System Reliability Evaluation Research Articles

Reliability analysis of interval-valued multi-state sliding window system for sequential tasks

In industrial applications, an interval variable with both an upper and a lower bound is utilized to define the bounded or ranged performance of a system or its elements. This paper proposes a new interval-valued multi-state sliding window system for sequential tasks (IMSWS-ST). The proposed system consists of n circularly or linearly connected multi-state elements (MEs) with their performance states described as interval-valued variables. The system function is determined by the ability of any group of r consecutive MEs for completing predetermined sequential tasks with interval-valued demands. To describe and evaluate system reliability, a universal generating function technique is employed, considering the differences between linear and circular configurations. Additionally, we develop a state aggregation method to reduce the computational burden during reliability evaluation. Numerical experiments are then conducted to demonstrate the proposed system model and validate the suggested algorithms. Finally, we investigate the optimal sequencing problem for MEs within the IMSWS-ST to achieve higher system reliability.

Study on Reliability of PACSs with Integrated Consideration of Both Basic and Mission Reliability

Protective relays play a fundamental role in power systems, whose functions consist of three parts, namely protection, automation, and control, thus called the PAC altogether. It turns out that the architecture of a PACS (protection, automation, and control system) may exert a direct impact on the reliability of protective relay systems, previous studies of which are often conducted on the assumption that intelligent electronic devices (IEDs) have a constant fault rate with only mission reliability of the systems considered. To obtain a more accurate evaluation of system reliability bearing system maintenance in mind, this article proposes a novel method to appraise the reliability of PACSs with integrated consideration of basic and mission reliability. Firstly, the basic reliability of IEDs is calculated by parts count prediction, which will provide a more precise fault rate of IEDs. Secondly, the reliability of PACSs is analyzed by the reliability diagram and Markov model. By using the parts count prediction method to calculate the failure rate of the device, the steady-state probability rate will be accurate more than 0.0107%. At last, a quantitative criterion is finalized for selecting a suitable architecture easily.

Quantitative evaluation of tourism crisis response policies: overview and lessons from China’s tourism epidemic response policies

ABSTRACT Governments and DMOs have enacted a number of policies to cope with the impacts of unpredictable disruptions, such as COVID-19, on recovering regional tourism industries. Retrospective analysis and scientific evaluation of the content, quality, and implementation efficacy of existing policies serve as an important reference for future policy formulation, modification, and improvement. This study utilized the PMC-AE index model to construct an evaluation model of the tourism epidemic response policy and then evaluated and compared China’s tourism policies at the national and provincial levels from the perspective of policy formulation. The results indicated that: First, China’s tourism epidemic response policy included four categories: epidemic prevention and control and follow-up supervision, relief support and recovery development, resumption of work and production, and consumption promotion. Second, most of the policies remain relatively high, and the scores at national and provincial levels decline from high to low, forming a ‘top-down’ pattern to cope with the epidemic’s impact effectively. Simultaneously, there were no significant differences between policy types and regions, but provincial policies were significantly more targeted than specialized policies. Lastly, some tourism epidemic response policies remained problematic, particularly concerning insufficient predictive content, a single target audience, the structural imbalance of incentive methods, and the lack of cooperation between the publishing parties. This study validated the reliability and efficacy of the PMC-AE policy evaluation system in tourism policy research and provided a reference for formulating future epidemic response policies.

A subset simulation analysis framework for rapid reliability evaluation of series-parallel cold standby systems

A subset simulation analysis framework for rapid reliability evaluation of series-parallel cold standby systems

System reliability evaluation of 12-pulse series converter station based on improved Dijkstra algorithm

System reliability evaluation of 12-pulse series converter station based on improved Dijkstra algorithm

Reliability Evaluation and Improvement of Power Transmission Systems Using Series Compensation

Reliability Evaluation and Improvement of Power Transmission Systems Using Series Compensation

Application of REPAS to analyze the sump clogging issue following a LOCA and its impact on the reliability of the ECCS long-term core cooling function

Sump clogging has been identified as a relevant issue after an accident occurred in the Barsebäck-2 nuclear power plant in Sweden (1992). Following a steam line Loss of Coolant Accident (LOCA) due to the inadvertent opening of a safety relief valve, the jet stripped some insulation material from nearby pipes. The insulation debris were transported to the inlet of the strainers for the drywell spray system, thus clogging the intake. The accident was not serious but showed that the Emergency Core Cooling System (ECCS) could have failed. As a consequence, several actions have been undertaken by international organizations, regulatory bodies and nuclear power plant owners to characterize this issue, and propose solutions and improvements. In the present paper, the Reliability Evaluation of Passive Safety Systems (REPAS) methodology is applied to analyze the sump clogging issue and its effect on the long-term core cooling function. Originally developed to evaluate the reliability of passive systems, REPAS is here applied for the first time to an active system. The application is performed using the TRAC/RELAP Advanced Computational Engine (TRACE) code, developed by the USNRC, to simulate a generic three-loop PWR, with an active decay heat removal system.

