Proposed Reliability Evaluation Method Research Articles

Reliability assessment of an aircraft locking mechanism considering tribocorrosion and correlated failure modes in a marine environment

Landing gear door locking mechanisms are critical for aircraft safety, as their failure can lead to severe accidents. Therefore, these mechanisms must meet stringent reliability requirements. This study introduces a reliability evaluation method for a locking mechanism operating in a marine environment, which integrates dynamic simulation with a tribocorrosion experiment of the joints. Initially, a multibody dynamic model of the locking mechanism was developed to establish the boundary conditions for the joints. Subsequently, an accelerated tribocorrosion experiment was performed to assess the tribocorrosion behavior of these joints. Based on the experimental outcomes, the motion torque and output of the locking mechanism were determined. Considering the correlation between failures due to insufficient accuracy and jamming, an improved response surface methodology utilizing cross-utilization of experimental points was developed. Reliability of the locking mechanism was subsequently confirmed. The present findings indicated that the maximum wear depth in the corrosive environment increased by 25.28 μm (37.15 %) compared to a non-corrosive, dry friction environment. Similarly, the maximum friction coefficient in the corrosive environment increased by 0.0818, which corresponds to an increase of approximately 11.76 %. Furthermore, the proposed reliability evaluation method proved to be 33 % more efficient than the traditional response surface method.

Optimal operation of microgrid with consideration of V2G's uncertainty

AbstractThe aggregation of the remaining battery capacity of electric vehicles (EVs) can be used as distributed energy storage to participate in the microgrid optimisation through vehicle‐to‐grid (V2G) technology. However, the reliability of this service to be delivered is affected by the uncertainty of EVs’ behaviour. The un‐reliable service will bring risks in the operation of microgrid when EVs’ V2G electricity is regarded as an important flexibility resource. This paper, first proposes an analytical method to quantify the reliability of EV aggregation's (EVA's) V2G electricity based on the analysis of historical charging data and compound Poisson process. Based on this model, electric vehicles aggregators can evaluate the V2G bid quantity for any time slot on day t+1 according to the reliability requirements. Secondly, an optimal operation model of microgrid with consideration of V2G's reliability is considered. Finally, a test system with photovoltaics (PVs) and EVA on top of the original IEEE 33‐node system is used to verify the effectiveness of the proposed model. The results show that with the proposed reliability evaluation method of V2G electricity, the optimal operation of the microgrid can be reached with appropriate evaluation of the capability of the EVA.

Reliability evaluation method of PMFSM system based on hidden Markov

To solve the complex calculation in the reliability evaluation of the motor system with the Markov model, this study developed a reliability evaluation method based on the hidden Markov model (HMM). Next, the developed method was employed in a type of permanent magnet hybrid segmented flux-switching machine (PMFSM). By analyzing and simplifying the components of the PMFSM system, the reliability measurement standard and the failure modes of the respective component were examined, and the relationships between the failure modes of each component and the system parameters were built. The optimal parameter observation sequence was determined by calculating the Minkowski distance, and the HMM was iteratively calculated by using the Baum–Welch algorithm. Moreover, the state transition probability matrix of the system was built, and the system reliability was evaluated. As revealed from the calculation results, the reliability of the PMFSM system is significantly higher than that of the conventional structure at the same time, and the mean time to failure (MTTF) of the PMFSM system is 14.8% higher than that of the conventional structure. Compared with the conventional evaluation method based on the Markov model, the two methods have similar reliability results for conventional and novel PMFSM systems, and the variation trend is the same. It shows that the proposed reliability evaluation method is feasible and effective, and the calculation is simple. The work in this study provides a basis for the design of the novel PMFSM system, and a practical engineering method to efficiently evaluate the reliability of other motor systems.

