The gear door lock system (GDLS) is a hydraulic and mechatronic system with high degree of complexity and uncertainty, making the performance assessment of the system especially intractable. We develop copula models to estimate the reliability of GDLS with dependent failure modes. Based on the working principle of the GDLS, kinematic and dynamic model with imperfect joints is built in which Latin hypercube sampling (LHS) and kernel smoothing density are utilized to obtain the marginal failure probabilities. Then, copula models are utilized to describe the dependence between the two function failure modes. Furthermore, to be more accurate, mixed copula models are developed. The squared Euclidean distance is adopted to estimate the parameters of the above reliability models. Finally, the Monte Carlo simulation is conducted to evaluate different reliability models.
Issue Section:
Research Papers
References
1.
Zhang
, L. G.
, Lu
, Z. Z.
, Cheng
, L.
, and Fan
, C. Q.
, 2014
, “A New Method for Evaluating Borgonovo Moment-Independent Importance Measure With Its Application in an Aircraft Structure
,” Reliab. Eng. Syst. Saf.
, 132
, pp. 163
–175
.2.
Wei
, P. F.
, Song
, J. W.
, Lu
, Z. Z.
, and Yue
, Z. F.
, 2016
, “Time-Dependent Reliability Sensitivity Analysis of Motion Mechanisms
,” Reliab. Eng. Syst. Saf.
, 149
, pp. 107
–120
.3.
Guo
, W.
, Cui
, W. M.
, and Shi
, Y.
, 2016
, “Function Failure and Failure Boundary Analysis for an Aircraft Lock Mechanism
,” Eng. Failure Anal.
, 70
, pp. 428
–442
.4.
Jiang
, C.
, Zhang
, W.
, and Han
, X.
, 2015
, “A Vine-Copula-Based Reliability Analysis Method for Structures With Multidimensional Correlation
,” ASME J. Mech. Des.
, 137
(6
), p. 061405.5.
Pang
, H.
, Yu
, T. X.
, and Song
, B. F.
, 2016
, “Failure Mechanism Analysis and Reliability Assessment of an Aircraft Slat
,” Eng. Failure Anal.
, 60
, pp. 261
–279
.6.
Mavris
, D.
, Mantis
, G.
, and Kirby
, M.
, 1997
, “Demonstration of a Probabilistic Technique for the Determination of Aircraft Economic Viability
,” AIAA
Paper No. 975585.7.
Zhang
, J.
, Messac
, A.
, Zhang
, J.
, and Chowdhury
, S.
, 2012
, “Improving the Accuracy of Surrogate Models Using Inverse Transform Sampling
,” AIAA
Paper No. 2012-1429. 8.
Brown
, A.
, DeHaye
, M.
, and DeLessio
, S.
, 2013
, “Probabilistic Methods to Determine Resonance Risk and Damping for Rocket Turbine Blades
,” J. Propul. Power
, 29
(6
), pp. 1367
–1373
.9.
Nelsen
, R. B.
, 2006
, An Introduction to Copulas
, 2nd ed., Springer
, New York
.10.
Wang
, Y.
, and Pham
, H.
, 2012
, “Modeling the Dependent Competing Risks With Multiple Degradation Processes and Random Shock Using Time-Varying Copulas
,” IEEE Trans. Reliab.
, 61
(1
), pp. 13
–22
.11.
Tang
, X. S.
, Li
, D. Q.
, Zhou
, C. B.
, Phoon
, K. K.
, and Zhang
, L. M.
, 2013
, “Impact of Copulas for Modeling Bivariate Distributions on System Reliability
,” Struct. Saf.
, 44
, pp. 80
–90
.12.
Eryilmaz
, S.
, 2014
, “Multivariate Copula Based Dynamic Reliability Modeling With Application to Weighted-k-Out-of-n Systems of Dependent Components
,” Struct. Saf.
, 51
, pp. 23
–28
.13.
An
, Z. W.
, 2015
, “Reliability Copula Model for Wind Turbine Gearbox Based on Failure Correlation
,” J. Shanghai Jiaotong Univ. (Sci.)
, 20
(3
), pp. 312
–316
.14.
An
, Z. W.
, and Sun
, D.
, 2017
, “Reliability Modeling for Systems Subject to Multiple Dependent Competing Failure Process With Shock Loads Above a Certain Level
,” Reliab. Eng. Syst. Saf.
