing the rating categories. Subsequently, the Rasch structure analysis in the context of dichotomized items was used to isolate and estimate a systematic error because of item inhomogeneity, as well as a random error. The size of the combined sources of error for the PANSS‐30 total score approximated 20% which is often regarded as clinical cut‐off between response versus no‐response.ConclusionThe results demonstrate the operational consequences of a lack of statistical fit of the Rasch model and suggest that the calculated measure of uncertainty needs to be considered when using the PANSS‐30 total score.

신뢰도지표를 활용한 신 가치기반신뢰도평가 (VBDRA) 기반의 배전 설비 투자 선택 방안 연구

We select the optimal distribution system investment plan, which has the largest ratio of the financial benefit and investment cost. We measure the financial benefit of investment plan based on the improvement level of reliability index on the target distribution system. However, in the classical value based distribution system reliability assessment (VBDRA), the financial benefit was measured based on the reliability index itself, so our approach is a new VBDRA. The improvement level of reliability index is converted to the financial benefit by multiplying the electricity interruption cost. In this study, we also introduce the reliability index calculation method based on three basic reliability parameters: average failure rate, average power outage time, and average annual power outage time. Then, we calculate the reliability index of six different distribution systems. Finally, we measure reliability index and financial benefits of three virtual distribution systems with different investment plans on distribution components. Based on the ratio of financial benefits to investment costs, we select the optimal distribution system investment plan.

Преобразование параметров надежности с использованием параметрического метода

As a whole calculation of reliability indicators and obtaining estimates of the reliability for infocommunication systems and networks is based on various assumptions about the distributions laws of empirical data obtained as a result of an experiment or during operation. As theoretical and practical studies an algorithm for calculating the numerical values of a random variable in a random process using the parametric method is presented. The article is aimed to transform different types of distribution. Calculated formulas are derived. The problem of obtaining a chi-square distribution from four normally distributed random sequences is solved. Software implementation was performed using the mathematical modeling program Matlab. Graphs are proposed to illustrate the transformation of a uniformly distributed random sequence into an exponentially distributed sequence. A comparison between theoretically and practically completed transformations is given.

Incorporating Setup Effects into the Reliability Analysis of Driven Piles

Driven-pile setup is referred to a phenomenon in which the bearing capacity of driven piles increases with time after the end of driving (EOD). The setup effect can significantly improve the bearing capacity (ultimate resistance) of driven piles after initial installation, especially the ultimate shaft resistance. Based on the reliability theory and considering the setup effects of driven piles, this article presents an increase factor (Msetup) for the ultimate resistance of driven piles to modify the reliability index calculation formula. At the same time, the correlation between R0 and Rsetup is comprehensively considered in the reliability index calculation. Next, the uncertainty analysis of load and resistance is conducted to determine the ranges of relevant parameters. Meanwhile, the influence of four critical parameters (factor of safety FOS, the ratio of dead load to live load ρ = QD/QL, Msetup, the correlation coefficient between R0 and Rsetup, and ρR0,Rsetup) on reliability index are analyzed. This parametric study indicates that ρ has a slight influence on the reliability index. However, the reliability index is significantly influenced by FOS, Msetup, and ρR0,Rsetup. Finally, by comparisons with the existing results, it is concluded that the formula proposed in this study is reasonable, and more uncertainties are considered to make the calculated reliability index closer to a practical engineering application. The presented formula clearly expresses the incorporation of the pile setup effect into reliability index calculation, and it is conducive to improving the prediction accuracy of the design capacity of driven piles. Therefore, the reliability analysis of driven piles considering setup effects will present a theoretical basis for the application of driven piles in engineering practice.