Accurate Reliability Boundary Evaluation of Approximate Arithmetic Circuit

Approximate arithmetic circuit (AAC) has emerged as a promising high-performance and energy-efficient circuit paradigm, which can be used in many applications with inherent error tolerance. To guarantee the usability of AACs and the availability of resilient applications, it is necessary to analyze the reliability of AACs. Most current literature focus on the error characteristics of AACs and few methods can be applied to estimate the reliability of AACs. These methods mostly have exponential time complexities and evaluate the average reliability assuming the input combinations are equally likely. In reality, the primary input (PI) signals can be given with any probability from 0 to 1. In this article, we assume that the PIs have random signal probabilities and propose approaches to reliability boundary estimation for AACs. First, we propose a new efficient and accurate method to evaluate the reliability of AACs. The method mainly calculates the AAC reliability for an input vector set, and furthermore, during the calculation, the correlation problem is considered to increase accuracy. Then, based upon the proposed AAC reliability evaluation method, we present the approaches to finding the reliability boundary. Randomly given signal probabilities of every PI, two heuristic search algorithms are utilized to find the lowest reliability. A comparison of the results on three series of AACs and the circuits in the EvoApprox8b library confirms that the proposed reliability evaluation method is more accurate and efficient than the previous method. Further experiments verify the plausibility of the calculated reliability boundary of AACs.

Data-Driven Reliability Evaluation of the Integrated Energy System Considering Optimal Service Restoration

The demand for environmental protection and energy utilization transformation has promoted the rapid development of integrated energy systems (IES). Reliability evaluation is a fundamental element in designing IES as it could instruct the planning and operation of IES. This study proposes a novel data-driven reliability improvement and evaluation method considering the three-state reliability model and an optimal service restoration model (OSR). First, a multi-energy flow model is introduced and linearized in order to reduce the computing complexity. Next, a three-state reliability model is developed, considering the transitional process and partial failure mode. Furthermore, an optimal service restoration model is established to determine the best repairment moment for minimizing the load curtailment, and a data-driven reliability evaluation method is developed that integrates OSR and models the stochastic state transition process using the historical measurement data of the smart meters. Finally, the proposed reliability evaluation method is tested on a test IES, and the numerical results validate its effectiveness in evaluating the reliability of IES and improving the overall reliability.

Reliability modelling for linear and circular [formula omitted]-out-of-[formula omitted]: F systems with shared components

Reliability analysis for k-out-of-n systems has received much attention in the field of reliability due to its practical importance. In this work, models for linear and circular k-out-of-n: F systems with shared components, consisting of m subsystems, are discussed. The finite Markov chain imbedding approach cannot be used directly to derive reliability of the considered systems because of the common area existing between adjacent subsystems. For this reason, we first derive the probability that the number of failed components is a given value in the m common areas. Then, all disjoint cases, each of which is regarded as a series system consisting of m subsystems with different initial state probability distributions, are obtained, with which the nith step transition rate matrix is calculated by using the Markov chain technique, for i=1,2,…,m. Finally, the reliability of the system is obtained by summing the reliabilities of all cases along with the finite Markov chain imbedding approach. Some numerical examples are presented to illustrate the efficiency of the proposed reliability evaluation method.

Investigation of impacts of plug-in hybrid electric vehicles’ stochastic characteristics modeling on smart grid reliability under different charging scenarios

Although it is essential to investigate the impacts of the analytical modeling of plug-in hybrid electric vehicles (PHEVs) for reliability and adequacy evaluation of smart grids, this issue has received less attention. This article tries to develop a new analytical reliability and adequacy model of smart grids, considering the precise model of PHEVs. Until now, no solution has been reported to determine the appropriate number of PHEVs’ states in the analytical reliability evaluation methods. In this paper, a novel framework is developed to determine the suitable number of PHEVs’ states that simultaneously guarantees the speed and accuracy of the reliability calculations. The Monte Carlo simulation (MCS) is used to validate the proposed reliability evaluation method of smart grids using the developed analytical model of PHEVs. In addition, the impacts of different stochastic parameters on the adequacy evaluation of PHEVs, such as distance driven, departure time, and arrival time are studied by performing a variety of sensitivity analyses under different charging scenarios. The proposed method is applied to an actual electric distribution network of Kashan, which is located in the Isfahan province distribution company. The comparative test results illustrate the advantages of the introduced analytical reliability evaluation framework. One point that claims attention is the importance of distance driven’s impact and its state reduction in comparison to the impact of arrival time or departure time. Test results imply that reliability calculations of smart grids could be accelerated significantly by investigating the suitable number of discretized states of PHEVs’ characteristics.