, 157
, pp. 129
–138
.15.
Li
, D. Q.
, 2015
, “Bivariate Distribution of Shear Strength Parameters Using Copulas and Its Impact on Geotechnical System Reliability
,” Comput. Geosci.
, 68
, pp. 184
–195
.16.
Tang
, X. S.
, Li
, D. Q.
, and Zhou
, C. B.
, 2013
, “Bivariate Distribution Models Using Copulas for Reliability Analysis
,” J. Risk Reliab.
, 227
(5
), pp. 499
–512
.17.
Nikravesh
, P. E.
, 1988
, Computer-Aided Analysis of Mechanical Systems
, Prentice Hall
, Englewood Cliffs, NJ
.18.
Garcia de Jálon
, J.
, and Bayo
, E.
, 1994
, Kinematic and Dynamic Simulations of Multibody Systems
, Springer-Verlag
, New York
.19.
Flores
, P.
, Ambrosio
, J.
, Claro
, J. C. P.
, and Lankarani
, H. M.
, 2008
, Kinematics and Dynamics of Multibody Systems With Imperfect Joints
, Springer
, Berlin
.20.
Lankarani
, H. M.
, and Nikravesh
, P. E.
, 1990
, “A Contact Force Model With Hysteresis Damping for Impact Analysis of Multibody Systems
,” ASME J. Mech. Des.
, 112
(3
), pp. 369
–376
.21.
Ambrósio
, J. A. C.
, 2002
, “Impact of Rigid and Flexible Multibody Systems: Deformation Description and Contact Models
,” Virtual Nonlinear Multibody Systems
, Vol. 2
, W.
Schiehlen
and M.
Valásek
, eds., NATO Advanced Study Institute
, Lisboa, Portugal, pp. 15
–33
.22.
Elsayed
, E. A.
, 2012
, Reliability Engineering
, 2nd ed., Wiley
, Hoboken, NJ
.23.
Clint
, S.
, 2008
, “Use of the Lognormal Distribution for the Coefficients of Friction and Wear
,” Reliab. Eng. Syst. Saf.
, 93
(10
), pp. 1574
–1576
.24.
Helton
, J. C.
, and Davis
, F. J.
, 2003
, “Latin Hypercube Sampling and the Propagation of Uncertainty in Analyses of Complex Systems
,” Reliab. Eng. Syst. Saf.
, 81
(1
), pp. 23
–69
.25.
Shu
, Z.
, and Jirutitijaroen
, P.
, 2011
, “Latin Hypercube Sampling Techniques for Power Systems Reliability Analysis With Renewable Energy Sources
,” IEEE Trans. Power Syst.
, 26
(4
), pp. 2066
–2073
.26.
der Kiureghian
, A.
, and Liu
, P. L.
, 1986
, “Structural Reliability Under Incomplete Probability Information
,” J. Eng. Mech.
, 112
(1
), pp. 85
–104
.27.
Richard
, D. D.
, Adrian
, W. B.
, and Adelchi
, A.
, 1997
, Applied Smoothing Techniques for Data Analysis
, Oxford University Press
, New York
.28.
Han
, W. Q.
, 2011
, “Copula Analysis of Structural Systems Reliability With Correlated Failure Mode
,” China Mech. Eng.
, 22
(3
), pp. 278
–282
.29.
Cornell
, C. A.
, 1967
, “Bounds on the Reliability of Structural Systems
,” J. Struct. Div.
, 93
(1
), pp. 171
–200
.30.
Ditlevsen
, O.
, 1979
, “Narrow Reliability Bounds for Structural Systems
,” J. Struct. Mech.
, 7
(4
), pp. 453
–472
.31.
Liu
, J. S.
, 2001
, Monte Carlo Strategies in Scientific Computing
, Springer-Verlag
, New York
.32.
Binder
, K.
, 1984
, Application of the Monte Carlo Method in Strategies Physics
, Springer-Verlag
, Berlin
.33.
Wu
, Y. J.
, and Sitakanta
, M.
, 2006
, “Variable Screening and Ranking Using Sampling-Based Sensitivity Measures
,” Reliab. Eng. Syst. Saf.
, 91
(6
), pp. 634
–647
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