THE IMPACT OF INFORMATION SERVICES THROUGH WHATSAPP MOTIVATION OF CLASS X STUDENTS OF SMAN 3 SAMARINDA IN THE PANDEMIC PERIOD OF THE 2020/2021 ACADEMIC YEAR

The background of this research is due to a decrease in students' learning motivation during the pandemic so that BK teachers provide information services with the help of Whatsapp Group media to increase students' learning motivation during the pandemic. The formulation of the research problem is how the impact of information services through Whatsapp Group in increasing the learning motivation of class X SMA Negeri 3 Samarinda students with the aim of knowing the impact of information services through Whatsapp Group in increasing the learning motivation of class X students of SMA Negeri 3 Samarinda during the pandemic. The type of data used is quantitative research with ex post facto correlational design research methods. The population is all students of class X in SMA Negeri 3 Samarinda with a sample of 138 respondents, purposive sampling technique. Data collection techniques are questionnaires on information services and students' learning motivation. The instrument validity test used the Pearson Product Moment correlation formula, and the instrument reliability test used the Cronbach Alpha coefficient approach reliability index calculation using the SPSS 25 program. The data analysis technique used descriptive analysis and simple linear regression analysis. Before testing the hypothesis, the analysis requirements test was conducted, namely normality and linearity tests using the SPSS 25 program. The results of the research from information services had an average of 132, a frequency of 60% with a useful category and learning motivation in the medium category had an average of 195, a frequency of 71%. In the results of tcount 10.253 > ttable 1.97756, a significance level of 5% means that information services through the Whatsapp Group media have a significant impact on increasing students' learning motivation during the pandemic with an R Square of 44% being in the strong category. This shows that information services through Whatsapp Group can be used as a strategy in increasing students' learning motivation, especially during this pandemic. This research is expected to be used as a reference and reference material to further innovate in providing information services to students' learning motivation.

Study on Structural Reliability of Prestressed Reinforced Concrete Beam Bridges Based on Full Probability Analysis

A three dimensional(3D) finite element model is established for a prestressed concrete girder bridge, list the limit state equation and variable probability distribution model, obtain the failure probability and reliability index of the limit state equation based on the Monte-Carlo method, investigate the reliability index’s sensitivity to random variables for limit state equations of bridge bearing capacity. The specific method of the research on the structure reliability index calculation is to select a suitable way that can fit the research’s object among the center point method, the checking-point method, the Monte-Carlo method, the importance sampling method, and so on. Authors use finite element software ANSYS to build model and perform 3D force analysis. According to the results, authors can determine the bridges’ failure modes under the state of 3D stress. Then, authors can list the possible limit state equations related to Stiffness, strength, function, durability, and some character else. After determining the bridge’s structural limit state equation and the probability distribution model of the variables, determine the distribution function of each impact factor and its characteristic parameters through the site survey data and other related data surveys. Then, use the Monte-Carlo method for the calculation of bridge reliability index, obtain the failure probability and reliability index of each limit state equation, analyze the sensitivity of each variable to the reliability index under the ultimate state of the bridge’s bearing capacity. At last, authors give construction quality control plans and suggestions according to the data above.

A data-driven accurate battery model to use in probabilistic analyses of power systems

Analytical battery models depend on a set of complex nonlinear equations that make them impractical to use in probabilistic analyses (e.g., reliability evaluation) of power systems. Machine-learning algorithms have the potential to reduce or even avoid the computational complexities of incorporating actual battery characteristics in probabilistic analyses. In this paper, a neural network (NN)-based approach is proposed to develop a battery model that captures the non-linear interactions between charging/discharging power and battery state of charge (SoC). In the proposed approach, an NN with a rectified linear unit activation function is trained using historical data generated from an experimentally validated battery model. Another NN with linear activation function is trained to capture the relationship between charging/discharging power limits and SoC. Weights and biases of the trained networks in conjunction with mixed integer linear programming are used to develop an accurate and computationally attractive battery model. Also, a mathematical model is formulated to accommodate the proposed battery model in power system reliability evaluation. Moreover, a genetic algorithm-based approach is used to determine optimal locations for batteries considering the developed model to enhance reliability of power systems. The proposed approach is demonstrated on a modified version of the IEEE 33-bus distribution system. Monte Carlo simulation is performed to calculate reliability indices. The results show that the proposed battery model is effective to incorporate actual battery characteristics in probabilistic analyses (evaluating reliability and finding optimal battery locations) of power systems.