A reliability evaluation method for embryonic cellular array based on Markov status graph model

Due to the limitations of the existing fault detection methods in the embryonic cellular array (ECA), the fault detection coverage cannot reach 100%. In order to evaluate the reliability of the ECA more accurately, embryonic cell and its input and output (I/O) resources are considered as a whole, named functional unit (FU). The FU fault detection coverage parameter is introduced to ECA reliability analysis, and a new ECA reliability evaluation method based on the Markov status graph model is proposed. Simulation experiment results indicate that the proposed ECA reliability evaluation method can evaluate the ECA reliability more effectively and accurately. Based on the proposed reliability evaluation method, the influence of parameters change on the ECA reliability is studied, and simulation experiment results show that ECA reliability can be improved by increasing the FU fault detection coverage and reducing the FU failure rate. In addition, by increasing the scale of the ECA, the reliability increases to the maximum first, and then it will decrease continuously. ECA reliability variation rules can not only provide theoretical guidance for the ECA optimization design, but also point out the direction for further research.

Sensor dynamic reliability evaluation based on evidence theory and intuitionistic fuzzy sets

This paper presents a new method for sensor dynamic reliability evaluation based on evidence theory and intuitionistic fuzzy sets when the prior knowledge is unknown. The dynamic reliability of sensors is evaluated based on supporting degree between basic probability assignments (BPAs) provided by sensors. First, the concept of asymmetric supporting degree is proposed. By transforming BPAs to intuitionistic fuzzy sets, supporting degree between BPAs is calculated based on intuitionistic fuzzy operations and similarity measure. Then the relationship between dynamic reliability and supporting degree is analyzed. The process of dynamic reliability evaluation is proposed. Finally, the proposed dynamic reliability evaluation is applied to evidence combination. A new evidence combination rule is proposed based on evidence discounting operation and Dempster’s rule. Comparative analysis on the performance of the proposed reliability evaluation method and evidence combination rule is carried out based on numerical examples. The proposed method for data fusion is also applied in target recognition to show its feasibility and validity.

Reliability of nonrepairable phased-mission systems with common bus performance sharing

This article considers the reliability analysis of phased-mission systems with common bus performance sharing. The whole system consists of client nodes, service elements, and a common bus redistribution system and it undertakes a multi-phase mission. In each phase, the service elements must satisfy the demands of the prespecified client nodes set. The service elements can share their surplus performance with other client nodes through the common bus. In any phase, the system fails if the demands of the prespecified client nodes set are not satisfied. In other words, the entire system succeeds if the demands of the prespecified client nodes set are satisfied in all phases. The reliability of the proposed model is analyzed by the backward recursive algorithm. The optimal allocation problem is solved by the genetic algorithm. Two examples are presented to demonstrate the proposed reliability evaluation method and optimal allocation algorithm.

Studying the Reliability Implications of Line Switching Operations

This paper proposes a method for studying the reliability implications of line switching operations in power systems. Two case studies are conducted on RTS and IEEE 118-bus system to illustrate this method. This method is designed to explore previously overlooked areas in reliability evaluation of line switching operations. Line removal test is proposed to obtain simulation data of the system, and then with risk analysis and impact analysis, six reliability indices are used to evaluate reliability performance of each transmission line in the system. Instead of the traditionally used mean value, this method introduces variance into analysis. Weibull distribution is used to reconstruct distributions of reliability indices which provide worst case scenario comparisons in reliability evaluation. Eventually, with results obtained from the proposed reliability evaluation method, categorization for line switching operations is introduced to classify all transmission lines based on their reliability performance. The categories provide reliability implications of line switching operations and can be used for guidance in actual operations.

