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14 pages, 1114 KiB

Open AccessArticle

Nonlinear Doubly Wiener Constant-Stress Accelerated Degradation Model Based on Uncertainties and Acceleration Factor Constant Principle

by Xiaoning Wang, Xiaobao Su and Jinjing Wang

Appl. Sci. 2021, 11(19), 8968; https://doi.org/10.3390/app11198968 - 26 Sep 2021

Cited by 2 | Viewed by 1533

Abstract

Although Wiener process models with the consideration of uncertainties, which are nonlinearity, random effects, and measurement errors, have been developed for lifetime prediction in the accelerated degradation test (ADT), they fail to describe the real degradation process because these models assume that the [...] Read more.

Although Wiener process models with the consideration of uncertainties, which are nonlinearity, random effects, and measurement errors, have been developed for lifetime prediction in the accelerated degradation test (ADT), they fail to describe the real degradation process because these models assume that the drift parameter correlates with the applied stress, while the diffusion parameter is constant. This paper put forward a nonlinear doubly Wiener constant-stress accelerated degradation model, where both diffusion and drift parameters were compatible with the applied stress according to the acceleration factor constant principle. When degradation data were available, we obtained the unknown parameters by applying a maximum likelihood estimation (MLE) algorithm in the constant-stress ADT (CSADT) model taking uncertainties into account. In addition, the proposed model’s effectiveness was validated through an illustrative example, and an application to the traveling wave tube (TWT) was carried out to demonstrate the superiority of our model in practical applications. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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14 pages, 2657 KiB

Open AccessArticle

Reliability-Based Design of an Aircraft Wing Using a Fuzzy-Based Metaheuristic

by Seksan Winyangkul, Suwin Sleesongsom and Sujin Bureerat

Appl. Sci. 2021, 11(14), 6463; https://doi.org/10.3390/app11146463 - 13 Jul 2021

Cited by 8 | Viewed by 2499

Abstract

The purpose of this paper is to design aircraft wing using reliability-based design optimization concerned to fuzzy uncertainty variables. A possibilistic safety index-based design optimization (PSIBDO) with fuzzy uncertainties is proposed to overcome difficult tasks from the original probabilistic problem. The design problem [...] Read more.

The purpose of this paper is to design aircraft wing using reliability-based design optimization concerned to fuzzy uncertainty variables. A possibilistic safety index-based design optimization (PSIBDO) with fuzzy uncertainties is proposed to overcome difficult tasks from the original probabilistic problem. The design problem is to minimize mass of a composite aircraft wing subject to aeroelastic and structural constraints through consideration of the material properties are the uncertainties. The design variables include aircraft wing structure dimensions. The reliability-based design approach is needed to alleviate such a problem. Due to the complexity of the aircraft wing structures design and aeroelastic analysis, nonprobability-based design is an alternative choice to increase computational efficiency in the design process. The optimum results show the efficiency of our proposed approach. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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15 pages, 14505 KiB

Open AccessArticle

The CIPCA-BPNN Failure Prediction Method Based on Interval Data Compression and Dimension Reduction

by Linchao Yang, Guozhu Jia, Fajie Wei, Wenbing Chang, Chen Li and Shenghan Zhou

Appl. Sci. 2021, 11(8), 3448; https://doi.org/10.3390/app11083448 - 12 Apr 2021

Cited by 10 | Viewed by 1685

Abstract

This paper proposes a complete-information-based principal component analysis (CIPCA)-back-propagation neural network (BPNN)_ fault prediction method using real unmanned aerial vehicle (UAV) flight data. Unmanned aerial vehicles are widely used in commercial and industrial fields. With the development of UAV technology, it is imperative [...] Read more.

This paper proposes a complete-information-based principal component analysis (CIPCA)-back-propagation neural network (BPNN)_ fault prediction method using real unmanned aerial vehicle (UAV) flight data. Unmanned aerial vehicles are widely used in commercial and industrial fields. With the development of UAV technology, it is imperative to diagnose and predict UAV faults and improve their safety and reliability. The data-driven fault prediction method provides a basis for UAV fault prediction. A UAV is a typical complex system. Its flight data is a kind of typical high-dimensional large sample dataset, and traditional methods cannot meet the requirements of data compression and dimensionality reduction at the same time. The method used interval data to compress UAV flight data, used CIPCA to reduce the dimensionality of the compressed data, and then used a back propagation (BP) neural network to predict UAV failure. Experimental results show that the CIPCA-BPNN method had obvious advantages over the traditional principal component analysis (PCA)-BPNN method and could accurately predict a failure about 9 s before the UAV failure occurred. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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12 pages, 66715 KiB

Open AccessArticle

Reliability Analysis of Accelerated Destructive Degradation Testing Data for Bi-Functional DC Motor Systems

by Chinuk Lee, Munwon Lim, Chanjoong Kim and Suk Joo Bae

Appl. Sci. 2021, 11(6), 2537; https://doi.org/10.3390/app11062537 - 12 Mar 2021

Cited by 8 | Viewed by 2203

Abstract

An accelerated degradation test (ADT) has become a popular method to accelerate degradation mechanisms by stressing products beyond their normal use conditions. The components of an automobile are degraded over time or cycle due to their constant exposure to friction or wear. Sometimes, [...] Read more.

