Reliability Evaluation Of Complex System Research Articles

A study on Bayesian method for reliability evaluation of small sample size aviation support systems

In order to realize the reliability evaluation of small sample size aviation support system with known prior information, the Bayes methods of system reliability evaluation are given by using the second-order moment equivalent method, relative least squares method (RLS method), maximum entropy method (ME method) and Chebyshev polynomial method respectively, and the accuracies of the above Bayes synthesis methods are compared and analysed through an example. The results show that the ME method and RLS method have higher evaluation accuracy than the second-order moment equivalent method and Chebyshev expansion method. Finally, ME method and RLS method are applied to the reliability evaluation of aviation support system, and good evaluation results are obtained. At the same time, it provides a valuable reference for the reliability evaluation of complex system with small sample size in engineering practice.

Reliability Evaluation of Superluminescent Diodes in Space Environment Based on Bayesian Networks

Reliability evaluation of electronic systems in space environment is a critical issue. In this work, reliability evaluation of superluminescent diode (SLD) systems, which are sensitive to both displacement damage effects and charge–discharge effects, was investigated by the Bayesian network model. Displacement equivalence model of the SLDs is verified by the irradiation results of 5-MeV protons and 1-MeV electrons. Charge–discharge effects of SLDs are induced by 110-keV electrons. Orbital energy spectra and cumulative distribution functions for the equivalent irradiation fluence are calculated by self-built software. Based on the experimental and calculated results, the Bayesian networks under various conditions are established. The probabilities of the type of faults prone in the system under each condition can then be analyzed and quantified. The proposed method provides a good idea for on-orbit reliability evaluation of complex systems.

White-Box and Black-Box Reliability Modeling Framework: Integration Through Analytical Model and User Profile Validation via Deep Learning — A Practitioner’s Approach

Software reliability evaluation of complex systems is always a challenging task with conventional methods comprising both functional as well as nonfunctional aspects of real-world applications. Prevailing model frameworks moreover apply a nonfunctional approach (black-box model) that is modeled on defect data or through a functional approach (white-box model) that uses component or state-based interactions. Also, other challenges involve integrating both approaches, and validating user profiles of software operation. Further, reliability assessment is one among the most important and desirable qualities of service requirements of software systems, particularly in monitoring critical business transactions. Here, we propose a model framework to evaluate the overall reliability estimation involving both functional and nonfunctional model analyses using: (a) white-box assessment based on intercomponent analysis via component-based Cheung’s model and user profile validations with one of the identified deep learning techniques and (b) black-box modeling evaluation via generalized stochastic Petri nets based on orthogonal defect classification. A newly introduced deep learning model using white-box analysis is validated with pertinent usage profiles to establish a new trend in artificial neural networks and as well with software reliability estimation. Additionally, we introduce and present a quantitative technique — analytical hierarchy process — to integrate reliability assessment and provide weights to the white-box and as well for black-box approaches to quantify overall reliability estimation. The proposed framework is illustrated with an application case study.

An Efficient Library for Reliability Block Diagram Evaluation

Reliability Block Diagrams (RBDs) are widely used in reliability engineering to model how the system reliability depends on the reliability of components or subsystems. In this paper, we present librbd, a C library providing a generic, efficient and open-source solution for time-dependent reliability evaluation of RBDs. The library has been developed as a part of a project for reliability evaluation of complex systems through a layered approach, combining different modeling formalisms and solution techniques at different system levels. The library achieves accuracy and efficiency comparable to, and mostly better than, those of other well-established tools, and it is well designed so that it can be easily used by other libraries and tools.

Multi-State System Reliability Evaluation and Component Allocation Optimization Under Multi-Level Performance Sharing

With the development of science and technology, the structure of engineering system has become increasingly large and complex. In order to ensure the safety and stability of the system in operation, the reliability evaluation of complex system has become an important research field. However, previous studies on the reliability of multi-state systems did not take into account the multi-level performance sharing in the system, and it has been unable to accurately assess the reliability of such complex systems. Therefore, based on the actual engineering system, this paper proposes a multi-state system with multi-level performance sharing mechanism. On this basis, we established a system reliability evaluation model using universal generating function technique. Through numerical examples, the application of the model and analyze the influence of different parameters on system reliability are demonstrated. In addition, we also use genetic algorithm to optimize the allocation of components in the system, so as to improve the reliability of the system. Different from the previous studies on system reliability with common bus performance sharing, the system proposed in this study is more general.

Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability

Multi-state components, common cause failures (CCFs) and data uncertainty are the general problems for reliability analysis of complex engineering systems. In this paper, a method incorporating fuzzy probability and Bayesian network (BN) into multi-state systems (MSSs) with CCFs is proposed. In particular, basic theories of multi-state BN and fuzzy probability are developed. Moreover, a model integrating CCFs with BN has also been illustrated. In order to incorporate fuzzy probability into MSSs reliability evaluation considering common parent node generated by CCFs, fuzzy probability has to be translated into accurate probability through defuzzification and normalization methods which are both elaborated. In addition, quantitative analysis based on BN is carried out. In this paper, feed system of boring spindle in computer numerical control machine is analyzed as an example to validate the feasibility of the proposed method. It can improve the ability of BN on reliability evaluation of complex system with uncertainty issues.

Trans-layer model learning: A hierarchical modeling strategy for real-time reliability evaluation of complex systems

Techniques addressing the loading condition of components in complex systems are of great significance for the real-time reliability analyses of systems. To recover component observabilities with combined condition monitoring data and empirical rules, an information criterion identifying the necessary data/rule set for the modeling of systems with the same hierarchical topologies to real-in-world realizations, referred to as trans-layer model learning (TLML), is proposed and proved. Then, with regard to general multi-component dynamic systems, a specific TLML algorithm is proposed. In this algorithm, the loss function and alternative training scheme of component models are specified for harnessing the information from sensor readings and empirical rules to serve the modeling. TLML is applied first on a simulation system to testify its ability to reveal component loading conditions, and then on an aircraft engine to test its effectiveness in improving the Residual Useful Life (RUL) prediction performance of engine turbine blades. Results show that TLML can provide real-time estimations of component loading conditions with sufficient accuracy, and thus improve the precision and reliability of the RUL estimation of system parts.

Fuzzy variable based fuzzy non-linear programming approach for optimization of complex system reliability

All most all systems in the field of science and technology are well complicated by the advent of modernity. Complex system reliability is mainly dependant on the credibility of its components. It is very difficult to evaluate precise value of component's reliability at the beginning stage of reliability evaluation, due to unavailable or inadequate information. In this respect, fuzzy reliability variable can play an important role in complex system reliability evaluation. In this paper, a fuzzy reliability variable based fuzzy non-linear programming problem is formulated to maximize the complex system reliability. Symmetrical trapezoidal fuzzy numbers are used as fuzzy variable for the component's reliability. Since fuzzy variable for optimization is not well defined, we first reduced the problem to an equivalent multi-objective non-linear programming problem. The proposed approach is applied on landing system of Boeing 747D airplane to evaluate the system reliability in fuzzy environment. The proposed approach and the complex system reliability model are well substantiated by providing numerical examples.

Reliability Evaluation of Complex System with Fuzzy Reliability of Components using Interval Nonlinear Programming

We have considered reliability of components of complex system is fuzzy in nature. Since reliability components are taken fuzzy in nature, so system reliability is also in fuzzy nature. We apply Zadeh’s extension principal and interval arithmetic operation to evaluate reliability of the system assembled with fuzzy reliability of components. We approximate the system reliability to a fuzzy number and evaluate the corresponding maximum divergence. Here, we demonstrate a bridge network whose components reliability are taken as triangular fuzzy number. Evaluating reliability of the system belongs to an interval. We have considered cost constrained goal as an interval number, interval nonlinear programming is used to find out the system reliability. Numerical examples are given to illustrate the approach to evaluate the system reliability.

Using state aggregation for reliability evaluation of a class of redundant systems

A mathematical model based on state aggregation is proposed for reliability evaluation of complex systems with slack time and structural redundancy. Formulas for the reliability characteristics are derived and their errors are estimated.

A complex system reliability evaluation method

This paper presents a newly developed method to evaluate reliability of complex systems composed of independent three-state devices. The method is demonstrated with the aid of a hypothetical example of a complex system. In addition, the impact of unit (i.e. three-state device) open and short mode failure probabilities on bridge network reliability is shown.

Monte Carlo simulation for reliability evaluation of complex systems

A complex system of s-dependent and s-independent units is considered in this paper for system reliability evaluation. It is also assumed that failure of any unit in the dependent set increases the failure probabilities of the remainder in the set. A general ease of partial redundant subsystems is considered. A computational algorithm to compute effective failure rates of the remaining components which fail sequentially, is explained for programme implementation. Fault-tree logic for the system failure is used as one of the subprogrammes. The advantage of this approach is that it can be used for a large complex system without any difficulty, besides many advantages normally associated with the fault-tree technique.

Reliability evaluation A comparative study of different techniques

Reliability evaluation of complex systems is of interest to engineers of all disciplines. The techniques for reliability evaluation depend upon the logic diagram of the system. System reliability evaluation is straight forward in case of series-parallel systems; while this is not so in general nonseries parallel systems. In this paper, many different techniques for reliability evaluation of general systems have been presented. Merits and demerits of every method are discussed. An example is solved by all the methods to have a comparison of computational labour involved and the size of final derived reliability expression.