Evaluating evidence reliability based on intuitionistic fuzzy MCDM model

In this paper, the combination of unreliable evidence sources is considered based on multiple criteria decision making (MCDM) model in intuitionistic fuzzy environment. In the intuitionistic fuzzy MCDM framework, evidence sources can be evaluated based on the ranking method between intuitionistic fuzzy numbers. A generalized discounting operation on unreliable evidence bodies is firstly proposed to deal with uncertain reliability factors. Then we mainly investigate the evaluation evidence reliability factors without prior knowledge. Our proposed evaluation method is based on the principle of self-assessment. It is implemented by the probabilistic comparison between intuitionistic fuzzy values. Our proposed evaluation method is independent to the dissimilarity measure between basic probability assignments represented by an evidential distance. Numerical examples demonstrate the performance of our proposed reliability evaluation method.

Reliability analysis and optimal structure of series-parallel phased-mission systems subject to fault-level coverage

ABSTRACTMany practical systems have multiple consecutive and non-overlapping phases of operations during their mission and are generally referred to as phased-mission systems (PMSs). This article considers a general type of PMS consisting of subsystems connected in series, where each subsystem contains components with different capacities. The components within the same subsystem are divided into several disjoint work-sharing groups (WSGs). The capacity of each WSG is equal to the summation of the capacities of its working components, and the capacity of each subsystem is equal to the capacity of the WSG with the maximum capacity. The system capacity is bottlenecked by the capacity of the subsystem with the minimum capacity. The system survives the mission only if its capacity meets the predetermined mission demand in all phases. Such PMSs can be commonly found in the power transmission and telecommunication industries. A universal generating function–based method is first proposed for the reliability analysis of the capacitated series-parallel PMSs with the consideration of imperfect fault coverage. As different partitions of the WSGs inside a subsystem can lead to different system reliabilities, the optimal structure that maximizes the system reliability is investigated. Examples are presented to illustrate the proposed reliability evaluation method and optimization procedure.

Risk management of smart grids based on plug-in hybrid electric vehicles' charging considering transformers' hottest spot temperature-dependent aging failures

This paper introduces a stochastic reliability evaluation methodology for quantifying the impact of unmanaged plug-in hybrid electric vehicles (PHEVs') charging on the transformers' hottest spot temperature (HST)-dependent aging failures. Further, a novel PHEVs' charging management method has been proposed from the distribution transformers' dynamic thermal modeling perspective. The proposed reliability evaluation method provided the precise stochastic model corresponding to the PHEV owners' behavior. The introduced reliability evaluation methodology has been applied to an actual distribution system of the Hormozgan Regional Electrical Company in Iran under various PHEVs' charging scenarios. The numerical results imply that the distribution transformers' failures are adversely affected due to unmanaged PHEVs charging. The system under study has been simulated during a 10-year-period. The test results show that the transformers' HST-dependent failures due to the PHEVs' charging demand load exponentially increased as a function of system age. As revealed by the results, the proposed PHEVs' charging management methodology mitigates the aggregated peak load and transformers' HST by deferring the peak charging load to midnight.

Reliability evaluation of a standalone wind-photovoltaic/battery energy system based on realistic model of battery

This paper presents the reliability evaluation technique of a standalone system including renewable energy resources such as wind and photovoltaic (PV), integrated with battery energy storage system. The focus in this study is on the effect of the operating restrictions of battery on system reliability by presenting a new modeling of battery. In this regard, the proposed reliability evaluation method is based on the combination of the analytical and simulation approaches in the domain of adequacy studies. In this technique based on time series approach, the realistic model of the electrochemical behaviors for the battery bank can be considered. The electrochemical behaviors change in different operation conditions, i.e., temperature, state of charge and charging/discharging current. In this way, a sample lead-acid battery is considered and then a new capacity model for the battery bank is presented based on the realistic electrochemical behaviors related to reserve applications. Simulation results for a case study are presented. The influence of battery modeling in the different studies is discussed and the beneficial results are assessed.