Использование композиционных и суперпозиционных законов распределения вероятностей отказов при оценке надежности электротехнических изделий военного назначения

An implementation of the developed computational structural method for assessing the reliability of complex electrical products. The basis of this method is the use of combinations of composition and superposition laws of distribution of probabilities of failures. The estimation of reliability of a rotating transformer type ВT-5. The calculated reliability indices are compared with results of standard test ВT-5 for reliability. Received high convergence of the results.

Algorithm for calculation of reliability indicators based on monitoring of technical condition parameters

Material by definition of local indicators of reliability of self-propelled farm vehicles, on the basis of monitoring of the controlled resource parameters used for definition of technical condition of the equipment is presented in article. The main dependences when calculating local indicators of a resource are given, examinees of cars/knots/interfaces.

Comparison of metaheuristic optimization techniques including Equilibrium optimizer algorithm in power distribution network reconfiguration

Equilibrium Optimizer (EO) is a new search algorithm inspired by the balance state of a simple and dynamic mass that is well-mixed on the region of the control volume. In this study, the EO algorithm is applied to the power distribution network reconfiguration (PDNR) for reducing active power loss, enhancing the voltage magnitude, and improving the reliability indices. The main contribution of this study is to provide a broad perspective on solving the reconfiguration problem by statistically comparing popular algorithms in the literature. The other contribution is a new algorithm has been developed for reliability index calculation, and the results are compared with the commercial software Etap. The performance of the EO algorithm has been discussed in four different distribution test systems and compared to ten meta-heuristic search algorithms studied in the literature. According to the statistical results of the analyses, the EO algorithm has provided the best performance in the solution of the reconfiguration problem in terms of several aspects such as having a lower error rate and attempting to reach the global optima successfully more than the other ten algorithms. The standard deviations of EO are calculated as 0, 3, 2.7, and 25.6 for 16-bus, 33-bus, 69-bus, and 118-bus test systems, respectively. To sum up, the proposed algorithm shows a competent, efficient and promising solution in PDNR.

АНАЛІЗ НАДІЙНОСТІ ШАСІ РЕГІОНАЛЬНОГО ПАСАЖИРСЬКОГО ЛІТАКА АН-140 НА ПОЧАТКОВОМУ ЕТАПІ ЕКСПЛУАТАЦІЇ

The article presents an analysis of the reliability of the chassis of the regional passenger aircraft AN - 140 at the initial stage of operation, as well as general information about the aircraft, front and main supports of its landing gear. The average failure rate and the total number of failures over a period of time are used as reliability indicators. The calculation of reliability indicators is based on failures detected during periodic maintenance (PM) of aircraft on planned forms 1H - 4H in the maintenance organization Part - 145 and entered into defective statements in accordance with the Management Maintenance Organization. These forms are made in accordance with the Aircraft Maintenance Manual of AN - 140 with a frequency of 500±50 flight hours. To analyze the reliability of the chassis selected a fleet of six aircraft AN - 140 and AN - 140 - 100 with a total flight of 12,000 hours and is divided into three groups by the date of their manufacture and the improvements made on them - "Leader Planes," "Refined Aircraft" and "Serial Aircraft". The condition of sampling the fleet of aircraft is the flight time of 2000 hours for each instance and the execution of four forms of PM on a swoop to form 4N. The dependence of the number of failures of the landing gear of each aircraft on the shape of the PM, the average flight of failure of the fleet and each aircraft individually, the total number of failures of the landing system for each instance of the aircraft, the most denied elements of the main and front landing gear of the aircraft are presented.Based on the results of the analysis of these reliability indicators, both generalized conclusions on the distribution of the number of failures by groups and aircraft instances, and on the specific most denied elements of the chassis system as a whole are presented. The tendency to reduce the number of failures and increase the average flight to failure, depending on the duration of aircraft operation and the manufacture date, has been revealed.