Reliability evaluation of radial distribution system considering common mode failures and different weather effects

Reliability evaluation of distribution systems plays a crucial role in ensuring the uninterrupted supply of electricity to consumers. This paper presents a comprehensive analysis of distribution system reliability using the Failure Mode and Effects Analysis (FMEA) technique. The study focuses on evaluating the reliability of the distribution system considering various failure modes, including busbar failure, section failure, distributor failure, transformer failure, maintenance-related issues, transient failures, and the impact of weather conditions. The findings of this research can assist utilities and system operators in identifying critical failure modes and implementing appropriate measures to enhance the reliability of distribution systems, ensuring continuous and reliable electricity supply to consumers.

Reliability evaluation of phased-mission systems exposed to random shocks

The paper aims to examine the reliability analysis problem of phased-mission systems that execute multiple consecutive non-overlapping mission phases in a random shock environment. Each phase is carried out by several subsystems which consist of non-repairable components connected in different topology configurations. The random shocks, modeled by a Poisson process, significantly affect the failure rate of components within the dynamic subsystems. The system configuration, success criteria, and component failure behavior may differ from phase to phase. The paper presents technical methodologies to evaluate the mission success probabilities of subsystems in various configurations and proposes a modularization method to compute the reliability of phased-mission systems by combining the mission success probabilities of all subsystems. Finally, a numerical example is provided to illustrate the proposed model and method.

QMU Analysis of Flexoelectric Timoshenko Beam by Evidence Theory

In recent years, with the rapid development of nanotechnology, a new type of electromechanical coupling effect similar to the piezoelectric effect, the flexoelectric effect, has gradually come into the public’s view. The flexoelectric beam that is the main structural unit of the flexoelectric signal output has broad application prospects in the next generation of micro- and nanoelectromechanical systems. Therefore, the investigation of flexoelectric materials and structures has important scientific and engineering application significances for the design of flexoelectric devices. In this paper, a model of flexoelectric Timoshenko beam is established, the deflection, rotation angle, and dynamic electrical signal output of the forced vibration are taken as the system response, and the density ρ , shear correction factor κ , and frequency ratio λ are selected as the key performance parameters of the system. The combination of available data and engineers’ experience suggests that there are random and cognitive uncertainties in the parameters. Therefore, the probability distribution of the system performance response is expressed by the likelihood function and belief function through the quantification of margins and uncertainties (QMUs) analysis methodology under the framework of evidence theory, and the system reliability or performance evaluation is measured by the calculated confidence factors. These results provide a theoretical basis for accurate analysis of flexoelectric components and provide guidance for the design of flexoelectric components with excellent performance.

Seismic Station Quality Monitoring and Evaluation System in Indonesia

Good quality seismic data is needed to produce accurate earthquake information, namely seismic data with low background noise. A reliable monitoring and evaluation system are necessary to determine the quality of seismic stations in recording earthquake waves quickly and accurately. The Seismic Station Quality Monitoring and Evaluation System (SQES) was created to obtain information regarding the quality of seismic data and the quality of seismic station sites efficiently, quickly, and accurately by assessing parameters that affect seismic station quality. Seismic data quality assessment is based on background noise, data continuity, and signal anomalies. In contrast, seismic station site quality is measured based on geological conditions, site class, Power Spectral Density (PSD), and solar energy potential. This system works automatically, semi-realtime, daily, and monthly through a web service that functions continuously to be accessed anytime and anywhere. By obtaining seismic station quality information quickly and accurately, it can be used to monitor the accuracy of earthquake information and optimize seismic station maintenance. SQES has been used to evaluate the quality of 428 seismic stations in InaTEWS and can provide an overview of the quality of seismic stations in Indonesia.