Reliability assessment of a standalone wind-conventional/energy storage system using probabilistic production simulation method

This paper presents a reliability evaluation technique for a small standalone system including wind and conventional resources integrated with an energy storage system. A battery bank is considered as the energy storage system. The focus in this analysis is on the effect of battery modeling and its performance on system reliability. In this way, this paper presents an accurate model for the electrochemical batteries, which takes into account all the influential characteristics of the battery related to reliability studies, such as depth of charge, efficiency of charge, and rate of discharge. The proposed reliability evaluation method is based on the combination of a probabilistic production simulation technique as an analytical method and time series technique, in the domain of adequacy studies. By using the probabilistic production simulation technique, not only can the reliability of wind-conventional resources be assessed, but the fuel consumption can also be analyzed. On the other hand, by using the time series approach, the time variation of wind speed and operating constraints of the battery bank can be considered in evaluating the reliability indices. In this paper, a typical lead--acid battery bank is used. It is shown how the accurate modeling of the battery bank can affect the reliability indices. Beneficial results are obtained for different operating strategies and wind penetrations and are then compared.

Reliability analysis of idealized tunnel support system using probability-based methods with case studies

In order to determine the overall safety of a tunnel support lining, a reliability-based approach is presented in this paper. Support elements in jointed rock tunnels are provided to control the ground movement caused by stress redistribution during the tunnel drive. Main support elements contribute to stability of the tunnel structure are recognized owing to identify various aspects of reliability and sustainability in the system. The selection of efficient support methods for rock tunneling is a key factor in order to reduce the number of problems during construction and maintain the project cost and time within the limited budget and planned schedule. This paper introduces a smart approach by which decision-makers will be able to find the overall reliability of tunnel support system before selecting the final scheme of the lining system. Due to this research focus, engineering reliability which is a branch of statistics and probability is being appropriately applied to the field and much effort has been made to use it in tunneling while investigating the reliability of the lining support system for the tunnel structure. Therefore, reliability analysis for evaluating the tunnel support performance is the main idea used in this research. Decomposition approaches are used for producing system block diagram and determining the failure probability of the whole system. Effectiveness of the proposed reliability model of tunnel lining together with the recommended approaches is examined using several case studies and the final value of reliability obtained for different designing scenarios. Considering the idea of linear correlation between safety factors and reliability parameters, the values of isolated reliabilities determined for different structural components of tunnel support system. In order to determine individual safety factors, finite element modeling is employed for different structural subsystems and the results of numerical analyses are obtained in different design scenarios. Finally, the reliability index values are obtained for the entire support structure in different design scenarios. The results of the work demonstrates that proposed reliability evaluation method of tunnel support system is effective not only for investigating the reliability of individual elements in the structure, but also for building an overall estimation about reliability performance of the entire tunnel structure.

Reliability Assessment of Smart Grid Considering Direct Cyber-Power Interdependencies

Smart grid initiatives are becoming more and more achievable through the use of information infrastructures that feature peer-to-peer communication, monitoring, protection and automated control. The analysis of smart grid operation requires considering the reliability of the cyber network as it is neither invulnerable nor failure free. This paper quantitatively evaluates the reliability of modern power systems, which incorporates the impact of cyber network failures on the reliability of the power network. In this paper, four types of interdependencies are defined and a new concept of state mapping is proposed to map the failures in the cyber network to the failures of the power network. Furthermore, in order to evaluate the impact of direct cyber-power interdependencies on the reliability indices, two optimization models are introduced to maximize the data connection in the cyber network and minimize the load shedding in the power network. The effectiveness of proposed reliability evaluation method is shown by a smart microgrid application. The methodology presented in this paper is a start point to optimize the future power grid which has increasingly interdependencies between cyber and power networks.

Study on Reliability Evaluation Method of Structures Using Multi State System

In the conventional reliability-based design method of structures, the reliability of a partially damaged structure that is not satisfied with the demand performance has not been considered. In performance-based design, however, the intermediate state such as partially damaged state that is between two distinguished states (perfect functioning and complete failure) should be considered. Especially, in an emergency, it is important to know if structures that break down partially can function at the level. If a structure is considered to be MSS (Multi-State System), the reliability-based design of this structure can be performed with considering the partially damaged state. In this study, a reinforced concrete short column is treated as a MSS structural example, the three reliability indices such as the availability, the mean performance and the expected performance deficiency are calculated and compared with the reliability index evaluated by a conventional reliability evaluation method, and then some advantages of this proposed reliability evaluation method using MSS is verified.