A Multi-Objective Reconfiguration Scheme for Reliability and Energy Usage Enhancement of Distribution Systems in the Presence of Wind Turbines Using the MOHSA Optimization Algorithm

The stochastic nature of the active power generated by wind turbines (WTs) has posed new challenges to the reliability assessment, load flow analysis, and reconfiguration process of distribution systems penetrated with WTs. In this paper, a new optimization approach has been presented to find the best configuration of the distribution system along with optimal locations of WTs. This is aimed at maximizing the reliability of the system, while energy losses are minimized. To this end, based on the graph theory and the system topology, a simple technique is proposed for finding minimal cut sets that could be used for calculating reliability indices. Furthermore, the multiple flow directions created in the presence of WTs cause difficulties in calculating reliability indices and in performing load flow analysis. Accordingly, a new concept called the independent reliability zone is introduced to overcome these problems. In this paper, the multi-objective harmony search algorithm, due to its suitability for multi-objective problems, is employed as a solution for solving the proposed optimization problem. The effect of the proposed approach has been evaluated on both test and real systems. The results show that using the proposed approach, a more practical solution is achieved for low-cost and reliable 24-hour planning of the system in the presence of uncertainties in DGs.

Calculation of Reliability Indicators in Nonmonotone Logical-Probabilistic Models of Multilevel Systems

Calculation of Reliability Indicators in Nonmonotone Logical-Probabilistic Models of Multilevel Systems

Reliability evaluation of bulk power systems with wind generation using small signal stability analysis

This paper presents a computationally efficient methodology for reliability evaluation of bulk power systems with wind power generation using small-signal stability analysis. The methodology is based on the application of Monte Carlo simulation to calculate reliability indices, where the sampled system states are evaluated by means of their small-signal stability condition. Therefore, the system small-signal stability is evaluated for scenarios that consider the failure of generation and transmission assets and the unavailability and power variations of wind farms. Unlike previous works, the proposed methodology does not consider the probability of small variations in system parameters, but instead the probability of occurrence of the scenarios themselves including the large and nonlinear variations resulting from network failures. This allows comparing different alternatives for the planning of large power systems, such as different PSS settings or system reinforcement solutions, in a more realistic approach. Additionally, the methodology uses a non-conventional partial eigenvalue solution focusing on a user-defined subset of poles of interest, efficient and practical for the small-signal analysis of large-scale power systems.

An Algorithm to Search for All Minimal Cuts in a Flow Network

Reliability evaluation approaches exploit a variety of tools for system modeling and calculation of reliability indices. Most proposed approaches in the literature are in terms of minimal cuts (MCs) or minimal paths. Hence, finding all the MCs in a network is an attractive problem in network flow and reliability theory. Here, investigating some works related to the MC problem, we first point out a number of defects in certain proposed algorithms, and present certain new techniques to rectify the flaws in two algorithms. Moreover, we present some techniques to improve the algorithms. Using our results, we propose an improved algorithm for finding all the MCs in a flow network. A benchmark network example is used to illustrate the performance of the algorithm. The proposed algorithm is shown to be correct. Finally, after establishing the complexity results, we demonstrate the proposed algorithm to be more efficient than some existing algorithms.