Verification of the Reliability and Validity of a Virtual Reality Cognitive Evaluation System Based on Motion Recognition Analysis Evaluation

Verification of the Reliability and Validity of a Virtual Reality Cognitive Evaluation System Based on Motion Recognition Analysis Evaluation

Software-hardware embedded system reliability modeling with failure dependency and masked data

Traditional system reliability models often ignore failure dependency between subsystems and the existence of system failure masked data, thereby they can’t accurately reflect the reliability modeling analysis of the whole system. This paper investigates an embedded system that comprises software subsystems and hardware subsystems. In order to more accurately assess the embedded system’s reliability, we proposed a reliability superposition model of the software-hardware system with masked data and failure dependency. In the model, the influence of masked failure data and failure dependency between the hardware subsystem and software subsystem is considered in system reliability evaluation, and the influence of fault dependence is solved by Copula function. Estimating the parameters of this model is a challenging task due to the complexity of the parameters. With regards to this, we proposed an immune particle swarm optimization algorithm with enhanced learning ability (IPSO-ELA), which is used to calculate the parameter’s estimation. Additionally, we investigated the impact of varying degrees of failure dependence on system reliability. Finally, the numerical experiment shown that the proposed model, which considers failure dependency among subsystems, outperforms other reliability models that do not. It can be seen from the experimental fitting results and the reliability trend charts that the system reliability when failure dependence is considered is higher than isn’t considered, which is more realistic.

Reliability evaluation of standby redundant systems based on the survival signatures methods

Reliability evaluation of standby redundant systems based on the survival signatures methods

Particle Swarm Optimization Method for Stand-Alone Photovoltaic System Reliability and Cost Evaluation Based on Monte Carlo Simulation

In rural regions with limited access to the power grid, self-reliance for electricity generation is paramount. This study focuses on enhancing the design of stand-alone photovoltaic installations (SAPV) to replace conventional fuel generators thanks to the decreasing costs of PV modules and batteries. This study presents a particle swarm optimization (PSO) method for the reliable and cost-effective sizing of SAPV systems. The proposed method considers the variability of PV generation and domestic demand and optimizes the system design to minimize the total cost of ownership while ensuring a high level of reliability. The results show that for the PSO method with 500 iterations, the error is around 2%, and the simulation time is approximately 2.25 s. Moreover, the PSO method allows a much lower number of iterations to be used in the Monte Carlo simulation, with a total of 100 iterations used to obtain the averaged results. The optimization results, encompassing installed power, battery capacity, reliability, and annual costs, reveal the effectiveness of our approach. Notably, our discretized PSO algorithm converges, yielding specific parameters like 9900 W of installed power and a battery configuration of five 3550 Wh units for the case study under consideration. In summary, our work presents an efficient SAPV system design methodology supported by concrete numerical outcomes, considering supply reliability and installation and operational costs.

Reliability Analysis of a Three-Engine Simultaneous Pouring Control System Based on Bayesian Networks Combined with FMEA and FTA

Pouring is an important process in the production of solid propellant rocket engines, and usually, the cost of a solid propellant rocket engine is extremely high. Therefore, pouring production with high reliability is very important. The pouring of three engines of solid propellant rocket engines simultaneously can greatly improve its production efficiency. However, it makes the system more complex and redundant. For a multi-state system, it is difficult to make an accurate evaluation of system reliability. Aiming at the redundancy of multiple engines and acousto-optic combined control in the three-engine simultaneously slurry pouring alarm control system with dissimilar redundant alarm units, a reliability analysis method is proposed based on the combination of Failure Mode Effect Analysis (FMEA) and Fault Tree Analysis (FTA). The control system is divided into several redundant states according to the alarm function, and then the Bayesian Networks method is used for reliability evaluation and calculation. Finally, the reliabilities of systems with dissimilar redundancy degrees are obtained. The tangible results of this research work are as follows: (1) The research results obtained by applying the FMEA method laid a foundation for the establishment of a fault trees model for analyzing the reliability of the control system using the FTA method, in addition, which can guide the maintenance and fault identification of the control system during engineering application. (2) The calculated value of the reliability of the control system is 0.999989, and the mean time between failures is MTBF is 5 × 104 by using the fault tree analysis method, which proves that the designed three-engine simultaneous pouring system is very reliable. (3) Based on the calculation and comparison of the Bayesian Networks of redundant three-engine pouring control systems, the circuit diagram of the improved control system is identified.