An accelerated degradation test (ADT) has become a popular method to accelerate degradation mechanisms by stressing products beyond their normal use conditions. The components of an automobile are degraded over time or cycle due to their constant exposure to friction or wear. Sometimes, the performance degradation can be measured only by destructive inspection such as operating torques of return-springs in a bi-functional DC motor system. Plastic deformation of the return-spring causes the degradation of actuating forces for shield movement, resulting in deterioration of the shield moving speed in a headlight system. We suggest a step-by-step procedure for a reliability analysis for a bi-functional DC motor in a headlight system, based mainly on accelerated destructive degradation test (ADDT) data. We also propose nonlinear degradation models to describe the ADDT data of the return-springs. Exposure effects of high temperatures on the return-springs are quantitatively modeled through the ADDT models. We compare the estimation results from both the closed-form expression and Monte Carlo simulation to predict the failure–time distribution at normal use conditions, showing that the lifetime estimation results from the closed-form formulation are more conservative. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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18 pages, 3369 KiB

Open AccessArticle

Integrating Modelling of Maintenance Policies within a Stochastic Hybrid Automaton Framework of Dynamic Reliability

by Simone Arena, Irene Roda and Ferdinando Chiacchio

Appl. Sci. 2021, 11(5), 2300; https://doi.org/10.3390/app11052300 - 5 Mar 2021

Cited by 11 | Viewed by 1956

Abstract

The dependability assessment is a crucial activity for determining the availability, safety and maintainability of a system and establishing the best mitigation measures to prevent serious flaws and process interruptions. One of the most promising methodologies for the analysis of complex systems is [...] Read more.

The dependability assessment is a crucial activity for determining the availability, safety and maintainability of a system and establishing the best mitigation measures to prevent serious flaws and process interruptions. One of the most promising methodologies for the analysis of complex systems is Dynamic Reliability (also known as DPRA) with models that define explicitly the interactions between components and variables. Among the mathematical techniques of DPRA, Stochastic Hybrid Automaton (SHA) has been used to model systems characterized by continuous and discrete variables. Recently, a DPRA-oriented SHA modelling formalism, known as Stochastic Hybrid Fault Tree Automaton (SHyFTA), has been formalized together with a software library (SHyFTOO) that simplifies the resolution of complex models. At the state of the art, SHyFTOO allows analyzing the dependability of multistate repairable systems characterized by a reactive maintenance policy. Exploiting the flexibility of SHyFTA, this paper aims to extend the tools’ functionalities to other well-known maintenance policies. To achieve this goal, the main features of the preventive, risk-based and condition-based maintenance policies will be analyzed and used to design a software model to integrate into the SHyFTOO. Finally, a case study to test and compare the results of the different maintenance policies will be illustrated. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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16 pages, 1953 KiB

Open AccessArticle

A New SORM Method for Structural Reliability with Hybrid Uncertain Variables

by Pidong Wang, Lechang Yang, Ning Zhao, Lefei Li and Dan Wang

Appl. Sci. 2021, 11(1), 346; https://doi.org/10.3390/app11010346 - 31 Dec 2020

Cited by 11 | Viewed by 1752

Abstract

(1) Background: in practical applications, probabilistic and non-probabilistic information often simultaneously exit. For a complex system with a nonlinear limit-state function, the analysis and evaluation of the reliability are imperative yet challenging tasks. (2) Methods: an improved second-order method is proposed for reliability [...] Read more.

(1) Background: in practical applications, probabilistic and non-probabilistic information often simultaneously exit. For a complex system with a nonlinear limit-state function, the analysis and evaluation of the reliability are imperative yet challenging tasks. (2) Methods: an improved second-order method is proposed for reliability analysis in the presence of both random and interval variables, where a novel polar transformation is employed. This method enables a unified reliability analysis taking both random variables and bounded intervals into account, simplifying the calculation by transforming a high-dimension limit-state function into a bivariate state function. The obtained nonlinear probability density functions of two variables in the function inherit the statistic characteristics of interval and random variables. The proposed method does not require any strong assumptions and so it can be used in various practical engineering applications. (3) Results: the proposed method is validated via two numerical examples. A comparative study towards a contemporary algorithm in state-of-the-art literature is carried out to demonstrate the benefits of our method. (4) Conclusions: the proposed method outperforms existing methods both in efficiency and accuracy, especially for cases with strong nonlinearity. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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17 pages, 22083 KiB

Open AccessArticle

Research on Reliability Evaluation Method of Aerospace Pyrotechnic Devices Based on Energy Measurement

by Yubo Zhu, Jili Rong, Qianqiang Song and Zhipei Wu

Appl. Sci. 2020, 10(22), 8200; https://doi.org/10.3390/app10228200 - 19 Nov 2020

Cited by 1 | Viewed by 1944

Abstract

High reliability is the basic requirement of aerospace pyrotechnic devices. Traditional reliability evaluation methods require a lot of tests, which become too expensive; therefore, the small-sample evaluation method is needed to reduce the cost. Using energy as a performance parameter can better reflect [...] Read more.