Reliability analysis of deepwater explosion test vessel based on dynamic prediction

A deep-water explosion test vessel is an important test equipment which is filled with water to simulate different water depth environment by loading different hydrostatic pressure, and it can be used to study deep water explosion theory and engineering technology based on the similarity principle. In order to ensure the safety of vessels used in deep-water explosion test, a random-interval dynamic reliability model based on intelligent prediction is proposed in this paper. A GRNN prediction network of vessel response is established through dynamic test data, and the maximum strain interval variable of the vessel is obtained. Considering the random characteristics of the vessel structure, the reliability analysis of the in-service deep-water explosion test vessel is carried out. During the period, three methods are used to calculate the reliability index, and the analysis shows that for the vessel structure with high reliability and lack of sample data, the hybrid reliability model based on dynamic prediction is established by the calculation of interval reliability index. The method is simple and feasible. At the same time, the interval variables of the model change with the structural dynamic test data, and the uncertainty analysis of the structure is also dynamic. Therefore, the reliability of the container obtained is also changing with the service process, and has dynamic characteristics, which can better reflect the performance changes of the container during the service period and provide the basis for the use and maintenance decision of the container.

Research on evaluation method of energy supply reliability of regional energy Internet

This paper studies the reliability evaluation technology of regional energy Internet and represents a reliability evaluation method considering the optimal load reduction strategy. The application scenario of regional Energy Internet with power system as the core is built. The specific form is that multiple Integrated Energy systems are connected to the superior distribution network through the tie line. The reliability evaluation index system of power system and regional energy Internet is introduced. Based on the modelling of components in the regional energy Internet application scenario in this paper, the operation model and two-state Markov model are mainly established for the renewable energy power generation devices, energy coupling devices and energy storage devices in IES. The optimal load reduction models based on load classification are established for the faults of distribution network lines and the faults of IES internal components connected to the distribution network in regional energy Internet respectively. Through the construction of different application scenarios, the load reduction situation under different faults and different component parameters is analysed, and the corresponding reliability index calculation and result analysis are carried out.

Index of the state of reliability of the heat supply system on the example of an individual residential building

The development of scientific and technological progress has led to the creation of many technical solutions for implementation in the heat supply system. Such solutions, as a rule, are energy-saving, automated, and are positioned by manufacturers as a quick payback. Over time, the cost of such technologies decreases to a level acceptable to most citizens. The introduction of inexpensive energy-saving technologies is becoming more and more widespread. Heat supply systems for even small buildings are becoming more and more complex and device-rich. Modern technologies that are energy-saving include, for example: a heat pump with the extraction of thermal energy from the ground; heat pump with the intake of heat energy from the outside air; recuperator of ventilation emissions with the intake of heat energy from ventilation emissions; thermal accumulators; individual heating station with weather-dependent automation; individual temperature regulators for heating devices; transition from metal pipes to plastic ones with insulation; bimetallic radiators for heating systems, etc. The issue of the durability of several possible options for the implementation of the heat supply system, complicated by the introduction of many different modern technologies, both in terms of the principle of operation and the achieved effect, is relevant. In this case, the use of element-by-element reliability calculation becomes much more complicated. First, the values of the failure rates for various types of modern equipment are usually trade secrets and are not provided by the manufacturer. Secondly, the excessive complication of modern heat-regulating devices does not allow making their element-by-element calculation of reliability due to the inaccessibility of information about a variety of patented solutions. Thirdly, for many new devices, sufficient operating time has not yet passed for the accumulation of statistical information sufficient to determine the value of the failure flow. The listed features stimulate the transition from element-by-element calculation of the reliability of heat supply systems to the calculation of reliability indices. This approach allows you to go to the integrated assessments of the reliability of the heating system of the building, to compare the predicted values of reliability and operating costs for various options for modernizing the building. Clarification of the algorithm and the transition to an index approach for assessing the reliability of heat supply systems will determine the flow of failures of system elements, which will allow assessing the reliability of the system and, according to the data obtained, take measures that will increase the longevity of heat supply systems. On the example of the heat supply system of an individual residential building, indices were determined for the current state of the system, as well as for two options for its modernization. It is shown that the complication of the building heat supply system does not always lead to a decrease in its reliability. Recommendations are formulated for the modernization of the building’s heat supply system, leading to an increase in the reliability index.