Chronological simulation and Quantitative Evaluation of System Reliability in a Complex Restructured Power System

Ensuring the provision of high-quality and dependable power supply to customers stands as a paramount responsibility within the realm of power systems. The concept of restructuring the power system emerges as an efficient approach to deliver economically viable and uninterrupted power supply. The assessment of power system reliability hinges on various factors, with the reliability index serving as a pivotal metric, dependent on both system security and adequacy. To enhance the reliability index, strategically locating FACTS devices becomes essential, a task facilitated through power flow analysis with specified constraints, pinpointing the weakest points through Genetic Algorithm-driven fast-acting device placement. The correlation between DG establishment and the reliability index was meticulously calculated, further bolstered by the introduction of a Derated Forced Outage Rate for enhanced performance assessment. In the pursuit of heightened power system reliability, sequential simulations prove invaluable, particularly in minimizing Expected Energy Not Supplied (EENS) and improving overall system reliability. The results obtained through sequential simulations underscore the effectiveness of this approach within bulk electrical systems. The installation of multiple FACTS devices in the system's weakest areas facilitated EENS computation, coupled with the assessment of related reliability indices such as system frequency and system duration. This approach not only enhances system reliability but also promotes the economic operation of both transmission and distribution.The simulation results substantiate the alignment of power system reliability objectives in deregulated power systems with the required standards, advocating for the restructuring of power networks. The reliability assessments, driven by the optimal placement of DGs and FACTS devices, reveal substantial improvements in system reliability, underscoring the pivotal role of these technologies in enhancing overall power system dependability.

Analyzing system reliability using conflicting bifuzzy failure rates of the components

Since uncertainty and ambiguity are common in real-world problems, numerous methods based on different kinds of fuzzy sets have been widely used in the evaluation of system reliability over the years. However, these methods are unable to deal with conflict uncertainty, particularly when it comes to the uncertain failure rates of the system's components. This paper introduces the idea of the triangular conflicting bifuzzy set (TCBFS), which is a novel paradigm for dealing with conflicting uncertainty. A novel method is devised to determine the membership and non-membership functions for the system's reliability when subsystems/components exhibit conflicting bifuzzy failure rates. In order to generate the membership and non-membership functions for various system configurations, including series, parallel, series-parallel, and parallel-series systems, non-linear programming is used to derive a number of functions based on conflicting bifuzzy numbers. The validity of the suggested method in modeling and evaluating system reliability with different conflicting bifuzzy failure rates is demonstrated through illustrated scenarios. This novel approach improves the precision and resilience of reliability estimations for systems by providing a more precise representation of uncertainties.

Comparative proteomic analysis of edible bird’s nest from different origins

Edible bird’s nest (EBN) mainly made of saliva that secreted by a variety of swiftlets is a kind of precious traditional Chinese medicine. EBNs from different biological and geographical origins exhibit varieties in morphology, material composition, nutritive value and commercial value. Here, we collected four different EBN samples from Huaiji, China (Grass EBN), Nha Trang, Vietnam (Imperial EBN) and East Kalimantan, Indonesia (White EBN and Feather EBN) respectively, and applied label-free quantitative MS-based proteomics technique to identify its protein composition. First, phylogenetic analysis was performed based on cytb gene to identify its biological origin. Second, a total of 37 proteins of EBNs were identified, among which there were six common proteins that detected in all samples and exhibited relatively higher content. Gene ontology analysis revealed the possible function of EBN proteins, and principal component analysis and hierarchical clustering analysis based on 37 proteins were performed to compare the difference of various EBNs. In summary, our study deciphered the common and characteristic protein components of EBNs of different origins and described their possible functions by GO enrichment analysis, which helps to establish an objective and reliable quality evaluation system.

A Novel Multi-state Bogie System Reliability Evaluation Approach by Extended d-MC Model for High Speed Train

Abstract Bogie is a pivotal system and plays a critical part in the safety and reliability management of high speed rail. However, the available bogie system reliability analysis methods lack the consideration of multi-state characteristics, and the common multi-state reliability analysis methods, being an NP-hard problem, lead to a low efficiency. In order to overcome the mentioned drawbacks, this paper proposes a novel multi-state rail train bogie system reliability analysis approach based on the extended d-MC model. Three different function interactions within the bogie system are considered to build the multi-state bogie system flow network model. Meanwhile, an extended d-MC model is established to remove unnecessary d-MC candidates and duplicates, which greatly enhances the computing efficiency. The bogie system reliability is calculated, and the examples are provided. Numerical experiments are carried out for the different operational conditions of the bogie system and are used to testify the practicability of the method projected in this article, and is is found that the proposed method outperforms a newly developed method in solving the multi-state reliability problems.