High reliability is the basic requirement of aerospace pyrotechnic devices. Traditional reliability evaluation methods require a lot of tests, which become too expensive; therefore, the small-sample evaluation method is needed to reduce the cost. Using energy as a performance parameter can better reflect the essence of the function of the pyrotechnic device compared to using force. Firstly, this article assumes that the strength obeys the normal distribution, and the stress is a constant; therefore, the reliability evaluation formula based on the t distribution is proposed. Then, taking the pin puller as the research object, four sets of energy measuring devices were developed so as to obtain its performance parameters. Finally, the evaluation results show that the pin puller has a high reliability of 0.9999999765 with a confidence level of 0.995. The reliability method proposed in this paper is a small-sample method for evaluating aerospace pyrotechnic devices, which can greatly reduce the cost of reliability evaluation. Moreover, the energy measuring devices developed in this paper can provide a new way of measuring performance parameters for piston-type pyrotechnic devices. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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14 pages, 5961 KiB

Open AccessArticle

A Study on Failure Analysis and High Performance of Hydraulic Servo Actuator

by Yong-bum Lee, Jong-won Park and Gi-chun Lee

Appl. Sci. 2020, 10(21), 7451; https://doi.org/10.3390/app10217451 - 23 Oct 2020

Cited by 3 | Viewed by 2716

Abstract

Hydraulic servo actuator is used as the core actuator in tensile compression fatigue life test equipment as it operates the micro displacement very precisely at a high frequency and can be used continuously for a long period of time. Recently, the life expectancy [...] Read more.

Hydraulic servo actuator is used as the core actuator in tensile compression fatigue life test equipment as it operates the micro displacement very precisely at a high frequency and can be used continuously for a long period of time. Recently, the life expectancy of automobiles has been extended, the load conditions of accelerated life testing on auto parts have been increased, and the life test time and number of tests have increased significantly in order to secure the reliability of the guaranteed life of produced vehicles. Therefore, hydraulic servo actuators mounted on accelerated life testing equipment for automotive parts are essential for much higher performance and a longer life than those tested. However, small- and medium-sized companies that supply test equipment for the fatigue life of auto often fail to develop technology due to a lack of research personnel and the development budget compared to the capabilities of large automobile manufacturers, resulting in frequent breakdowns due to the technical overload of test equipment. In this study, servo actuators were used to test automotive parts, with a maximum output of 2 ton, a maximum frequency of 3.3 Hz and a maximum displacement of 50 mm. The hydraulic servo actuator, which was installed in the tensile compression fatigue life test equipment, failed to operate normally at the site, and by analyzing it, we realized this resulted from the heat generation of insulation compression due to the accumulation of air and gas into the hydraulic oil and the increase in friction due to the deterioration of flow. A static pressure bearing was adopted as a design change to improve the root cause for this failure mode, and a very high level of geometric concentricity was secured by inserting concentric tubes outside the labyrinth seal type piston. The newly designed and manufactured actuator is the result of research that has achieved a semi-permanent long life and improved performance up to 100 Hz by non-contact operation. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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19 pages, 4788 KiB

Open AccessArticle

Influence of Drivetrain Hybridization on Transmission Lifetime

by Christian Habermehl, Georg Jacobs, Stephan Neumann and Kevin Weißenfels

Appl. Sci. 2020, 10(20), 7086; https://doi.org/10.3390/app10207086 - 12 Oct 2020

Cited by 2 | Viewed by 2252

Abstract

Parallel hybrid drivetrains for passenger cars have additional electric drives compared to conventional drivetrains. In the event of vehicle deceleration, the electric drives are operated as generators, thus recovering kinetic energy through regeneration. If these drives are positioned upstream of the transmission input, [...] Read more.

Parallel hybrid drivetrains for passenger cars have additional electric drives compared to conventional drivetrains. In the event of vehicle deceleration, the electric drives are operated as generators, thus recovering kinetic energy through regeneration. If these drives are positioned upstream of the transmission input, regeneration power must be transferred by the transmission. This creates additional loads on the individual machine elements, which has a negative effect on the transmission lifetime. This paper investigates the influence of hybridization in terms of regeneration on the lifetime of bearings as highly critical elements in a dual clutch transmission. The vehicle simulation model employed in this study consists of an internal combustion engine, an electric motor, a mechanical drivetrain and the vehicle body, as well as a driver and a simple operating strategy. In this model, a detailed transmission model including its controls is embedded to determine its component loads. The resulting load spectra are used in a methodical approach to calculate the bearing lifetime of the transmission. The results show that the additional regenerative power flow reduces the bearing lifetime so that additional loads must be taken into account in the development and operation of transmission systems. Full article

(This article belongs to the Special Issue Reliability Modelling and Analysis for Complex Systems)

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