scholarly journals Mechanism reliability and sensitivity analysis of landing gear under multiple failure modes

2021 ◽  
Vol 39 (1) ◽  
pp. 46-54
Author(s):  
Changcong Zhou ◽  
Mengyao Ji ◽  
Yishang Zhang ◽  
Fuchao Liu ◽  
Haodong Zhao
Keyword(s):  
Failure Probability ◽  
Failure Modes ◽  
Kriging Model ◽  
Landing Gear ◽  
Multiple Failure Modes ◽  
Analysis And Design ◽  
Extension System ◽  
Extension Mechanism ◽  
Assembly Error ◽  
Adaptive Kriging

For a certain type of aircraft landing gear retraction-extension mechanism, a multi-body dynamic simulation model is established, and the time-dependent curves of force and angle are obtained. Considering the random uncertainty of friction coefficient, assembly error, and the change of hinge wear under different retraction times, the reliability model is built including three failure modes of landing gear, i.e. blocking failure, positioning failure and accuracy failure. Based on the adaptive Kriging model, the reliability and sensitivity of retraction-extension system under the condition of single failure mode and multiple failure modes in series are analyzed, and the rule of reliability and sensitivity changing with the number of operations is given. The results show that the system failure probability of landing gear mechanism tends to decrease first and then increase when considering the given information of random factors, and the influences of random factors on the failure probability vary with the number of operations. This work provides a viable tool for the reliability analysis and design of landing gear mechanisms.

A global sensitivity analysis approach for multiple failure modes based on convex-probability hybrid uncertainty

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yidu Zhang ◽  
Yongshou Liu ◽  
Qing Guo
Keyword(s):  
Failure Probability ◽  
Failure Modes ◽  
Sensitivity Index ◽  
System Failure ◽  
Multiple Failure Modes ◽  
Content Type ◽  
Global Sensitivity ◽  
Sensitivity Indices ◽  
Independent Variable ◽  
Hybrid Uncertainty

Purpose This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty. Design/methodology/approach The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR. Findings The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty. Originality/value Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.

scholarly journals Addition laws of failure probability and their applications in reliability analysis of structural system with multiple failure modes

2012 ◽  
Vol 227 (1) ◽  
pp. 120-136 ◽  
Author(s):  
Pengfei Wei ◽  
Zhenzhou Lu ◽  
Longfei Tian
Keyword(s):  
Linear Programming ◽  
Failure Mode ◽  
Failure Probability ◽  
Failure Modes ◽  
Programming Model ◽  
Small Scale ◽  
Structural System ◽  
Third Order ◽  
Multiple Failure Modes ◽  
Basic Principles

Compared with the methods solving failure probability of the structural system with multiple failure modes, those solving failure probability of a single failure mode are simpler and more well-developed, thus in order to employ the latter to establish the former, the addition laws of the failure probability are derived mathematically by use of the basic principles of probability theory. In the derived addition laws, the failure probability of the structural system with n failure modes is expressed as a combination of the failure probabilities of 2 n−1 single failure modes. Therefore, the failure probability of the structural system with multiple failure modes can be solved by the well-developed methods for the failure probability of a single failure mode. After reviewing the boundary theories, such as the second-order boundary, the third-order boundary, and the linear programming based boundary for analyzing the failure probability of the structural system with multiple failure modes, the derived addition laws are applied to evaluate several former order joint failure probability involved in those boundary theories. Additionally, a new small-scale linear programming based boundary theory which can sufficiently reduce the scale of the linear programming model involved is proposed. Two numerical examples, including a series and a parallel structural system, are employed to demonstrate the accuracy and efficiency of proposed techniques.

Reliability Analysis and Design Considering Disjointed Active Failure Regions

2015 ◽  
Author(s):  
Pingfeng Wang ◽  
Xiaolong Cui ◽  
Zequn Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Failure Modes ◽  
Kriging Model ◽  
Engineering Systems ◽  
Random Input ◽  
Performance Function ◽  
Analysis And Design ◽  
Practical Engineering

Failure of practical engineering systems could be induced by several correlated failure modes, and consequently reliability analysis are conducted with multiple disjointed failure regions in the system random input space. Problems with disjointed failure regions create a great challenge for existing reliability analysis approaches due to the discontinuity of the system performance function between these regions. This paper presents a new enhanced Monte Carlo simulation (EMCS) approach for reliability analysis and design considering disjointed failure regions. The ordinary Kriging method is adopted to construct surrogate model for the performance function so that Monte Carlo simulation (MCS) can be used to estimate the reliability. A maximum failure potential based sampling scheme is developed to iteratively search failure samples and update the Kriging model. Two case studies are used to demonstrate the efficacy of the proposed methodology.

Reliability analysis of structural system with multiple failure modes and mixed uncertain input variables

2012 ◽  
Vol 227 (7) ◽  
pp. 1441-1453 ◽  
Author(s):  
Pengfei Wei ◽  
Zhenzhou Lu ◽  
Bo Ren
Keyword(s):  
Linear Programming ◽  
Failure Probability ◽  
Failure Modes ◽  
Structural System ◽  
Multiple Failure Modes ◽  
Random Inputs ◽  
Numerical Examples ◽  
Input Variables ◽  
Uncertain Input ◽  
The Membership Function

In the design of engineering structure, uncertainties can be modeled as randomness or fuzziness depending on the amount of information available. In this article, the estimation of failure probability of structural system with multiple failure modes and mixed (random and fuzzy) inputs is considered. We firstly review the addition law of failure probability and a linear programming based bound method, and then these two techniques are combined to deal with structural system with multiple failure modes and only random inputs. Eventually, this method is extended for estimating the membership function of the failure probability of structural system with both random and fuzzy inputs. This method is computationally cheap, especially for the structural system with a large number of failure modes. Several numerical examples are introduced for demonstrating the efficiency and accuracy of the proposed method.

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